Misconfigured components in production remain one of the most common—and most preventable—sources of security risk. To help you better understand and prioritize your organization’s misconfiguration issues, Dynatrace Security Posture Management (SPM) introduced severity classification labels for all misconfiguration findings based on the Common Configuration Scoring System (CCSS). CCSS provides a standardized, vendor-agnostic way of assessing configuration weaknesses that allows for clear, consistent scoring across diverse environments.

By aligning our findings with CCSS, teams can now compare misconfigurations across different frameworks, benchmarks, and technology stacks using a unified metric. This not only improves prioritization and triage but also strengthens communication between security, operations, and compliance teams. Whether you’re evaluating a Center for Internet Security (CIS) benchmark, the Digital Operational Resilience Act (DORA) framework, or Defense Information Systems Agency Security Technical Implementation Guides (DISA-STIGs), severity is now measured on the same transparent and repeatable scale—making it easier than ever to focus on what matters most.

How Dynatrace determines misconfiguration severity levels

By leveraging CCSS, Dynatrace researchers and domain experts evaluate the severity of configuration weaknesses by scoring them using metrics that capture the intrinsic characteristics of each misconfiguration—such as how easy it is to exploit and its potential impact. These metrics are combined into a numerical score that maps to a severity level (low, medium, high, or critical), providing a consistent and repeatable way of measuring configuration risk.

Specifically, these metrics can be summarized along three focus areas:

• Likelihood (L): Measures how easily a misconfiguration can be exploited. It considers factors such as required access level, required system knowledge, authentication requirements, and whether exploitation is automated or manual.
• Technical Impact (TI): Assesses the degree to which a misconfiguration affects confidentiality, integrity, and availability if exploited.
• Configuration Impact (CI): Captures risk related to the misconfiguration itself—how significantly it weakens expected security controls or baselines.

How it works

Our security research team recently evaluated the Ensure that the –authorization-mode argument is not set to AlwaysAllow rule from the CIS Kubernetes benchmark. This check describes a configuration in which the Kubernetes API server allows all requests—this rule should not be used in any production environment.

Our internal researchers and Kubernetes experts assessed this rule as follows:

This assessment results in a severity classification of Critical, which is appropriate, as the CIS benchmark states that this configuration should not be used in a production Kubernetes cluster.

The severity of each misconfigured rule is tracked in the Dynatrace Security Posture Management app, where each rule’s severity label is assigned by a domain expert, ensuring the highest assessment quality.

Impact on the current rule severities in Security Posture Management

The new rule-severity level assessments in the Security Posture Management app will replace the current labels, which are based on different factors and vendor classification. While the current severity labels aren’t wrong, depending on the rule-benchmark vendor, they sometimes focus on different areas. For example, rules might be classified by how difficult they are to implement in a given configuration in a specific environment.

By adopting the Common Configuration Scoring System for all misconfiguration findings in Dynatrace SPM, we’re taking a major step toward delivering clearer, more transparent, and more actionable security insights. This standardized, expert-driven severity model ensures that every rule—across every benchmark—is evaluated with the same rigor and security-focused methodology. As a result, teams can make better-informed decisions, prioritize risk more effectively, and maintain a consistent understanding of configuration health across their entire environment. While some individual rule severities will change with the transition, the outcome is a stronger, more reliable foundation for managing configuration risk at scale.

What you need to do

With the new CCSS-based classifications, we ensure that each benchmark in SPM receives a unified, security-focused rule classification. The current severity label of a rule might change when the CCSS-based classification is deployed with Dynatrace version 1.334. If you’re on Dynatrace SaaS, this change will happen automatically when version 1.334 is rolled out in March 2026. If you’re on Dynatrace Managed, an update to Dynatrace Managed version 1.334 (or later) is required.

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Trusted vulnerability data empowers teams to make faster and clearer security decisions. That’s why we’re elevating the Dynatrace Vulnerabilities app with the Dynatrace Vulnerability feed: a new, native source of vulnerability intelligence that’s more accurate, transparent, and threat-aware, helping maintain strong coverage of critical risks. With curated inputs, stronger sourcing, and deeper integration across the Dynatrace platform, teams can prioritize what matters most—and act with confidence.

A native vulnerability feed: Agile, precise, and focused on real customer risk

We recognize how quickly noise and alert fatigue can slow vulnerability management. When teams face a high volume of security findings, they require accurate, timely, and reliable threat intelligence to address potential breaches and optimize remediation time, resources, and costs. That’s why Dynatrace is upgrading the Vulnerabilities app to use the Dynatrace vulnerability feed—a new, internally curated source of vulnerability data that replaces the previously used external feed. It delivers more accurate, timely, transparent, and threat-aware vulnerability information, tightly integrated with innovations from Dynatrace security researchers, already recognized through a European patent.

The Dynatrace Vulnerability feed is built on multiple reputable sources, including OSV.dev, GitHub, the National Vulnerability Database (NVD), and vendor advisories, providing comprehensive coverage of vulnerabilities. These insights are further curated and enriched by Dynatrace’s own findings and internal security research.

Key benefits for customers

The new Dynatrace Vulnerability feed is included in the Vulnerabilities app at no additional cost and offers:

• Trustworthy, high-quality, curated vulnerability data

• Clearer and more consistent vulnerability descriptions and remediation guidance
• Strong coverage of critical and high-severity vulnerabilities
• Improved accuracy for certain findings compared to the previous feed
• Better long-term agility: Dynatrace owns and evolves the feed based on customer needs

• Deeper integration with the Dynatrace platform.

Coverage and parity with the previous vulnerability feed

The Dynatrace Vulnerability feed provides full parity with the previously used feed for critical and high-severity vulnerabilities in customer environments. For medium- and low-severity vulnerabilities, we ensure over 90% coverage in customer environments compared to the previous feed, while also adding extra vulnerabilities that were not previously included. Certain medium- and low-criticality vulnerabilities, as well as those without a CVE number that exist solely in the previous feed, will be marked as deprecated (Figure 1).

We recognize that coverage is a key topic for organizations when it comes to vulnerabilities. The Dynatrace Vulnerability feed is designed to be dynamic, keeping pace with the large volume of newly reported vulnerabilities. This agility ensures timely updates to meet customer-specific coverage needs, reducing blind spots and protecting against emerging threats. This flexibility is one of the key reasons we decided to introduce our own feed.

What changes for existing vulnerabilities?

From an access and viewing standpoint, nothing changes for existing vulnerabilities. You can continue accessing vulnerability insights from the existing Vulnerabilities app, ensuring a seamless experience with minimal disruption.

Existing vulnerabilities from our previous feed will retain their CVE numbers, but the IDs will be replaced with the Dynatrace Vulnerability IDs (Figure 2). Vulnerabilities from the previous feed without a CVE number will be automatically marked as resolved.

If your organization drives vulnerability remediation through an IT Service Management (ITSM) tool like ServiceNow, your existing tickets remain unchanged regarding CVEs and Dynatrace IDs. Tickets linked to vulnerabilities outside the Dynatrace Vulnerability feed will still function, but when accessed, the vulnerabilities might be deprecated, have updated severity, or have an adjusted score.

Availability for SaaS vs. Managed: What You Need to Do

The Dynatrace Vulnerability feed is available in all Dynatrace SaaS environments starting with version 1.334. If you’re on Dynatrace SaaS, this change will happen automatically when version 1.334 is rolled out in March 2026.

If you’re on Dynatrace Managed, an update to version 1.334 (or later) is required to use the Dynatrace Vulnerability feed. Be sure to update to version 1.334 or later before April 1, 2027; otherwise, you’ll no longer be able to analyze vulnerabilities.

Not a Dynatrace customer yet? Try the Dynatrace Vulnerabilities experience in our Playground and see how threat-aware, curated vulnerability intelligence helps you cut through noise and focus on real risk.

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Established by the Government of Dubai, DESC sets rigorous cybersecurity standards to safeguard critical systems, promote secure cloud adoption, and support transformational smart city initiatives. DESC certification confirms that Dynatrace meets and exceeds these standards, giving Dubai government entities confidence to deliver seamless, secure digital services to their citizens.

Overcoming challenges in public sector IT compliance

Dynatrace collaborates closely with public sector organizations in the UAE and worldwide to support government and educational institutions in delivering secure, reliable, and efficient services. Such organizations are obliged to implement adequate controls to ensure the integrity and security of their data. Government agencies are under added pressure; as they continue to digitally transform and their data is distributed across multiple platforms and applications, the complexity of their systems increases. Delivering secure, resilient, and optimized operations within these environments requires a platform that provides actionable insights and intelligent automation from vast amounts of cloud data, all while adhering to stringent cybersecurity requirements.

Dynatrace: Certified solutions to complex problems

The Dynatrace® AI-powered observability platform is purpose-built to process and analyze massive volumes of data, with robust controls in place to protect customer data. The platform continuously invests in advanced capabilities to stay ahead of evolving market standards, as well as regional and sector-specific requirements. Key Dynatrace capabilities that help Dubai governmental entities protect their data include the following:

• End-to-end observability — Real-time insights into applications, infrastructure, and user experience across hybrid/multicloud environments.
• AI-powered automation — Predictive analysis, root-cause detection, and instant remediation to accelerate resolution.
• Application security — Continuous threat detection and automated mitigation aligned with DESC requirements.
• UAE data residency — While operating globally, Dynatrace stores UAE public-sector data securely within the UAE’s borders.
• Independent validation — Assessment against DESC’s cybersecurity framework by qualified third-party auditors.

Empowering secure digital transformation for Dubai’s public sector

Our partnership with Microsoft Azure UAE and the Dubai Government reflects a shared vision of creating smarter, safer, and more sustainable cities. Dynatrace’s intelligent observability and integrated security capabilities empower organizations to:

• Accelerate digital transformation with speed, confidence, and resilience.
• Enhance citizen experiences by delivering secure, high-performance, and reliable digital services.
• Foster trust by safeguarding data privacy and following UAE regulations.

Dubai’s ambition to lead the world in smart city innovation, sustainability, and digital empowerment is at the heart of this collaboration. Dynatrace’s achievement of DESC certification on Microsoft Azure in the UEA aligns seamlessly with this vision, delivering:

• A secure foundation for smart cities — Safeguarding interconnected systems that drive smart infrastructure and digital ecosystems.
• Enhanced citizen engagement — Enabling secure, seamless, and efficient services that elevate the quality of life for residents and visitors.
• Sustainability through efficiency — Harnessing AI-powered automation and intelligent observability to optimize resource consumption and operations, advancing Dubai’s environmental goals.

Together, we’re building the foundation for a future-ready digital ecosystem that empowers Dubai to thrive as a global leader in innovation, sustainability, and security.

Join us in shaping the future

At Dynatrace, we’re committed to driving innovation and helping organizations thrive in the digital age. Achieving DESC certification on Microsoft Azure in the UAE is just one of the many ways we’re delivering on this promise.

We invite all government agencies, critical non-government entities, and forward-thinking private sector organizations seeking secure, compliant, and innovative cloud solutions to discover what Dynatrace on Microsoft Azure in the UAE can do for the future of smart cities and secure digital transformation.

Get started today with a free trial and transform your own enterprise with an AI-powered observability platform, purpose-built for Azure cloud native and AI environments. Or start your free trial via the Azure Marketplace.

The post Dynatrace secures Dubai’s digital future with DESC certification appeared first on Dynatrace news.

Managing sensitive data in log files is getting even easier with Dynatrace. Our new Sensitive Data Center unifies privacy request workflow, data cleanup, and the new Sensitive Data Scanner to help you streamline working with sensitive data in Dynatrace. It allows teams to respond to data subject rights with confidence, remove records safely when required, and proactively discover and govern sensitive data ingested into Grail®. Sensitive Data Scanner will be available in a limited preview release by the end of 2025.

Handle sensitive data throughout your growing data ecosystem

Organizations face increasing pressure to demonstrate responsible practices for managing sensitive data while maintaining efficient operations and minimizing downtime. In addition to meeting end users’ data subject rights requests, such as the export or deletion of personal data, organizations must take proactive steps to prevent unnecessary exposure and storage of sensitive information. Achieving these objectives is challenging, especially with fragmented tools, siloed teams, and manual processes. As telemetry volumes increase, these inefficiencies lead to slower response times, higher operational overhead, and increased compliance risks.

Streamline privacy operations in Dynatrace with the Sensitive Data Center

The Sensitive Data Center brings privacy operations and sensitive data management together in a single app on the Dynatrace platform and complements existing privacy controls with an additional layer of control. Aligning scanning, cleanup, and data subject rights workflows with where your data resides helps teams reduce manual work and improve accuracy, all in a transparent process where every scan, cleanup, and request is logged and auditable, supporting your regulatory obligations with clarity and control.

Continuously scan for unintentionally ingested sensitive data in Logs on Grail

Imagine a service administrator who suspects that sensitive data might have been unintentionally ingested in their observability data. They need a quick way to confirm whether it happened and, if so, where the sensitive data resides and what type of sensitive data is affected—ideally without having to build custom scripts or pull engineers off priority work. The Sensitive Data Scanner is a new module in the Sensitive Data Center that helps you discover sensitive data at the time of ingestion, allowing you to govern it more effectively in three steps:

1. Configure the scanner
2. Review the scan results
3. Mitigate any potential findings

Configure scans in the Sensitive Data Scanner

The setup is straightforward. You can choose to monitor specific buckets or the entire environment. Select the sensitive data type or types from built-in rules such as email, credit card, or IP address. You can set up several fine-grained scans with different scopes to accommodate different scan areas. A scan runs at a defined cadence every 6, 12, or 24 hours, depending on your compliance needs, and alerts you when data matching the selected criteria is found.

Review scan results

A dashboard provides a clear overview of scan statuses and highlights when sensitive data is found. From there, you can drill down into a specific scan to review detailed findings and understand exactly what was detected.

You can review the results and examine the data flow from ingestion to the storage location.

Mitigate potential findings

With these results, you can immediately take action. You can configure or adjust masking rules to prevent similar data from being ingested in the future, change access to stored data, update retention periods, or utilize the cleanup functionality to delete the data as needed.

Sensitive Data Scanner preview

The Sensitive Data Scanner will be available in a preview release by the end of 2025. As we gather feedback, we will continue to refine the experience and expand coverage, allowing teams to move confidently from identification to action within the same app.

Act decisively with precise, auditable cleanup

Data cleanup is available directly within the Sensitive Data Center, allowing you to take action when your organization’s regulatory obligations or policies require the removal of data.

The “Cleanup data” workflow in Sensitive Data Center allows you to easily locate, review, and delete an entire time frame of data, as well as any selected individual records that contain sensitive data defined in your DQL search query. To improve accuracy and minimize the risk of accidentally deleting data, you can also select a reviewer who will review and approve deletion requests before the data is deleted. Learn more about deleting data in Grail.

Efficiently locate, export, and delete end users’ personal data

Let’s walk through another common scenario. The services administrator, ensuring Dynatrace is operating smoothly, receives an urgent request from the privacy legal team: “Please locate, compile, and delete all personal data associated with this email address in Dynatrace as part of our end-user’s right to be forgotten.” Privacy requests in the Sensitive Data Center offer an end-to-end experience for managing data subject rights requests within the Dynatrace platform, allowing for quick, compliant, and efficient handling of sensitive data.

Dynatrace empowers you with a ready-made solution for submitting, tracking, and verifying the status of requests. With a user interface designed for compliance needs, you can efficiently manage data export and deletion requests. A dashboard summarizes key details, including the request reference, status, and due date alignment.

Together, scanning and cleanup ensure that only the sensitive data you intend to process is stored in Logs on Grail, while privacy requests provide the workflows and approvals necessary to comply with user privacy rights for lawfully processed personal data.

This blog may contain forward-looking statements about our product plans, upcoming features, and anticipated improvements.  These statements are for informational purposes only and are not promises or guarantees.  The development, release, and timing of any features or functionality described remain at the sole discretion of Dynatrace LLC and may be modified, delayed, or canceled without notice.  We encourage readers to make decisions based on the product’s current capabilities and features.

The post Unified privacy and sensitive data management for logs with the Sensitive Data Center appeared first on Dynatrace news.

Kubernetes has rapidly established itself as a cornerstone technology for deploying and managing applications at scale. It’s designed to streamline operations and offer considerable potential for fostering carbon-friendly applications by including automated deployment and dynamic scalability, which allow for efficient resource allocation and significant savings through optimized container orchestration. With its intelligent provisioning of containers, Kubernetes aims to optimize the use of underlying resources, ultimately leading to better infrastructure utilization compared to traditional, often over-provisioned, approaches.

However, the increasing complexity of Kubernetes environments necessitates active and diligent management of their carbon footprint. Mainly because, despite their promise of efficiency, if not properly managed, Kubernetes environments can paradoxically lead to excessive carbon emissions.

Measure Kubernetes energy consumption and carbon footprint

With the latest release of Cost & Carbon Optimization, Dynatrace now provides reporting and analytics for your Kubernetes infrastructure, allowing you to understand the carbon footprint (both energy and carbon emissions – CO2 equivalent) of Kubernetes clusters, namespaces, and nodes. You can now measure and determine whether the utilization of Kubernetes resources justifies their carbon footprint, identify anomalies and trends, and compare this against emissions from physical or single-use host infrastructure to ensure that migrating workloads to Kubernetes provides an appropriate sustainability return on investment.

Supporting all modes of Kubernetes monitoring, whether deployed in the cloud or on-premises, Cost & Carbon Optimization offers the following capabilities for your Kubernetes environment:

• Understand the energy and carbon footprint of Kubernetes clusters and namespaces with the new Kubernetes explorer interface.
• Highlight optimization opportunities by correlating the carbon footprint with the size of the cluster or node via Kubernetes metrics.
• Confirm if sustainability or optimization efforts deliver the assumed results with automatic time-period comparisons.
• Inspect resource requests and limits, quotas, or idle workloads/jobs that reserve resources but run infrequently with one-click contextual navigation into the Kubernetes app.
• Create custom reports using Notebooks or Dashboards
• Calculate your carbon footprint without installing additional complex Kubernetes plug-ins or configurations by leveraging information from your existing Dynatrace Kubernetes platform monitoring.
• Provide accurate measurements by using certified energy and carbon calculation algorithms.

Why bother with setting up a sustainable Kubernetes environment?

If you already use Kubernetes, or plan to migrate workloads to Kubernetes, you should consider using Dynatrace Cost & Carbon Optimization today to unlock the following benefits:

• Energy use is a direct driver of cost: Cloud infrastructure costs are largely driven by energy consumption. CPU, memory, storage, and networking all consume power, and cloud providers factor this into pricing. By measuring energy usage, you can track the underlying metric that influences cost.
• Carbon footprint adds environmental context: Carbon footprint translates energy consumption into environmental impact. This is especially valuable for organizations with sustainability goals or Environmental, Social, and Governance (ESG) reporting requirements.
• Opportunities to align cost and environmental optimization: Inefficient clusters, namespaces, and nodes that consume more energy (and thus emit more carbon) are often the ones driving up cloud costs. Identifying high-carbon workloads can highlight areas for both cost and environmental optimization.

Practical examples

Once activated, you can easily identify the Kubernetes clusters and namespaces with the highest energy consumption and carbon emissions, and correlate this with additional metrics from Dynatrace Kubernetes monitoring to identify the most costly and underutilized Kubernetes resources. Drill down from the Cost & Carbon Optimization app into Kubernetes to get more information on resource requests and limits, quotas, or idle workloads/jobs that reserve resources but run infrequently. Once identified, you can easily leverage this information to optimize your carbon and costs.

Use our ready-made dashboards to gain a deeper understanding of the data over time and identify anomalies that require further investigation. A large spike in energy and carbon usage could be a normal side effect of increased usage; it could also signal a change based on automatic scaling or inappropriate resource provisioning.

But why stop with focusing on your existing infrastructure only? Measure and compare carbon emissions from single-use servers against Kubernetes infrastructure and ensure that migration efforts meet the desired sustainability goals. You can even start gamifying this and challenge your engineering teams to develop solutions that delight end-users and the environment.

Start optimizing costs & carbon

If you’re already monitoring your Kubernetes infrastructure with Dynatrace, measuring Kubernetes energy consumption and emissions is as simple as installing and activating the Cost & Carbon Optimization app from Dynatrace Hub.

The app is available to all Dynatrace SaaS customers and leverages capabilities outlined in your rate card, supporting all Dynatrace Kubernetes monitoring modes. Are you interested in learning more? Do you know that Dynatrace Cost & Carbon Optimization is certified for accuracy and transparency? Have a look at our documentation and learn how to calculate and monitor your IT costs and carbon footprint. Then use the link below to install Cost & Carbon Optimization in your Dynatrace environment.

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The NVIDIA Enterprise AI Factory addresses the rapidly evolving needs for AI infrastructure to support the rise of agentic AI. Since its launch, customers have leveraged this validated design to build agents by following structured methodology and recommended frameworks, which simplifies deployment and configuration while facilitating the implementation of AI factories in both on-premises and hybrid cloud environments.

Dynatrace has been an integral part of this initiative. Dynatrace full-stack AI and LLM observability helps organizations move forward with confidence in building their AI and agentic AI initiatives.

Observable AI: Turn a black box into a glass box to build confidence

With the publication of comprehensive guidelines, it’s simpler than ever for Dynatrace customers to set up and start monitoring their full-stack NVIDIA enterprise AI infrastructure, including its key tiers and components. Covering the infrastructure layer from GPUs to Kubernetes, NVIDIA NIM microservices, NVIDIA NeMo, and other technologies up to the application layer, Dynatrace observability enables customers to confidently run and operate complex AI workflows on NVIDIA infrastructure.

In parallel, Dynatrace has worked to significantly advance our AI and LLM observability offering by introducing the following:

• A dedicated app experience for AI observability with out‑of‑the‑box analytics, auto‑instrumentation, targeted metrics, a debugging flow, and ready‑made dashboards.
• Data governance and audit trails for AI services, turning governance into a competitive advantage.
• Model versioning and A/B testing to compare model performance across versions.
• Multi-modal agent explainability and tracing throughout RAG pipelines and agentic frameworks.

These improvements address challenges such as missing observability insights, scale, sovereignty, and trust. This empowers organizations to operationalize AI by building trust and monitoring guardrails; providing analytics capabilities to detect user-facing issues; helping SREs and AI-native engineers maintain performance, reliability, and security; and reducing cost across the agentic, AI, and LLM stack.

Privacy and security lead the way to scaling AI with confidence

AI is delivering significant productivity improvements, with 66% of senior executives reporting positive trends in productivity, according to PwC’s AI Agent Survey. This momentum is driving the demand to manage AI expenditures, enhance the decision-making quality of agents, and optimize development through visibility into AI components’ behavior in production environments — from pilot projects to full-scale operations.

However, sensitive data considerations and strict compliance requirements often impede progress, preventing organizations from fully realizing the benefits of AI adoption. As enterprises prioritize data privacy, regulatory compliance, and data sovereignty, there is an increasing need for high-performance NVIDIA AI infrastructure alongside frameworks designed to preserve control, trust, and autonomy in AI development.

In a recent blog on sovereign AI, NVIDIA shares strategies for nations and enterprises to develop AI factories that uphold local governance, security, and cultural values. Combining such factories with the Dynatrace advanced observability solution enables organizations to operationalize AI at scale — building secure and scalable agents, deployed on premises or in hybrid environments.

From privacy needs to public-sector requirements: NVIDIA AI Factory for Government

At NVIDIA GTC Washington, D.C. today, NVIDIA AI Factory for Government was announced, in support of the needs for regulated environments to drive AI initiatives. The U.S. Office of Management and Budget’s decision to establish scorecards for agencies’ AI maturity and management is in line with a 2024 Gartner Research forecast that more than 60% of government organizations will be prioritizing their investments in business automation by 2026 — up from 35% in 2022. The NVIDIA AI Factory for Government is a full-stack, end-to-end reference design that brings the power of reasoning AI to federal organizations. It helps organizations unlock productivity gains just like it does for enterprises, from service delivery to threat detection and day-to-day operations.

Built on the experience of deploying internal AI factories, the reference design offers guidance for deploying agentic AI, physical AI, and high-performance computing workloads on premises and in hybrid cloud environments, while meeting the compliance needs of federal and other secure organizations. The NVIDIA AI Factory for Government reference design includes NVIDIA Blackwell accelerated computing and NVIDIA networking, NVIDIA-Certified Systems, NVIDIA AI Enterprise software, NVIDIA Nemotron open models, and third-party software from AI leaders, all validated by NVIDIA.

Dynatrace delivers trusted observability and automation for regulated environments

Dynatrace has always been committed to supporting the public sector and other industries with regulatory requirements by providing customers with capabilities to control data flow through its lifecycle and manage sensitive data from ingestion to deletion, as well as global deployment options to meet data residency requirements, configurable retention times for different data types and use cases, unique encryption keys for customer’s stored data, and more.

Our dedication is reflected in customers’ success stories from regulated industries, as well as a growing list of global and local certifications, such as ISO 27001, SOC 2 Type II, CSA STAR 2, ENS, Tisax, and others. Find out more about our certifications and supported compliance frameworks in our Trust Center. For organizations also navigating evolving sovereignty requirements, our approach to digital sovereignty demonstrates how Dynatrace combines technical innovation with policy alignment to deliver trusted solutions globally.

Benefit from full-stack observability for end-to-end validated design

Dynatrace observability with the NVIDIA AI Factory for Government reference design enables organizations to accelerate the deployments of their AI agents and applications for federal and enterprise environments, and benefit from real-time, AI-powered insights.

These benefits range from improved scalability and performance to reduced complexity and total cost of ownership by simplifying processes, mitigating deployment risks to improved data security and compliance.

Visit the Dynatrace Playground to experience the possibilities of AI and LLM observability, and discover how Dynatrace is accelerating enterprise AI at scale.

Dynatrace and the Dynatrace logo are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners.

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The value of automation and agentic AI

The Dynatrace® AI-powered observability and security platform, with its remote Model Context Protocol (MCP) server, revolutionizes this process by integrating observability context into automation and agentic AI-driven workflows. By connecting Dynatrace with GitHub Copilot coding agent, organizations can achieve prioritized and automated vulnerability remediation that not only streamlines security but also maintains system performance and developer efficiency.

Both developers and site reliability engineers (SREs) benefit from this agentic AI collaboration, bringing actionable runtime insights from Dynatrace directly into GitHub and efficiently automating vulnerability remediation.

Automated security remediation with smart runtime verification use case

GitHub Dependabot proactively alerts developers when known vulnerabilities are detected in their projects’ dependencies, helping teams stay secure and compliant. As organizations and projects scale, prioritizing and addressing the alerts becomes a challenge: deciding which vulnerabilities matter most in a given context and streamlining the path to remediation.

Let’s dig deeper into two different scenarios, where Dynatrace can help to improve remediation by automating developer tasks and prioritizing work based on impact.

To optimize remediation efforts and minimize release delays, it’s essential to prioritize vulnerabilities based on their actual impact on production applications.

Dynatrace providing context for automating the remediation of GitHub Dependabot alerts

In a typical environment, when streamlining vulnerability remediation, you might utilize GitHub Actions workflows to regularly poll Dependabot. Once a new alert is detected, the workflow creates a new issue and assigns it to the GitHub Copilot coding agent.

To fully understand the problem and its impact, GitHub Copilot coding agent queries Dynatrace—using the remote MCP server—to get additional runtime data. Dynatrace confirms that the vulnerable library is loaded, and that its own Runtime Vulnerability Analytics (RVA) identifies the same issue and verifies the impact by highlighting if the vulnerable function is used in live environments and if it’s exploitable.

Equipped with the additional context, the coding agent generates a code-level fix. To remediate and prevent insecure code, the fix is added as a pull request to the GitHub repository, awaiting developer review to ensure human oversight.

Once the change is approved and the fix deployed, Dynatrace continuously monitors the environment, verifying the remediation and ensuring the issue is resolved without introducing new problems.

Automate and orchestrate security findings from GitHub Dependabot with Dynatrace Workflows

Unifying and contextualizing vulnerability findings across different tools helps apply prioritization and centralize automation for real-time runtime validation and fix deployment, supporting SREs to minimize potential disruptions to their services.

With the Dynatrace integration for GitHub Advanced Security, you can continuously forward GitHub Dependabot alerts to Dynatrace. Once ingested, Dynatrace uses its capabilities for further analysis, including an RVA verification that provides a contextual understanding of the potential impact on the monitored environment.

The workflow creates a new GitHub issue, including a comprehensive summary of alerts with their confirmation status.

GitHub Copilot Coding Agent automatically picks up the issue and submits the proposed fix for verified alerts as a pull request for a developer to review. This ensures the remediation process remains transparent and allows for human oversight before deployment. Once the pull request is approved and merged, the alert is remediated and the code is secured.

Automated end-to-end security remediation

These two scenarios exemplify how organizations can shift from reactive to proactive security management, automating repetitive tasks and providing actionable insights for developers.

The relationship between Dynatrace and GitHub demonstrates the power of agentic AI in modern software development, where runtime data drives decision-making and empowers coding agents to apply fixes to code environments—all in a standardized way, applying enterprise guardrails.

Reduce your mean time to resolution (MTTR), enhance developer productivity, and ensure robust system security by automating security remediation—all without sacrificing performance or uptime.

The benefits of the coding agent are further amplified with the GitHub announcement of introducing custom agents. Dynatrace has just launched its first custom agent, which seamlessly integrates Dynatrace’s observability and security capabilities into GitHub Copilot, empowering teams to maintain operational excellence, ensure application reliability, and uphold security compliance across the entire software development lifecycle (SDLC).

This allows teams to streamline incident response, perform root cause analysis, validate deployments, triage production errors, and many more use cases—all directly within their GitHub repository workflows.

By delivering real-time insights and actionable data from production environments, Dynatrace extends GitHub’s reach into production, effectively closing the SDLC. Stay tuned for our upcoming blog, where we’ll dive deeper into the powerful capabilities of Dynatrace’s custom agent for GitHub Copilot.

Ready to transform your security workflows?

Explore how Dynatrace can integrate seamlessly into your development landscape using our remote MCP Server and read through our walkthrough documentation.

Sign up for the preview and experience how real-time production context makes your organization more efficient.

The post Hands-free vulnerability remediation with Dynatrace and GitHub Copilot appeared first on Dynatrace news.

Rising cybersecurity risks in the public sector

Modern public sector organizations manage and store increasingly large volumes of sensitive data, elevating cloud security as a top priority. At the same time, these organizations face mounting pressure to innovate and modernize, all while maintaining rigorous standards for data protection and regulatory compliance.

Qualification of cloud infrastructure and services is a central pillar of the Italian Cloud Strategy, issued by the Department for Digital Transformation and the Agenzia per la Cybersicurezza Nazionale (ACN). The strategy provides guidelines for migrating data and digital services of the Italian Public Administration to the cloud, ensuring that security and resilience are foundational at every stage.

To this end, the Italian government—through ACN—has established a robust framework for qualifying cloud solutions that manage all levels of public sector data and workloads. This framework ensures that only providers who meet strict criteria for security, reliability, and transparency are eligible to serve the public administration. The QC1 certification, in particular, is designed to simplify, regulate, and secure how cloud services are acquired by Italian administrative bodies. It aligns with the objectives of the National Cybersecurity Strategy, which aims to plan, coordinate, and implement measures to make Italy safer and more resilient.

For technology vendors, achieving ACN QC1 is not merely a regulatory requirement; it is a demonstration of trustworthiness and a prerequisite for participating in Italy’s digital future. Without this qualification, cloud solutions will not be considered by public sector entities—ultimately limiting both innovation and public benefit.

Empowering Secure Digital Transformation for Italy’s Public Sector

Dynatrace’s attainment of the ACN QC1 qualification directly addresses the complex requirements of Italy’s public sector. By certifying our platform against the rigorous standards established by the Italian Cloud Strategy and the ACN, Dynatrace allows public sector organizations to adopt advanced observability and automation aligned with the security, compliance, and resilience requirements defined by the ACN.

The Dynatrace platform represents a new era in observability, uniting analytics, AI, and automation to help organizations thrive in the age of agentic AI. The latest Dynatrace platform is engineered to contextualize vast streams of observability data, transforming it into real-time intelligence that powers actionable insights, automation, and the path toward autonomous operations.

QC1 certification confirms that Dynatrace has implemented comprehensive technical and organizational safeguards to protect data, prevent unauthorized access, and ensure the reliability of services. This independent validation gives public sector customers confidence that they can accelerate their digital transformation initiatives on a secure, compliant, and future-ready platform.

What ACN QC1 means for Dynatrace customers

With ACN QC1 qualification, Italian government agencies and public sector bodies can now confidently adopt Dynatrace for their mission-critical workloads. Key benefits include:

• Assured compliance: Independent validation that Dynatrace meets or exceeds all ACN QC1 requirements for managing ordinary data.
• Accelerated procurement: Simplified onboarding through the ACN marketplace, reducing procurement friction and time-to-value.
• Operational transparency: Ongoing alignment with Italian cybersecurity regulations, with clear documentation and audit readiness.
• Trusted innovation: Access to the full capabilities of the Dynatrace platform, enabling secure cloud native transformation and intelligent automation.

At Dynatrace, every certification we achieve unlocks a new level in our mission to empower our customers worldwide with cutting-edge, secure, and compliant solutions. Visit the Dynatrace Trust Center to review all our certifications and accreditations and to learn more about the Dynatrace approach to security and compliance by design.

The post Dynatrace achieves QC1 certification from the Italian Agency for National Cybersecurity appeared first on Dynatrace news.

We’re excited to announce that Dynatrace has been recognized as a Cloud Security Innovator in the Latio Pulse 2025 Cloud Security Market Report, authored by James Berthoty. This recognition validates the Dynatrace approach to bridging observability and security, and underscores our commitment to providing the runtime visibility and application-layer insights that modern cloud security demands.

Why we love this recognition

The cloud security landscape is undergoing a fundamental shift. According to the Latio report, traditional Cloud Native Application Protection Platforms (CNAPP) are evolving into more specialized categories, and runtime visibility is at the heart of this transformation.

The report highlights a critical insight: “Report after report has indicated that most cloud breaches are now beginning with web application attacks.” This validates what Dynatrace has been building toward for a while now: a Cloud Application Detection and Response (CADR) solution that understands applications at runtime, not just infrastructure in isolation.

As the report states, teams increasingly need “visibility into the application layer” to allow “meaningful runtime protection in the cloud.” And this is exactly where Dynatrace excels.

The application layer: Cloud security’s missing piece

For too long, cloud security platforms have focused primarily on infrastructure—containers, instances, and configurations, while overlooking the application layer where most attacks actually begin. The Latio report identifies this gap explicitly, saying  that CNAPPs “didn’t pay enough attention to the Application part.”

Dynatrace brings deep application-layer visibility that traditional security tools simply lack. Our foundation in observability gives Dynatrace unique insights into:

• Function-level execution visibility through OneAgent® and eBPF technology, helping teams to distinguish theoretical risks from real threats based on what actually runs in production
• Runtime telemetry that contextualizes security alerts with application performance data
• End-to-end traces that show exactly how attacks traverse through your environment
• Real-time monitoring of APIs, microservices, and serverless functions in dynamic cloud environments

All of this feeds into our Davis® Security Score (DSS), which translates observed application behavior into actionable insights by individually adjusting CVSS scores based on the actual risk of exposure for each vulnerability.

Observability-powered security: A natural evolution

The convergence of observability and security isn’t just a trend—it’s a necessity. As highlighted in the Latio report, over 60% of survey respondents identified Application Detection and Response (ADR) capabilities as the most exciting emerging feature for cloud security solutions.

This aligns perfectly with the Dynatrace approach. Traditional application security tools, like static AST, SCA, or vulnerability management platforms, still generate long lists of potential issues, leaving teams unsure which vulnerabilities truly matter in production. ADR and Cloud Application Detection and Response (CADR) bridge this gap by providing runtime and production insights, helping organizations focus on the vulnerabilities that actually create risk.

Dynatrace Cloud Security provides:

1. Complete visibility into digital environments with automatic dependency mapping and topology insights
2. Rich application context including function-level execution data, end-to-end traces, runtime telemetry, and API/microservice interactions, allowing security operations to understand the full story behind incidents and prioritize what truly matters
3. Real-time runtime protection that empowers teams to take immediate, autonomous action
4. Unified data brings security events, logs, traces, and user behavior into a single platform to prioritize, automate, and share information to those who need to act for more autonomous security processes.

What the Latio report says about Dynatrace

The Latio report specifically recognizes Dynatrace among vendors “expanding early functionality” in providing function-level reachability insights through OneAgent capabilities. This technology represents the cutting edge of runtime security, allowing teams to:

• Reduce false positives by identifying which vulnerabilities are actually reachable and exploitable in production
• Prioritize remediation efforts based on real risk, not theoretical severity scores
• Automatically detect and block attacks at the application layer without breaking functionality

The report emphasizes that “the difference these capabilities make within a tool are massive, and their relative importance will continue into 2026.”

Runtime Vulnerability Analytics: Prioritize what matters

One of the biggest challenges security teams face is the overwhelming volume of alerts that lack context and actionability. As we covered in our post on Runtime Vulnerability Analytics, traditional tools “overload you with data, making it challenging to identify which vulnerabilities actually put your environment at risk.”

Dynatrace takes this a step further, transforming vulnerability management from a manual process into an autonomous platform capability that not only prioritizes risks but actively drives remediation.

Here’s how Dynatrace solves this:

• Davis Security Score (DSS) adapts to your specific environment segments.
• Exposure-based prioritization focuses on assets vulnerable to internet-based threats or linked to sensitive data.
• Automated context enrichment eliminates noise and surfaces genuine threats.
• Cross-platform segmentation allows teams to focus on specific areas like payment processing systems.
• Integration of third-party findings (from tools like SCA, AST, or CNAPPs) applies Dynatrace prioritization intelligence across sources, reducing redundant findings and focusing on what truly matters.
• Closed-loop collaboration with developers operationalizes vulnerability management by automatically routing prioritized issues to the right owners—eliminating “man-in-the-middle” friction and accelerating resolution.

The Latio report’s emphasis on “runtime insights to prioritize reducing real risks” perfectly captures our approach. Dynatrace extends this further by making vulnerability management an integral, automated part of cloud operations.

Cloud Security Posture Management (CSPM) with real-time context

Beyond runtime detection, the Latio report highlights the continued importance of posture management—but with a critical evolution. As noted in our Cloud Security Posture Management announcement, “30% of all cloud environment attacks during the first half of 2024 used misconfigurations as the initial access vector.”

Dynatrace CSPM provides:

• Continuous monitoring across hybrid and multicloud environments.
• Automated remediation through workflow automation.
• Continuous compliance monitoring that helps meet strict regulatory timeframes.
• Centralized visibility that breaks down silos between SecOps and DevOps teams.

Protect AI workloads: The next frontier

The Latio report identifies AI security as a critical emerging capability, with 65% of survey respondents expressing strong interest in AI posture management. As AI adoption accelerates, so do the risks.

Our recent work on protecting Agentic AI applications demonstrates how the Dynatrace multi-layered approach, combining runtime vulnerability analytics, security posture management, and deep log investigation, provides robust defense for these dynamic AI environments.

This builds on Dynatrace AI observability innovations, which deliver deep visibility into AI pipelines, model interactions, and even prompt-level activity. These insights not only enhance reliability but also establish the foundation for agentic AI security, where taint tracking across AI agents helps detect and prevent unwanted data propagation or malicious behavior between systems.

The path forward: CADR represents the future

The Latio report introduces a new framework for understanding cloud security, moving beyond the “everything platform” approach of traditional CNAPPs to three specialized categories:

• Application Security Testing (AST) for developer-focused code security
• Continuous Threat Exposure Management (CTEM) for unified vulnerability management
• Cloud Application Detection and Response (CADR) for advanced runtime workload protection

At Dynatrace, we see CTEM not just as another tool category, but as a holistic program that requires process and organizational adaptation to be successful. CADR provides the technological foundation to make CTEM actionable: delivering the runtime insights, prioritization, and automation needed to continuously manage real-world exposure in dynamic cloud environments.

Dynatrace is recognized as an innovator in the CADR category, representing the future of runtime security. As the report states, CADR provides “the best runtime solution to protect cloud environments, and surface runtime telemetry for prioritization and threat detection.”

What this means for your security program

If you’re evaluating cloud security solutions, the Latio report provides guidance: architecture matters. For organizations running containerized workloads with complex microservices architectures, runtime visibility isn’t optional; it’s essential.

The report’s survey found that:

• Over 70% of respondents found posture findings to be most valuable when enriched with runtime context.
• Over 50% split their security tooling between posture and runtime capabilities.
• 64% indicated that their SOC team responds to runtime cloud security alerts.

This highlights the importance of solutions like Dynatrace that bridge security operations and development teams with unified, actionable insights.

Get started with Dynatrace Cloud Security

Whether you’re looking to:

• Consolidate security and observability into a single platform
• Use OneAgent for both observability and security capabilities
• Gain deeper visibility into your runtime environment
• Reduce vulnerability noise with context-aware prioritization
• Detect and respond to application-layer attacks in real time
• Or, secure AI workloads and agentic applications…

Dynatrace Cloud Security provides the comprehensive, context-driven protection your modern cloud environment demands.

As noted in our executive perspective on security compliance, “The benefits of cloud native architecture for IT systems come with the complexity of maintaining real-time visibility into security compliance and risk posture.” Dynatrace makes this complexity manageable through intelligent automation, unified data, and actionable insights.

Recognition driven by customer success

This recognition from Latio reflects the real-world impact Dynatrace Cloud Security delivers for customers. As we continue to innovate and expand our capabilities—from enriching Microsoft Defender findings to breaking down security silos with runtime context—we remain focused on solving the challenges our customers face every day.

It’s worth noting that Dynatrace pioneered this evolution back in 2019, introducing Runtime Vulnerability Analytics (RVA) long before runtime security became an industry trend. What has changed since then is not our vision, but the market’s recognition of the importance of our vision. Organizations are increasingly realizing that runtime visibility and application context are essential to effective cloud security.

With the third generation of Dynatrace Cloud Security, we’ve taken RVA even further, operationalizing it through automated workflows, developer integration, and cross-tool vulnerability ingestion and prioritization. These capabilities are critical for making runtime vulnerability analytics truly usable within customer organizations, turning insights into action at scale.

The evolution from traditional CNAPP to specialized categories like CADR isn’t just about new acronyms—it’s about recognizing that different teams need different capabilities, and that runtime visibility with application context represents the future of cloud security.

Ready to see how Dynatrace can transform your cloud security posture?

• Explore Dynatrace Cloud Security
• Start a free trial
• Contact us to discuss your specific security needs

Additional Resources

• Cloud Security and CADR: Revolutionizing cloud security with observability context
• Empowering SREs with Runtime Vulnerability Analytics
• Discover the new Runtime Vulnerability Analytics experience
• Elevate cloud security with real-time compliance

Dynatrace is proud to be recognized as a Cloud Security Innovator and remains committed to advancing the convergence of observability and security for the modern cloud era.

About Latio:  Latio is a modern security analyst firm redefining how organizations evaluate and select security solutions. Latio conducts hands-on testing, engages with stakeholders across all personas, and consolidates market insights to ensure organizations find the right security solutions for their needs.

About the Cloud Security Market Report:  The Cloud Security Market report delivers a comprehensive analysis of industry solutions, based on hands-on research and insights from practitioners and security leaders. It outlines critical functionality requirements, provides strategic buyer guidance, and examines emerging trends and innovation trajectories across the cloud security landscape.

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But we’d be remiss not to invite the creative and demanding cooks of the developer world into the kitchen itself. That’s why we’ve opened up access to the world-class environment we’ve built, complete with carefully sourced ingredients and precision tooling.

In that spirit, we follow a simple mantra: build for builders. We use what we ship, and ship what we build. That’s what drove the recent launch of the Dynatrace MCP Server, designed to equip developers with observability context and security. The result? Faster fixes, safer code, and superior performance.

But our commitment to developers goes even further. To ensure that our app teams can ship confidently and quickly, we’re focused on delivering exceptional developer experience: striving for faster, more reliable, and user-friendly tooling.

And because we share our tooling with customers and partners, every improvement we make benefits the broader community. That’s why we launched App Toolkit 1.0: a developer-first toolkit that reflects our commitment to support builders. It equips teams with the means to craft custom apps and solutions on the Dynatrace platform with greater speed, flexibility, and clarity.

From SREs building apps to automate quality gates and monitor MS Teams, to dev teams diving deep into CI/CD metrics down to commit ratios; from CMDB apps that transform Smartscape® data into dynamic configuration maps, to support staff tracking container metrics, our customers and partners have built one of the broadest and most versatile collections of custom apps on Dynatrace.

Accelerate developer productivity

The App Toolkit is the developer toolchain that’s designed to turn ideas into custom apps that extend the Dynatrace platform and deliver tailored solutions for your organization. From a single command line, developers can create, develop, and deploy apps, create new app functions, or update packages.

The focus of this release is on improving developer productivity, articulated through smarter builds, automation-ready design, and a streamlined UI. This makes it easier than ever to create, develop, and maintain Dynatrace Apps.

Smarter builds for enterprises

The App Toolkit 1.0 allows for smarter builds that dramatically cut development and deployment time while improving support for building large-scale apps. Key performance enhancements include the change detection system and enhanced type checking.

The new change detection system improves performance by only building and checking components with actual changes instead of scanning the entire codebase. This means that the dev server triggers re-builds whenever changes are made during development, ensuring that the latest updates are immediately reflected in the browser. This significantly optimizes rebuild times: going from an average of 2.7 seconds in the previous version to just 0.05 seconds, a 54-fold increase in speed.

Enhanced type checking operates seamlessly in the background when initializing a new workspace. Developers no longer need to wait for type checks to complete before proceeding. This allows teams to build custom apps for large codebases with hundreds of files, where comprehensive type checking is a bottleneck. The newly introduced incremental type checking ensures that recent changes and relevant code are prioritized, facilitating robust typing practices even in larger projects.

The combination of both features significantly accelerates feedback loops. Since only modified files and their dependencies undergo re-checking, with background type checking turned on, type errors are identified and resolved in a fraction of the time.

Automation-ready commands for CI/CD Efficiency

The App Toolkit 1.0 introduces an enhanced CLI designed for automation. Every command line can automatically run in scripts or pipelines, making it ideal for CI/CD. Commands that accept additional parameters can now be executed with arguments and options directly in the command line, instead of being prompted every time the CLI needs input. Builds and deployment processes stay automated, consistent, and repeatable, ultimately accelerating delivery.

A brand-new interface for faster, error-free development

The enhanced command line interface features a redesigned command structure. All available commands are now easier to discover and use consistently and intuitively. Each command now supports a comprehensive set of parameters as options, allowing developers to access the full capabilities of the in-pipeline automations.
The CLI has improved interactions for workflow continuity. For instance, when creating a function, the output now displays all generated files within a file tree, offering clear feedback on the results of each action.

The smarter workspace setup now features a distinct separation between the user interface components and Dynatrace app functions. This offers transparency into the workspace structure and minimizes errors, particularly relevant to enterprises dealing with increased application complexity and size. Furthermore, we’ve introduced suffixes for Dynatrace Apps functions and other conventions, significantly reducing configuration complexity.

Ready to get started?

Getting started with the App Toolkit is as straightforward as it is powerful. To kick off your build, ensure your environment meets the minimum requirements, then run the following command in your code editor terminal:

npx dt-app@latest create

Next, we recommend installing the Dynatrace Apps extension for VS Code or Cursor. For documentation, examples, and best practices, head over to Dynatrace Developer and explore everything you need to build with confidence.

The post Build Dynatrace® Apps faster, simpler, and smarter with the new App Toolkit appeared first on Dynatrace news.

Unless you’ve been living under a rock this past year, you’ve heard the buzz about how AI is changing the day-to-day lives of developers, whether it’s using LLMs for vibe coding or adopting agentic AI concepts to improve productivity. In particular, the introduction of Model Context Protocol (MCP) as a standard for connecting AI agents with other agents or tools has led to exponential growth in the number of solutions connecting AI coding assistants with APIs, databases, and more. Last month, GitHub, publisher of the prominent AI coding assistant GitHub Copilot, announced its new MCP registry as a place where developers can find links to MCP servers. This registry solves the challenge of numerous registries, repos, or community threads listing the same MCP servers.

We’re excited to share that the GitHub MCP registry now includes Dynatrace MCP, so developers can integrate Dynatrace observability and security analysis directly into their workflows.

In this blog post, we’ll explore how developers can use Dynatrace MCP together with GitHub Copilot to streamline troubleshooting, enhance security, and boost productivity—without ever leaving their IDEs.

Need to troubleshoot an issue? Dynatrace MCP has the answers

One of the biggest challenges in troubleshooting and observability is knowing where to look for missing data when issues arise in production. It might sound odd, but when you consider the sheer number of tools, applications, environments, and layers of source code developers need to navigate, it’s not at all clear where they should look for quick answers. No wonder onboarding time is such a major factor in engineering productivity.

Your day as a developer might start with a complaint about something not working correctly. You receive a Jira ticket with a cryptic error message that includes a link to a service health dashboard or a notification in the problem list. You start rummaging through the logs and dashboards to find answers outside your IDE, with little context. This greatly increases your cognitive load and delays the problem’s resolution.

Developers who use Dynatrace, though, don’t have to manually dig through logs and dashboards. They get clear summaries, root cause information, and all relevant data in the context of the affected service. Thanks to the updated problem flow, it’s easy for them to identify the root cause and remediate it.

Context is key

Now imagine a scenario in which your DevOps team uses MCP as their standard for integrating external tools and insights. As a developer, your instinct is to jump straight into the source code, so why not share as much context as possible right there? Utilizing GitHub Copilot with the Dynatrace MCP integration in place, you get all relevant data from your production environment and quickly isolate the problem, giving you the ability to:

• Get information on the root cause
• Query related logs, metrics, and traces
• Get real-time data from all environments, including production
• Leverage additional gathered insights, such as CPU and memory profiling, from the affected service
• Get further context using query patterns, such as “group logs by customer impact”

And the best is, you don’t need to know how or where to look—Dynatrace handles all this for you automatically. And there’s more: you can even ask Dynatrace for remediation suggestions.

_{Figure 2. Dynatrace identifies the problem root cause as an arithmetic exception, all via LLM and the MCP protocol in the developer VS Code IDE. (video)}

What’s happening behind the scenes

When you type a natural language prompt into the GitHub Copilot chat, GitHub’s MCP client establishes a connection with the Dynatrace MCP server, which then connects to Dynatrace. The LLM converts the prompt into a context-aware call and ultimately transforms it into a DQL query that it executes on Dynatrace Grail® data lakehouse, which retrieves the necessary data.

Need to fix a security issue? Dynatrace MCP has the answers

By integrating security testing practices earlier in the Software Development Lifecycle, the Shift-left principle has brought security responsibilities into the developer’s world, and they’re here to stay. Developers often find themselves reacting to alerts from SREs, manually auditing code, or relying on static analysis tools that frequently miss context-specific vulnerabilities.

You can instantly access insights like:

• Vulnerabilities in your code, including open source and third party vulnerabilities
• Recommendations for fixing an issue
• Proactive checks tailored to your current coding context

All of this happens without pulling developers away from their flow. MCP allows for a smarter, more proactive approach to security—one that’s embedded in their development process.

Need to create new code? Dynatrace is here to help

Writing new code with Dynatrace allows developers to look ahead proactively. By typing natural-language, conversational questions like “Have I bumped into CPU limits?” or “What is my CPU usage? Is it too high?” developers can identify potential bottlenecks and performance issues before they become real problems, ultimately delivering higher quality code.

Developing new code or optimizing a service in an existing app brings even more complexity. Such work involves identifying inefficient API usage, reducing unnecessary load, improving performance, and assessing the potential impact of the new code so as to minimize deployment issues.

Need to verify recent CICD builds? Dynatrace helps you shift left

As a developer, you want to catch build issues early—before they snowball into deployment delays or production incidents. With Dynatrace MCP, you can type questions like:

• “What failed in the last build?”
• “Are there any performance regressions tied to this commit?”
• “Did this deployment introduce any anomalies?”

By integrating Dynatrace into your CI/CD pipeline, you gain real-time visibility into build health, test coverage, and deployment impact. This means faster feedback loops, fewer surprises, and higher delivery quality. Dynatrace helps you to shift from reactive debugging to proactive delivery assurance—all through natural language interactions.

Get started with Dynatrace MCP

The Dynatrace MCP server is available as a community-supported open source project. To familiarize yourself with all it can do, visit the Dynatrace MCP project. in our GitHub repository. There you’ll find all the necessary documentation to guide you through the setup process and explain all the available capabilities.

The post Sky-high developer productivity with Dynatrace MCP and GitHub Copilot appeared first on Dynatrace news.

The Dynatrace unified platform experience delivers actionable insights to engineers without the hassle. With customizable launchpads, seamless Backstage integration, the RedHat DevHub plugin, and automated deployment validation with Site Reliability Guardian, engineers get the most important information front and center, allowing them to prioritize work and make informed decisions.

In this blog post, you’ll learn how platform teams can bring observability to developers, right where they need it.

Focus on what matters with launchpads

Dynatrace launchpads let you create customizable home pages that offer an easily digestible view of your environment, tailored to the needs of engineering teams. Launchpads can address various use cases, from onboarding and learning, serving as an entry point for occasional users, or providing an opinionated view for daily operations across different users, teams, and departments.

You can pin quick access to relevant Dynatrace® Apps, link to external tools or specific entries in Dashboards, Notebooks, Workflows, Problems, and more.

For example, the launchpad below was built for a developer team. It covers their daily routines, relevant content, and documents. Using Launchpads this way ensures that even occasional users know where to find key apps, how to resolve common issues, and how to debug problems—using Dynatrace and external resources.

Read our Launchpads blog and explore different Launchpads on our Dynatrace Playground tenant!

Bring observability to developers with developer portal integrations

Developer portals like Backstage have become increasingly popular in recent years, based on their ability to centralize access to tools, services, and documentation. By offering a consistent interface, they help developers navigate complex ecosystems more effectively and reduce time spent on context switching.

The seamless integration between Dynatrace and Backstage allows developers to pull observability and security data from Dynatrace and display it in software components you manage through the Backstage Software Catalog. This plugin allows you to provide smart links to Dynatrace apps, context-rich overview tables, and Site Reliability Guardian results and logs, all directly in Backstage!

Read our documentation on Backstage integration, and to get started, check out the Backstage Dynatrace plugins monitoring & observability page on the Dynatrace Hub.

Teams using the RedHat Developer Hub can also benefit from the Dynatrace integration. This plugin seamlessly integrates observability and security data from Dynatrace into the portal, enabling teams to monitor and operate their software components more effectively.

You can display real-time insights alongside managed components and add links to Dynatrace Apps for deeper analysis and root cause investigation.

Validate deployments automatically with Site Reliability Guardian

Dynatrace’s Site Reliability Guardian (SRG) embeds observability directly into the engineering workflow, allowing for fast, automated validation of service health during every change.

Automated change impact analysis

SRG automatically analyses the impact of deployments on performance, availability, and capacity. Powered by Davis® AI, it detects regressions and anomalies early—before they hit production.

SLO validation

Engineers can define service-level objectives for their software components to ensure they meet expected quality standards. See how your software components rate against company benchmarks and get insights on where and how to improve to deliver the best quality. SRG validates these objectives regularly or on demand, ensuring services stay performant and resilient.

Unified overview

SRG validation results are stored in Dynatrace Grail® data lakehouse and visualized in a single-page summary, showing the pass/fail status of the last validations and a detailed evaluation of individual objectives. This allows you to easily spot trends and degressions over time. Visualization can be enriched with custom metadata, such as release versions, build IDs, and environment identifiers.

Automated release validation, CI/CD integrated

Trigger SRG validations directly from your CI/CD pipeline, to get instant feedback and observability insights into the current health and performance state of your component.

For more information, check out our documentation and then go to the Hub and set up your first Site Reliability Guardian! If you’re looking for inspiration, check out our Site Reliability Guardian config-as-code samples.

Conclusion

Observability as a self-service is a reality with Dynatrace. Our unified platform experience allows platform teams to connect observability with developer portals, workflows, and automated deployment validation, giving engineers direct access to the data they need—without bottlenecks.

By empowering engineers to curate and automate their data according to their needs, teams can work more effectively and bring reliability checks earlier into the development lifecycle.

Next steps

Ready to try out these self-service observability enhancements yourself? Explore Dynatrace integrations and start customizing your observability and developer experience!

• Try out launchpads on the Dynatrace Playground 
• Install Dynatrace plugins (Backstage integration)
• Set up RedHat dev portal Dynatrace integration 
• Explore Site Reliability Guardian (SRG)

The post Self-service observability: Empower engineers to get the most value out of your observability data appeared first on Dynatrace news.

Debug, optimize, and secure your AI models with confidence

As agentic AI applications and systems gain traction, delivering reliable, high‑performing LLMs and agents becomes challenging due to heterogeneous stacks, non‑deterministic behavior, and cost sensitivity across multi‑cloud runtimes. Reliable delivery and deployment to production requires end-to-end telemetry across the full chain:
UI/services → orchestration/agents (LangChain, LlamaIndex, MCP/A2A) → RAG pipeline (embedding + vector DB) → model gateway (OpenAI, Azure/OpenAI, Bedrock, Gemini, Mistral, DeepSeek) → GPU/infra. To support deterministic rollouts and continuous model improvement, teams need standardized tracing/metrics, guardrail signal capture, and automated cost and performance governance.

The hidden challenges of AI model management

The invisible bottlenecks

AI models, especially LLMs, are prone to issues like hallucinations, degraded performance, and incorrect outputs. Debugging these problems is often like finding a needle in a haystack. Existing tools fall short in providing a unified view to compare prompts, datasets, or model versions, making it hard to identify regressions or improvements.

Navigating the risks of rapid model evolution

The impact of deprecation and automatic upgrades on cost, performance, and quality

The rapid pace of innovation in the AI space means that providers like OpenAI and Anthropic frequently release new versions of their models, such as ChatGPT 5 or Anthropic Opus 4.1.

While these updates often promise better performance and new capabilities, they can also introduce significant risks for your AI services:

• Deprecation of older versions: Providers may discontinue support for older models, forcing you to adopt newer versions without sufficient time to test their impact.
• Automatic upgrades: Many AI providers automatically update their underlying models, which can lead to unexpected changes in behavior, degraded performance, or even broken workflows.
• Compatibility issues: Changes in model behavior, such as output format or token usage, can disrupt your application’s functionality, requiring adjustments to prompts, configurations, or integrations.

Tracking token usage and managing costs is another uphill battle. Add to this the risk of prompt injection attacks and data leaks, and it’s clear that traditional methods are no longer sufficient

The new AI Model Versioning and A/B testing

Ship better models with confidence. In a single view, compare models and versions to validate improvements and spot bottlenecks across latency, reliability, token usage, cost, and output quality, then drill into prompt-level differences to confirm why a variant wins. When something breaks, follow the request end to end with distributed tracing: from input through orchestration steps and model calls to completion, so you can pinpoint exactly where an error or slowdown originated.

Compare models and versions: Detect bottlenecks and validate improvements in a single view.

Trace prompt failures: Debug errors from input to output with our Distributed Tracing solution.

Monitor costs and token usage: Gain real-time insights into token consumption and cost implications.

Detect security and guardrail risks: Identify and alert on vulnerabilities like prompt injection attacks, toxic responses, or captured PII.

Attach your own attributes like user session, feedback, or dataset ID for additional debugging information.

How it works

With AI Model Versioning, you can track metadata such as model version, dataset ID, and hyperparameters.

A/B testing lets you expose different user segments to model variations, providing data-driven insights into performance metrics like accuracy and cost.

Instrument in minutes: Use the supported OpenTelemetry-based SDK to instrument your service to capture prompts, completions, token usage, errors, and guardrail signals.
You can also enrich spans with attributes like model.version, dataset.id, user/session, and feedback for deeper analysis. (You can read more about this here.)

Start analyzing out of the box: Once data is flowing, the AI Observability app provides ready-made dashboards and distributed tracing so you can compare models/versions, monitor costs and tokens, and debug prompt failures end to end. No extra setup is required; you can try it out on the Dynatrace Playground right now.

By combining observability, AI-driven insights, and organizational knowledge, we’re enabling systems that don’t just react but learn and adapt. Each critical issue or incident you resolve fuels a living knowledge base, paving the way for proactive incident prevention through alerting.

What’s next?

We’re committed to enhancing these capabilities further. Upcoming updates will include a dedicated app experience for multi-model and multi-cloud setups, advanced visualization tools, enhanced security features, intelligent forecasting, and alerting for cost/performance and guardrail optimization.

Get started today

Ready to revolutionize your AI services? Here’s how:

1. Sign up for a free trial.
2. Install the AI Observability app.
3. Explore the AI Model Versioning ready-made dashboard, or check it out on our playground

Together, let’s build smarter, more reliable AI systems.

Read more

• Part one of the Rise of Agentic AI blog series covers the fundamentals of AI agents, models, and emerging communication standards such as Agent2Agent (A2A) and MCP.
• Part two of the Rise of Agentic AI blog series explores AI agent observability and monitoring, A2A and MCP communications, and how to scale and monitor Amazon Bedrock Agents.
• Part three explains how to monitor Amazon Bedrock Agents and how observability optimizes AI agents at scale.
• Part four covers full-stack observability for AI with NVIDIA Blackwell and NVIDIA NIM.
• Part five demonstrates how to build a simple agentic application using the OpenAI Agents SDK and instrument the data with Dynatrace.
• Part seven introduces data governance and audit trails for AI services.

The post The rise of agentic AI part 6: Introducing AI Model Versioning and A/B testing for smarter LLM services appeared first on Dynatrace news.

OpenTelemetry excels at capturing data from any environment and service: traces flowing from microservices, metrics streaming from containers and infrastructure hosts, and logs capturing the application and service lifecycles. OTel does exactly what it was designed to do: standardize telemetry collection. But here’s what OpenTelemetry doesn’t do by design: unified observability that analyzes that data, correlates it across services, or turns it into actionable, intelligent insights.

This is where most organizations hit a wall and require lots of expert knowledge. Organizations today have more observability data than ever before, but somehow less visibility into what’s actually happening in their systems. Raw telemetry data becomes a burden rather than an asset. Engineers spend more time hunting through dashboards than solving actual problems.

This is the “analytics gap” that Dynatrace was built to solve, transforming your telemetry data from scattered signals into unified, AI-powered intelligence.

Why OpenTelemetry + Dynatrace changes everything

Here’s what makes this combination powerful: OpenTelemetry gives you standardized data collection. Dynatrace gives you intelligent analysis that goes far beyond the static dashboards and manual correlation work that other platforms require.

While many observability solutions leave it to you to build custom dashboards and manually connect the dots between your telemetry signals, Dynatrace transforms your OpenTelemetry data into insights that actually drive decisions. Your traces, metrics, and logs aren’t just stored; they’re automatically correlated, analyzed, and contextualized as they flow through Dynatrace OpenPipeline®.

When a trace shows latency spikes, you immediately see related log entries and metric anomalies automatically contextualized and correlated. Lightning-fast queries via Dynatrace Grail® data lakehouse process millions of spans at the speed of thought, making observability accessible to your entire team, not just the experts who know how to build complex queries and visualizations.

The result? Your OpenTelemetry investment becomes a competitive advantage, not just another data collection project that requires a team of dashboard architects to maintain.

Complete OpenTelemetry coverage

Here’s how Dynatrace helps you to get the most out of your telemetry data, without requiring additional agents or complex configurations:

Distributed tracing excellence

Native OpenTelemetry tracing delivers superior span and trace processing with dynamic visualization tools that transform complex distributed architectures into complete end-to-end visibility. But it doesn’t stop there; all your telemetry signals (logs, traces, and metrics) correlate seamlessly, giving you clear, actionable insights within the full context of your traces and services. Get simple answers to advanced questions by expanding your investigations with DQL for powerful analytics, including correlation of logs and traces.

Service monitoring that understands your Architecture

Comprehensive service health monitoring built on OpenTelemetry standards. Dynatrace provides intelligent service analysis, anomaly detection, and visualization that work seamlessly with your OpenTelemetry-instrumented applications. Our service monitoring goes beyond simple health checks.

When issues arise, you see exactly which services are affected and how problems cascade through your architecture, all without manual tagging, configuration, or service discovery setup with YAML files.

Intelligent metrics with full context

You get flexible metric ingestion for custom business metrics and standard application performance indicators. Your metrics connect directly to the services and traces that generated them. But here’s where Dynatrace takes it further: we allow you to unify all your OpenTelemetry signals into comprehensive service intelligence. Instead of analyzing metrics in isolation, you see how they connect to actual service behavior, request flows, and application logs. Every metric becomes part of a complete service story.

Complete log processing

Your OpenTelemetry logs are transformed from noise to narrative. Instead of searching through endless log streams and manually created dashboards, Dynatrace supports a comprehensive log ingestion and analysis pipeline, allowing you to go big with Dynatrace.

Every log event becomes part of a larger story about user journeys, interactions, services, and app behavior, all focused on your desired business outcomes and incident investigations.

Here’s where it gets powerful: you automatically get additional contextual enrichment when you direct all your telemetry signals to Dynatrace. By creating bi-directional relationships between logs and traces, where logs provide context to traces and traces illuminate relevant logs, Dynatrace evolves troubleshooting from detective power-user work into AI-driven, streamlined, and intuitive investigations.

Video: See the full story behind every trace with correlated logs.

Kubernetes native support

For teams running OpenTelemetry in Kubernetes, Dynatrace delivers enterprise-grade support that scales with your cloud native operations. Native Kubernetes handling of spans, metrics, and logs from your Kubernetes OpenTelemetry deployments automatically collects Kubernetes context for automated enrichment: namespace, cluster, and workload relationships, all without any additional instrumentation. Your existing Kubernetes labels, AWS tags, and Azure tags become first-class filtering dimensions for all OpenTelemetry data, enabling automatic cost attribution and comprehensive data permissions using your existing RBAC patterns.

The result is that your OpenTelemetry observability inherits the same operational patterns, security boundaries, and cost structures as your Kubernetes infrastructure.

Why this matters for your team

Every organization adopting OpenTelemetry faces the same challenge: turning data collection into intelligent insights. The engineering teams that succeed are those that choose analytics platforms built specifically for OpenTelemetry data.

Dynatrace transforms your OpenTelemetry investment from a data collection project into a competitive advantage. We meet you where you are. We respect your choice to standardize OpenTelemetry by simplifying its operational complexity and enhancing it with analytics that actually deliver value.

Ready to transform your OpenTelemetry data?

Open standards have clear benefits. Industry standardization makes it easier to make sense of data coming from multiple different sources, whether it’s traces, metrics, logs, or telemetry from third-party tools. Your analytics platform can deliver intelligent insights across your entire technology stack. Your OpenTelemetry investment deserves analytics that reveal its full potential.

• Want to explore specific OpenTelemetry capabilities with Dynatrace? Try them out on the Dynatrace Playground
• Boost your productivity with these quick video guides for service owners working with OpenTelemetry:

Video: Easy access to your OTel Logs and Traces

Video: Analyze Service Failure from OTel Data

Video: Easy access to your OTel & Prometheus Service Metrics

Join us at OpenSource Summit. We’ll be in Amsterdam August 25-27. Stop by our booth to see the magic in action!

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Dynatrace has enhanced its runtime vulnerability analytics by integrating data from the Cybersecurity & Infrastructure Security Agency’s (CISA) Known Exploited Vulnerabilities (KEV) catalog, complete with critical remediation due dates. This powerful addition allows organizations to prioritize actively exploited vulnerabilities, align with federal security standards, and focus remediation efforts where they matter most—on threats that attackers are weaponizing right now.

The challenge of vulnerability prioritization

In today’s threat landscape, security teams face an overwhelming challenge in determining which vulnerabilities pose the greatest risk to their organization. With thousands of new vulnerabilities discovered each year, traditional scoring systems like the Common Vulnerability Scoring System (CVSS) often fall short of providing the real-world context needed for effective prioritization.

The reality is that not all vulnerabilities are created equal. While a vulnerability might receive a high CVSS score based on its theoretical impact, it might never be exploited in the wild. Conversely, some vulnerabilities with moderate scores are favorite tools of threat actors and are often involved in widespread attacks and significant business impact.

This disconnect between theoretical risks and actual threats creates several challenges for organizations:

• Resource allocation inefficiencies: Teams spend valuable time patching vulnerabilities that might never be exploited, while more dangerous threats remain unaddressed.
• Alert fatigue: Security professionals become overwhelmed by the sheer volume of vulnerability notifications, which leads to critical issues being missed.
• Compliance gaps: Organizations struggle to align their security practices with federal standards and regulatory requirements.

Enhanced Vulnerability Management with CISA KEV

Dynatrace already provides a Davis Security Score, an enhanced risk-calculation score that’s based on the industry-standard CVSS. Davis® AI provides this precise risk-assessment score by considering additional parameters such as public internet exposure and whether or not data assets are reachable from an affected entity.

Now, Dynatrace has further enhanced its runtime vulnerability analytics by integrating data from the CISA KEV catalog, including the critical due dates for remediation. This addition brings a new layer of actionable intelligence to vulnerability management by unlocking the ability to prioritize actively exploited vulnerabilities.

Unlike general vulnerability databases, KEV is based on real-world exploitation data and expert analysis. Each entry is carefully vetted and includes a due date by which federal agencies must remediate the issue. This due date is not arbitrary—it reflects the urgency of the threat and the need for swift action. By aligning with KEV, Dynatrace helps organizations stay ahead of attackers by focusing on vulnerabilities that are not just theoretical but actively weaponized.

The KEV catalog is especially valuable because it’s curated by cybersecurity experts at CISA using intelligence from government, industry, and open source reporting. Customers integrating KEV into their security workflows can align with federal standards, improve risk-based prioritization, and reduce exposure to high-impact attacks.

KEV filtering and prioritization

Once you’ve turned on runtime vulnerability analytics in Dynatrace, you can filter KEV vulnerabilities in the Vulnerabilities app. The resulting view is sorted based on the remediation due date, starting with the most urgent vulnerability.

Expanding KEV support

CISA KEV data is available directly within the Vulnerabilities app, giving your teams immediate visibility into the known exploited vulnerabilities that affect their environment and the remediation date by which they must be resolved. In the future, Dynatrace will expand support for KEV data to vulnerability dashboards and automation workflows so you can visualize KEV-related risks in your custom dashboards or assign remediation tasks based on KEV due dates or exploit status.

Try KEV filtering today

This integration helps organizations align with federal security standards, improve risk-based prioritization, and reduce exposure to high-impact attacks. It’s a practical way to stay ahead of cybersecurity threats by focusing on vulnerabilities that are actively exploited.

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Delivering reliable, business-critical applications to production is more complex than ever. The growing complexity and granularity of modern software systems and the trend to shifting more and more responsibilities to development teams (shift left) lead to increased pressure on your development teams.

In fact, traditional development teams now have a wider set of responsibilities; they must be highly skilled and educated in a multitude of domains. The responsibilities of these teams now range from specification, planning, testing, risk assessment, cost estimates, and deployment, to load testing, UI testing, integration testing, and on-call responsibilities for their software services.

While development teams need to be literate in all new technology stacks, cloud resources, and quality assurance methods, they also need to work with numerous tools.

The invisible bottleneck in your remediation process

The whole shift-left trend has pushed operational responsibility closer to development, expanding workloads to include on-call rotations, more frequent deployments, and growing expectations around uptime. When incidents occur, dozens of engineers are dragged into war rooms to perform analysis of the underlying root causes.

Reducing the Mean Time to Repair (MTTR) is essential to business continuity and customer satisfaction. Without access to the right knowledge at the right time, even skilled teams lose momentum. In high-pressure situations caused by critical incidents, it becomes more important than ever to ensure that all relevant information is shared with every role involved. This requires the most automated and intelligent methods available for effectively collecting, analyzing, and distributing information.

The on-call engineer’s journey

Take Omar, an SRE; an automated voice jolts him awake to summon him into a war room in the middle of the night after a routine update caused a spike in failed requests for a cloud-based payment service. It’s a P1 incident. With each passing minute, merchants are losing value, support requests surge, and customers are complaining. Dozens of caffeinated engineers are already in the war room.

Logs point to timeouts, but this is just a symptom; the real problem is somewhere else. Reading every message and document would take hours, so Omar scans for summaries, key findings, and any mention of his team’s services. Several hypotheses have already been tested, and one points to a potential issue in a backend service Omar’s team owns. Meanwhile, customer complaints are beginning to surface from other time zones. The payment service is failing, and customer success managers are growing increasingly anxious.

And while a similar outage has happened before, Omar is not able to find any documentation or insights into how to remediate the issue.

Why organizational knowledge doesn’t scale

When remediation history lives in documents, scattered across teams, formats, and platforms, engineers waste time searching instead of solving. Even well-documented incidents don’t prevent recurrence if they’re disconnected from future incidents. Even centralized platforms like Backstage don’t help if they can’t surface the right guidance at the right time.

Without a way to systematically identify, reuse, and scale this knowledge, it remains reactive. That’s not just inefficient, it’s a blocker to building intelligent automation and truly preventative operations. This is the hidden obstacle, silently inflating your MTTR, buried knowledge that costs time, delays response, and drains focus from what really matters. This is what remediation intelligence solves.

Introducing remediation intelligence

Dynatrace has a long history of providing DevOps teams with AI-driven tools for anomaly detection, root cause identification, and incident impact assessment in complex application environments. Over the past decade, it has contributed to reducing mean time to resolution (MTTR) by learning application behavior and analyzing dependencies in real time.

Building on this foundation, Dynatrace launched remediation intelligence, which adds an additional element to the incident response process from alert through resolution. It assists engineers during remediation by combining Davis® AI root cause and impact analysis with input from global community knowledge and internal expertise. It integrates data such as logs, metrics, traces, and topological context into a single view and offers support for documenting post-incident reviews.

Close the knowledge gap:  Embedded troubleshooting knowledge

What truly sets Dynatrace remediation intelligence apart is its ability to proactively surface relevant internal knowledge at the moment it’s needed most. It adds an AI-guided assistive layer to the Problems app that brings implicit, organizational knowledge directly into the flow of incident response. Once a problem is detected, Davis AI scans the historical data, surfacing past remediation playbooks, troubleshooting dashboards, and notebooks that were used to resolve similar issues.

With troubleshooting guides, we introduce a context-aware guidance system, built on Davis AI, that connects current incidents with prior resolution paths. It makes organizational knowledge queryable, remediation patterns reusable, and every responder effective, even when they’re solving an unfamiliar issue.

Remediation intelligence surfaces the most relevant remediation insights

When an incident occurs, Dynatrace excels at automatically analyzing and surfacing technical insights. It collects and organizes all relevant signals—logs, metrics, traces, and topology—into a single coherent problem. No fragmented alerts. No disconnected symptoms. Just one structured, AI-curated incident view. In parallel, Dynatrace AI scans all documents marked as troubleshooting-relevant. Using advanced semantic search and vector embeddings, it ranks and surfaces the most relevant past incidents, dashboards, notes, and postmortems, based on their similarity to the current problem. This is not just keyword matching; Dynatrace understands patterns, failure modes, and system relationships, surfacing ranked, high-similarity incidents in the problem view.

From observability to trusted automation: The power of context-aware AI

The future of resilient, self-healing systems lies in the seamless integration of observability, AI, and organizational knowledge. When these elements come together, they form the foundation for trusted automation—a system that not only reacts to incidents but learns from them, adapts, and eventually prevents them altogether.

At the heart of this vision is context. Effective auto-remediation depends on the ability to precisely identify the root cause of an issue and understand its broader impact across the application stack. But automation doesn’t stop at detection. By capturing and integrating the remediation strategies used by engineers, Dynatrace builds a living knowledge base. This organizational knowledge, when combined with AI-driven root cause analysis, allows the system to replicate proven remediation paths and suggest next steps with increasing accuracy.

With all relevant data and insights unified in a single platform, engineers gain a single pane of glass view into their systems. This not only streamlines manual remediation efforts but also lays the groundwork for flexible, context-aware auto-remediation. Each incident you resolve fuels the knowledge. Over time, as the system learns, it evolves from reactive automation to proactive incident prevention—anticipating issues before they escalate and taking preemptive action.

This is the vision Dynatrace is delivering: a future where engineers can trust automation not just to respond, but to understand, learn, and improve—turning every incident into a step toward greater system intelligence and reliability.

Empower your teams: turn hard-won operational insights into scalable remediation power

Dynatrace remediation intelligence is ready to work for you today. To start benefiting, opt into Davis CoPilot®, the Dynatrace generative AI assistant. Once turned on, you’ll need to configure Davis CoPilot to learn from a curated set of Dynatrace documents—specifically, Notebooks and Dashboards that are either created directly from detected problems or clearly labeled with the prefix [TSG] in their titles (short for Troubleshooting Guide).

Davis CoPilot will analyze and learn from your team’s historical remediation efforts, capturing valuable insights and strategies, allowing it to proactively suggest relevant documentation and guidance when similar incidents are detected in the future, helping your engineers respond faster and more effectively.

All data uploaded to Dynatrace remains strictly private. All data and remediation insights remain within your tenant. Davis CoPilot treats your documents as strictly confidential and never shares or transfers this information outside your Dynatrace environment. Your team’s knowledge stays private, secure, and entirely under your control, while still powering smarter, more context-aware automation.

Learn more about document suggestions and Dynatrace remediation intelligence in our documentation, and read about discovering relevant troubleshooting guides and how to create new ones.

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To ensure effective utilization of observability data and meet data governance requirements at the same time, organizations must preserve both technical and business context across massive, fast-moving data streams. This is a complex challenge:

• Maintaining data context: Relating logs, metrics, and traces across domains requires advanced correlation mechanisms. Yet, inconsistent tagging practices across teams and services lead to fragmented views and blind spots.
• Maintaining business context: Observability data often relies on enrichment rules to inject business metadata, such as service owners, cost centers, or deployment tags. These enrichment rules are typically static and hardcoded, requiring constant updates to keep pace with shifting organizational structures, service ownership, and evolving business priorities.

At enterprise scale, these challenges are magnified. Organizations often have hundreds of teams and thousands of users who require access to observability data, each with different needs and use cases. Centralized teams are expected to provide real-time access to relevant data while managing an ever-growing number of filters and governance rules. Manually maintaining and rolling out thousands of static filters across dynamic environments is not only time-consuming; it simply doesn’t scale. To remain effective, organizations need an approach to organizing their data that is dynamic, easy to manage, and empowers users with self-service access to the right data in the right context, without compromising compliance or security.

Dynatrace addresses this with the introduction of Segments, a dynamic, multidimensional, enterprise-grade approach to data segmentation that’s applied at query time. This allows centralized teams to provide smart filtering that removes noise by applying user, team, or application-specific context, while at the same time reducing their maintenance effort.

Decoupling backend data organization from frontend data utilization

Dynatrace is built from the ground up to meet the scale and manageability demands of modern cloud- and AI-native enterprises. With organizations generating petabytes of telemetry daily, Dynatrace ensures real-time ingestion, exploration, and analysis across all data types. Its architecture supports thousands of users across ITOps, SRE, developers, platform engineering, and business teams, while remaining efficient and easy to maintain.

While other observability solutions struggle with scalable, use–case–optimized data segmentation and robust access controls, Dynatrace delivers enterprise-grade manageability with full flexibility to meet any requirements. It decouples compliance and security from day-to-day data usage, enabling both control and agility at scale.

To support this, Dynatrace introduces three core concepts that feature segments as a key part of the solution:

1. Data partitioning (buckets): Organize data logically to meet performance, compliance, and retention requirements. Think of a bucket as a folder in a filesystem. Use buckets to group telemetry data that naturally belongs together, for example, data from the same region, environment, or with the same sensitivity classification.
2. Data access (IAM): Stay flexible and meet compliance and security demands by defining fine-grained access to data and Dynatrace platform capabilities based on a user’s context. Use IAM to manage fine-granular permissions, enforcing enterprise-grade governance.
3. Data segmentation (segments): Enable real-time filtering across massive data sets without the need to create thousands of individual rules. Segments are fully governed by existing access controls, ensuring that users only see the data they’re authorized to access.

Use segments across your organization

Segments bring business context to observability data and are consistently available across the Dynatrace platform. The key benefits of using segments are:

• Dynamic, not static: Segments adapt automatically using variables, keeping filters relevant as environments evolve. New services, Kubernetes namespaces, and more are picked up without manual updates. Segments are multidimensional, so users can combine them to zoom in on their data.
• Performance-optimized pre-filters: Applied at query time, segments scope queries to only the selected data segment, reducing overhead and increasing efficiency.
• Establish shared, global data views, aligned to business logic: Structure data segments, for example, by data ownership region, business unit, environment, or application. Provide a consistent source of truth across the organization.
• User-created context: By combining centrally managed segments with their own custom filters, users can personalize their views without involving the centralized team.
• Built for scale: Real-time filtering across petabyte-scale data volumes, by thousands of users, without compromising performance.

Consider the following examples, how different roles can use the same set of segments to tailor their view of shared data to their specific needs.

• An IT Ops team looking to quickly assess infrastructure health in a specific region does this by combining segments for region with host group, cloud provider, or Kubernetes cluster, instantly narrowing the scope.
• Developers troubleshooting a web app select the segment focusing on all data related to this particular app, and combine it with an additional filter for Kubernetes namespaces to zoom in on logs, metrics, and traces tied to that exact deployment. They then layer on details like error types or device models to pinpoint exactly where issues occur. This allows them to rapidly identify issues and improve stability and user experience.

Although both teams work from the same unified observability dataset, segments dynamically apply each user’s individual context at query time, ensuring they only see what’s relevant.

Tip: To further customize the Dynatrace experience for different roles, familiarize yourself with Launchpads, our central entry point for users that consolidates relevant resources and makes their Dynatrace experience more personal and relevant. Learn more about Launchpads.

Discover how to leverage segments in your organization

For more on how to get the most out of segments, explore our documentation and these helpful resources:

• The benefits of segments for users
• How to use segments for advanced log analysis
• How to best use filtering and segments on dashboards
• How to segment data by Kubernetes clusters

The post Segments empower centralized teams to dynamically organize data at petabyte-scale appeared first on Dynatrace news.

We’re proud to announce that the Dynatrace® platform is now certified in accordance with Esquema Nacional de Seguridad (ENS), Spain’s National Security Framework by OCA CERT.

The ENS is an official cybersecurity framework established by the Spanish government to ensure the protection of information and services in the public sector and among regulated service providers. By aligning to ENS standards, organizations guarantee that their technology, processes, and people meet stringent requirements set forth by the Spanish government, fostering greater trust and reliability in digital services.

Partnering with the Spanish public sector

Many public sector organizations across Spain and the broader EU are eager to accelerate their digital transformation. They want to deliver faster services, better user experiences, and smarter operations. Due to the criticality and sensitivity of the information handled by public sector institutions, finding the right balance between innovation and regulatory adherence is a constant challenge. Regulations such as ENS are designed to ensure that data remains protected while enabling digital progress.

This dynamic often slows down transformation efforts, leaving teams reliant on legacy monitoring tools that lack scalability, cloud-readiness, and automation. To move forward, public institutions must rely on technology partners who not only deliver innovation but do so with trust, accountability, and a deep understanding of national cybersecurity standards.

We’re proud to support this mission and honored to stand alongside our customers in Spain as a trusted partner for their secure digital future.

Dynatrace: Security meets intelligence

The Dynatrace® platform is reimagining observability by combining the power of analytics, AI, and automation to drive organizations forward in the age of agentic AI. The 3rd generation platform has been built to harness a goldmine of observability data in context and turn that data into real-time knowledge for AI, creating actionable insights and automation, and paving the way for autonomous intelligence. The ENS certification reinforces our commitment to delivering trustworthy, compliant, and secure cloud services, enabling organizations to innovate with confidence.

Certification comes with practical advantages

• Public sector onboarding: Spanish government agencies and regulated entities can now confidently adopt the Dynatrace platform and meet local compliance requirements.
• Enterprise risk reduction: Organizations in finance, healthcare, and other critical sectors benefit from reduced risk and a proven security framework, simplifying their own compliance efforts.
• Accelerated RFP and procurement: ENS certification streamlines the procurement process, enabling faster onboarding and go-live timelines for projects subject to regulatory scrutiny.

Example use cases include deploying digital citizen services, secure data analytics platforms for healthcare, and compliant hosting environments for fintech applications, all leveraging the Dynatrace ENS-certified platform, a solution that combines world-class observability with government-grade security. The bigger story is what this allows: faster innovation, smarter public services, and more trust between citizens and their institutions.

How ENS High elevates Dynatrace security and trust for the public sector

ENS certification reinforces Dynatrace’s already robust security foundation, which includes:

• Enhanced data protection mechanisms that offer access, confidentiality, integrity, traceability, authenticity, and conservation of data.
• Formalized incident response protocols for quick detection and remediation of potential threats.
• Advanced risk management strategies, including regular vulnerability assessments.
• Increased transparency and monitoring of operational activities.

The bottom line is, with Dynatrace, Spanish public sector organizations have gained the performance insights they need, supported by the compliance and security standards required for regulated environments.

Compliance without compromise

Achieving ENS High certification is one of many testaments to our dedication to setting industry benchmarks. Visit the Dynatrace Trust Center to review all our certifications and accreditations and to learn more about the Dynatrace approach to security and privacy by design.

The post Dynatrace achieves High certification under Spain’s National Security Framework (ENS) appeared first on Dynatrace news.

Log data alone, however, is often not enough to give you a complete overview. In the case of security incidents, the origin of a failed request or a login attempt is often the most valuable information you have in triaging a potential incident and determining its severity.

To speed up your threat hunting and incident response activities, Security Investigator now allows you to enrich IP addresses with additional context from third-party threat detection databases.

Fast insights into IP addresses

Dynatrace Security Investigator is one of the built-in apps shipped with Dynatrace. It’s designed for evidence-driven security use cases based on the logs, metrics, and traces ingested into the Dynatrace Grail® data Lakehouse.

Imagine you’re solving a security incident and need to understand more about the origin of an attack. You want to check the IP address reputation analysis provided by AbuseIPDB or VirusTotal, but manually looking up and pasting these addresses takes too much time. Not to mention, you want to keep this external reputation information tied to your investigation for future access.

By right-clicking an IP address in Security Investigator and selecting Enrich IP, you can choose your configured enrichment source to enrich the address. For this first release, Dynatrace offers IP enrichment insights from AbuseIPDB and VirusTotal.

Suppose you find something suspicious in your log data related to a certain IP address. You can now add the IP address and additional reputation analysis to your Suspicious IP evidence list in Security Investigator.

The IP address and corresponding enrichment data are now kept in the context of your investigation; you can revisit this enrichment data at any time.

Automatic IP evidence enrichment

You can now automatically enrich all the IP addresses you collect with evidence. In the evidence list enrichment menu, choose if enrichment should be enabled for all added elements by default, and which connection should be used to enrich the IP addresses that are added to your evidence list.

When you add new IP addresses to the evidence list, they’re automatically enriched on your behalf using your selected enrichment connection.

Select the details icon to quickly access the persisted IP enrichment data that’s fetched from each third-party source.

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The business observability gap in cloud-based transactions

Business observability, at its best, delivers real-time insights into business health, reporting, and interpretation of the metrics and KPIs that business and IT leaders need to make decisive and effective decisions.

But how can you access this data when cloud-based solutions deliver your critical services? One of the more common examples is payment gateways, or payment service providers (PSPs)—hosted services that verify account details, check for available funds, and transfer money into your business merchant account.

There’s a wealth of business data in your systems’ transaction requests to these PSPs and other SaaS solutions. Without visibility into this data, you’re left with an incomplete and delayed understanding of transaction success, sales data, and business health. This is particularly problematic since the transaction success or failure status is often embedded within the response body.

Here are some of the challenges our customers have identified:

• Delays in resolving issues. Failed transactions are only discovered in scheduled reports or when customers complain.
• Reconciliation discrepancies. Inconsistencies between internal records and PSP reports lead to frustrating, time-consuming, and error-prone manual work.
• Inability to understand short-term trends. Identifying failure patterns for specific providers or transaction types is nearly impossible without timely and detailed transaction data.
• Compliance risks. Lack of granular detail makes auditing and demonstrating compliance with payment regulations more challenging.

Business events from outgoing web requests

Dynatrace business events are in a special class designed to support even the most demanding business use cases. Whether derived from OneAgent, log files, RUM sessions, or APIs, business events deliver real-time lossless access to critical business data—wherever it lies. In particular, OneAgent’s unique capability to extract business data from in-flight application payloads—without writing any code—has proven invaluable to hundreds of our customers.

OneAgent now supports capturing business events from outgoing web requests that are specifically designed to illuminate these blind spots. You can now transform critical business information within your outgoing web requests and their corresponding responses into structured business events, which can then be analyzed, correlated, and acted upon within Dynatrace.

Use case: Business events and payment gateways

Here’s how it works, and what it means for our payment gateway use case.

Granular configuration for targeted capture

• Define endpoint-specific rules to capture data from requests to specific URLs or IP addresses (for example, api.stripe.com/payments or paypal.com/checkout).
• Define method-specific rules to capture data from relevant HTTP methods like POST or PUT that are used to initiate transactions.

Deep insight into request and response payloads

Support for business-event capture from outgoing web requests adds compelling new value and expands on current OneAgent capabilities for extracting business data from in-flight application payloads.

• Extract data from the request body. Imagine you’re sending payment requests that include customer account numbers, transaction amounts, and transaction identifiers. You can now define rules to extract these key pieces of information directly from your JSON or XML request bodies. This is crucial for linking your internal transaction IDs to the business data sent to the provider.
• Extract data from the response body. Potentially greater value lies in the response body. Often, PSPs return transaction status messages (for example, transactionStatus:success, authorizationResult:approved, or responseCode:1954) within the response body. Extracting these status messages allows you to report, alert, and act on failures or anomalies as they occur.

Transform raw data into meaningful business insights

Business data increases in value when enriched with business and IT attributes. For example, you could map extracted fields to meaningful attributes of a “Payment Transaction” business event. These attributes might include payment_provider_id, transaction_amount, and customer_id, extracted from the request body, and payment_status extracted from the response body.

These events are automatically enriched with Dynatrace observability data, such as the request’s originating host, service, user journey, or geographical source, facilitating business and IT collaboration.

Real-time visibility and proactive alerts

• Real-time business transaction monitoring. Know each PSP transaction’s success, failure, and value as it happens, not hours later.
• Custom dashboards. Dashboards make it easy to visualize different PSPs’ success rates and revenue, exposing bottlenecks and highlighting business and failure trends.
• Proactive alerting. Set up alerts based on real-time payment status messages. Trigger alerts on failed transactions over a certain amount, or when the success rate SLA degrades.

Enhanced traceability and root cause analysis

• End-to-end transaction tracing. Trace the entire lifecycle of a payment, from the user initiating the purchase through your internal services to the outgoing request to the PSP and the response status indicating success or failure.
• Accelerated root cause analysis. Quickly determine the source of payment transaction failures, bottlenecks, and anomalies to speed resolution and improve business outcomes.

Payment gateway example: From opaque to transparent

Here’s what this could mean for your organization:

1. A customer attempts a major purchase. Your e-commerce system sends the request to your PSP, but the transaction is declined.
2. OneAgent captures relevant business data from the outgoing request, including customer ID and transaction amount attributes. Dynatrace also captures the relevant response fields, including the status:declined message.
3. A “Payment Failure” business event is automatically generated in Dynatrace. This event triggers an alert to notify your operations and customer support teams.
4. Your customer support team can now proactively contact the customer while your operations team works to resolve the issue, knowing exactly why the transaction failed and which provider was involved.

This is possible without any code changes. Extracting business data from outgoing requests and responses turns opaque customer interactions into transparent, actionable business insights, empowering you to improve customer experience, optimize payment workflows, and reduce operational risk.

Initial support for outgoing web request capture is available for Java; see Supported Technologies for details. Additional technology support will be available soon.

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NVIDIA Blackwell systems provide high-performance infrastructure for enterprise AI, and now, thanks to the Dynatrace integration with the NVIDIA Enterprise AI Factory reference design, enterprises can add Dynatrace Full-Stack Observability to NVIDIA Blackwell infrastructure. This magnifies the value of the NVIDIA Blackwell platform by providing real-time performance insights, anomaly detection, and dependency mapping.

Keep high performance and security top of mind with unified observability and security

Dynatrace aligns with high data security and privacy standards typical of on-premises NVIDIA Blackwell deployments, particularly in regulated industries such as finance and healthcare. Its unified data model, Smartscape® topology mapping, and Davis® AI engine provide deep visibility into the full stack—from GPU metrics and containerized workloads to distributed applications and user experiences, enabling tailored observability for workloads running on  NVIDIA Blackwell. Integrating NVIDIA Data Center GPU Manager or other telemetry sources is straightforward, allowing teams to monitor GPU health, utilization, thermal thresholds, and memory bandwidth alongside traditional infrastructure metrics.

Dynatrace technology allows for automated discovery and instrumentation of services running on NVIDIA Blackwell-accelerated systems. Whether monitoring high-throughput GPU compute tasks, Kubernetes clusters, or microservices, Dynatrace ensures low-overhead performance monitoring with minimal manual configuration.

AI-powered, real-time insights improve performance and explainability

With Dynatrace Full-Stack AI Observability, you can monitor real-time performance, trace prompts end-to-end, and ensure compliance, optimizing cost and throughput for your AI and LLM workflows and agents, offering various use cases such as

• Monitor service health and performance, tracking real-time metrics and offering clear visibility into service incidents.
• Validate service quality by measuring response speed or identifying performance hotspots.
• End-to-end tracing and debugging pinpoint the root cause of errors and failures in the LLM chain, troubleshoot issues in complex pipelines, and trace dependencies across the entire system spanning multiple LLMs, RAG pipelines, and agentic frameworks.

Unified AI-powered observability

Dynatrace delivers full stack observability for your LLMs and Generative AI applications running on NVIDIA Blackwell systems. Its ability to provide visibility into complex, high-performance environments allows enterprises to fully leverage Blackwell’s capabilities while maintaining operational excellence and system reliability, improving the performance, explainability, and compliance of your AI workloads and agents.

Visit the Dynatrace Playground to learn more and gain hands-on experience with prepopulated data, so you can experience the possibilities of AI and LLM observability with Dynatrace. If you’re interested in using Dynatrace for your own AI workloads, visit our documentation and start benefiting from full stack observability for AI and LLM.

Read more

• Part one of the Rise of Agentic AI blog series covers the fundamentals of AI agents, models, and emerging communication standards such as Agent2Agent (A2A) and MCP.
• Part two explores AI agent observability and monitoring, A2A and MCP communications, and how to scale and monitor Amazon Bedrock Agents.
• Part three explains how to monitor Amazon Bedrock Agents and how observability optimizes AI agents at scale.
• Part five demonstrates how to build a simple agentic application using the OpenAI Agents SDK and instrument the data with Dynatrace.
• Part six explores AI Model Versioning and A/B testing for smarter LLM services.
• Part seven introduces data governance and audit trails for AI services.

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Dynatrace introduces a new advanced way to enhance your DQL queries in Security Investigator cases. The pivoting queries concept allows engineers to quickly change the investigation context by switching the scope of a query using available pivoting dimensions.

Time is critical

Imagine you’re investigating latency issues in your cloud applications by analyzing your Istio proxy logs with Security Investigator. You have hundreds of pods, each of which has application containers and Istio containers running side-by-side. You analyze all the Istio logs at once to get a comprehensive overview of the whole infrastructure, fetching logs for all long-running requests, and you want to investigate some of the requests to identify the issues behind the high latency.

Dynatrace Security Investigator is one of the built-in apps shipped with Dynatrace. It’s designed for evidence-driven security use cases based on the logs, metrics, and traces ingested into the Dynatracer Grail® data lakehouse.

Security Investigator allows you to:

• Keep your whole investigation flow in context.
• Perform complex security investigations on the data stored in Grail.
• Build DQL queries based on your findings in a fast and easy way.
• Save and use the found evidence to build your DQL queries and find answers to your questions.
• Navigate with ease to any point in your investigation history and review queries and results.
• Fetch detailed results in the original format to quickly understand the information.

Quickly shift your investigative perspective

Thanks to pivoting queries, it‘s now possible to quickly shift your investigation from one perspective to another. You can choose Pivot query by right-clicking any record in the results table in Security Investigator and selecting the dimension you want to pivot your query by, for example, Kubernetes pod. As a result, a new query node is created, containing all the logs from the same Kubernetes pod from which the Istio record originated, giving you the full context and all application logs from that pod.

Pivoting queries also work at scale: if you select multiple records and use pivoting queries with multiple values, multiple nodes will be created based on the distinct selected values. So, if you choose five result records and pivot query by trace_id, then five new query nodes will be created, which will contain results for each respective trace ID. This allows you to continue investigating each trace in your query branch, keeping the context and tracking your individual query history.

The pivoting dimensions are chosen from the metadata fields of your log records and can be further customized in Security Investigator. You can switch dimensions from, for example, a high-level Kubernetes cluster or host to the corresponding process group instance or cloud application, depending on your investigation’s purpose and the context you need.

The pivoting queries feature allows you to speed up your investigations and apply them in different contexts using the power of the query tree and other investigative features of Security Investigator.

Get started

The post Pivot the perspective of your investigative queries with Security Investigator appeared first on Dynatrace news.

Business Insights is a unique team within Dynatrace that partners with organizations to maximize their value from Digital Experience Monitoring (DEM) and Business Analytics, through our deep product expertise and exclusive technology capabilities. The Business Insights team provides product configuration and best practices, exclusive analytics and analysis to drive improved customer experience, and expertise on demand. Dedicating the necessary time, resources, and focus to deliver excellent end-user experiences can be a challenge. This is why Dynatrace’s largest and most sophisticated customers rely on Business Insights to deliver the strategic value that helps drive improved customer experience and business outcomes, whether that’s:

• Deploying a synthetic monitoring strategy to help a large beverage company achieve 100% age-verification compliance for the first time across 3,000+ properties
• Using our deep expertise in real user analysis to help a global automaker drive a 90% reduction in frontend errors, a 50% reduction in search results load time, and a 58% year-over-year reduction in outages
• Identifying the root cause of a performance issue impacting customers on one of the UK’s largest retail sites, which, when fixed, reduced exit rate by 2%, driving $500k+ of additional monthly revenue
• Working with senior executives and cross-functional teams at one of the world’s largest airlines to implement a holistic Business Observability strategy combining DEM, Business Analytics, and the broader Dynatrace platform to provide an end-to-end view of how infrastructure, services, and front-end applications impact critical business flows and KPIs in real time

Business Insights has long worked closely with Dynatrace customers to help accelerate adoption and value from the Dynatrace Digital Experience Monitoring (DEM) and Business Analytics capabilities; however, customer collaboration could be challenging at times with information scattered across emails and PowerPoint slides, multiple channels of engagement, and analysis disconnected from the Dynatrace platform. The Business Insights app simplifies and enhances the experience and engagement of Business Insights services, making it more seamless and accessible. It’s also the starting point for delivering more advanced AI-driven analysis, like those pioneered in the Opportunity Insights app.

Dynatrace delivers more value than its competitors

The Business Insights app directly addresses these pain points through unified, contextual delivery on the Dynatrace platform that transforms how insights are received, consumed, engaged with, and acted upon.​​​​​​​​​​​​​​​​

Bringing Business Insights into an app on the Dynatrace platform creates an enhanced experience of both the service and the platform through targeted, actionable analysis and recommendations directly in Dynatrace, in the context of the rest of the product, and with the ability to move seamlessly between them.

Timeline view: Your complete analysis history

As a Business Insights customer, keeping track of communications (enablement content, historical analysis, value over time, etc.), bringing new team members up to speed on the service, and summarizing value received over time for key stakeholders could be a challenge, with everything buried in emails. The Business Insights app centralizes all engagement and analysis in a single timeline view, making it easy to review everything the Business Insights team has provided for your organization, including:

• Analysis value moments
• Announcements
• Enablement material

Invites to live sessions such as Tech Talks and Customer Connects.

Each analysis value moment is tagged with helpful metadata, including type (performance, operational, business), product component (web, mobile, synthetic), application/synthetic monitor name, and specific page or event details. Enablement moments help you ramp up on the product more quickly, while announcements make sure you’re always up to date with what’s happening with the DEM and Business Analytics capabilities in the context of what matters to you. This comprehensive view helps new team members quickly understand your digital experience landscape and previous insights, accelerating onboarding for the service and Dynatrace DEM.

Value moment detail: Rich interactive content

Value moments are small and consumable DEM insights and analysis deliverables put together by our analysts for operational, performance, and business use cases to help you understand where to focus. Selecting a value moment from the timeline opens the main view with structured, easy-to-navigate content. Each value moment includes an optional video summary at the top for a quick overview, followed by indexed sections that allow you to jump directly to relevant information. Content links seamlessly to other Dynatrace Apps, Notebooks, and Dashboards for deeper context, eliminating the need to switch between tools. Each value moment also includes a shareable deep link, making bringing additional team members into the conversation simple. The structured, consumable content of value moments and easily navigable content help teams quickly identify focus areas and collaborate on operational decisions and actions.

Collaborative engagement and real-time feedback

The Business Insights app transforms analysis from a one-way delivery into a collaborative experience. Simply select any content within a value moment to leave comments or questions directed to the Business Insights team or your team members. Our team receives immediate notification and responds directly in the comment thread, keeping everyone aligned and in context. You’ll also receive email notifications with direct links when we reply. Threaded discussions and immediate notifications keep teams aligned and engaged with the Business Insights team.

Each value moment also includes a dedicated feedback section, allowing you to quickly indicate value and direct our future analysis and priorities.

Early feedback

The ability to easily provide feedback has been pivotal in quickly refining our interactions with the Insights team and the value we get from the service
– North American gaming company

By centralizing everything in one place, we’re inspiring people to use RUM and freeing them from digging through multiple tools and endless emails to find the context they need.
– UK insurance company

What’s next

The Dynatrace Business Insights app has been built to transform the way you engage with Business Insights and increase the value you receive from the Dynatrace platform, giving you:

• Centralized communication – All analysis, discussions, reports, and material in one searchable location
• Contextual engagement – See analysis in context of your real-time data within the product, with direct links to other apps/notebooks/dashboards
• Increased adoption and team exposure – Easy sharing of value moments with deep links, making insights more accessible across your organization
• Simplified collaboration – Comment directly on specific content to seamless interaction with Business Insights and your internal teams
• Historical access – Timeline view for easy tracking of past interactions, discussions, and analysis
• Self-service access – Anytime access to reports and insights without waiting for emails and calls
• Enhanced service through direct feedback – Simple, built-in mechanisms indicate value and guide future analysis

This first release is just the beginning, not merely a new interface but the foundation for next-generation Business Insights that will allow advanced machine learning and AI capabilities for enhanced analysis.

Get started

The new app is now generally available for Dynatrace Business Insights customers running a Dynatrace SaaS deployment. We’ll progressively roll the app out to existing customers over the coming weeks:

• If you’re interested in being part of the initial wave of adopters, please talk with your Dynatrace analyst or submit this form.
• If you’re not a Business Insights customer and are interested in learning more, please reach out to the Dynatrace Sales team.

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© 2025 Dynatrace LLC

Dynatrace and the Dynatrace logo, are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners.

The post The Power of Business Insights expertise now directly on the Dynatrace platform appeared first on Dynatrace news.

Organizations are under growing pressure to exercise autonomy over their digital assets while maintaining operational performance in hybrid and multi-cloud environments. The concept of cloud sovereignty — minimizing external dependencies and exerting full control over data, applications, and infrastructure — has become a critical business imperative.

In collaboration with Deloitte, Dynatrace has crafted a comprehensive whitepaper, “Observability for sovereignty: The keystone for compliance & control,” exploring how enterprise observability can drive sovereignty and showcasing real-world use cases and practical insights.

The importance of observability to sovereignty

Cloud sovereignty is more than just data residency compliance; it encompasses security, resilience, and operational traceability. With increasing political scrutiny and more stringent cybersecurity regulations, organizations must have comprehensive observability to monitor, detect, and respond to ICT risks across their operational ecosystems.

With a comprehensive observability platform, organizations can take advantage of the following benefits:

• Support in operational compliance and regulatory adherence. The Dynatrace platform provides continuous monitoring across hybrid and multi-cloud environments, delivering real-time observability into system behavior and access patterns. This transparency supports data residency, operational traceability, and audit readiness—key components of cloud sovereignty—while helping organizations align with regional compliance requirements.
• Strengthened security and risk management. Early threat detection and rapid incident response mitigate risks associated with unauthorized access, data breaches, and sovereignty-related IT challenges.
• Optimized cloud performance and resilience. AI-driven insights and automation help achieve operational continuity, reduce downtime, and identify resilience and dependency risks over critical workloads and data.
• Greater autonomy from providers. A comprehensive observability strategy enables organizations to identify their level of reliance on cloud vendors, assess the impact of different deployment models, and embrace resilient strategies aligned with business objectives.

Achieving these crucial sovereignty benefits requires technology capable of providing complete, uninterrupted visibility across complex environments — precisely where core tracing capabilities from the Dynatrace platform excel.

The role of the Dynatrace observability platform in cloud sovereignty

The cutting-edge observability platform from Dynatrace, combined with Deloitte’s deep-industry and cloud-engineering expertise, supports organizations’ ability to meet their sovereignty requirements. PurePath® is at the heart of the Dynatrace platform’s DNA. The patented distributed tracing technology delivers continuous, end-to-end visibility into application transactions and data flows. With capabilities like automated topology mapping, distributed trace analysis, and real-time anomaly detection, observability solutions like the Dynatrace platform can help institutions maintain service continuity and detect operational issues that could impact compliance or service-level obligations in regulated markets. Check out the video below to learn how enterprises can address data sovereignty challenges using AI-powered observability.

Analyzing real-world applications of observability

With its comprehensive tracing capabilities that provide unparalleled visibility and control, the Dynatrace observability platform should be a cornerstone of data sovereignty.

The whitepaper delves into practical applications of observability in highly-regulated sectors, such as healthcare and financial institutions that may need to retain data in specific geographical locations.

These institutions must implement best practices to meet regulatory obligations, customer expectations, and reduce risks, safeguarding sensitive data and strengthening resilience against cyber threats. By delivering end-to-end visibility into application performance, infrastructure behavior, and user interactions, observability platforms like Dynatrace help financial institutions detect anomalies, trace root causes, and demonstrate operational traceability—key requirements for maintaining regulatory readiness in complex environments.

Future trends and takeaways

The evolution of sovereignty is increasingly shaped by regulatory, geopolitical, and technological forces. Organizations should adopt integrated, compliance-driven architectures to navigate this complex landscape.

Key takeaways include the following:

• Consider observability as a key enabler. Sovereignty is about control, transparency, and strategic autonomy — not just regulatory box-checking.
• Embrace sovereignty by design, powered by observability. Integrate sovereignty into the design phase to prevent compliance and security risks before they occur in production.
• Scale sovereignty through a PoC with measurable outcomes. Dynatrace and Deloitte help organizations embed observability into their cloud strategy through scalable approaches with measurable benefits.

Achieving true cloud sovereignty requires more than just meeting regulatory mandates — it demands a comprehensive approach that enables organizations to reevaluate their cloud strategies. Industry-leading observability solutions from Dynatrace, combined with Deloitte’s expertise in cloud engineering and regulatory strategy, empower organizations to take ownership of their cloud environments with a seamless path to cloud sovereignty.

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© 2025 Dynatrace LLC

Dynatrace and the Dynatrace logo, are trademarks of the Dynatrace, Inc. group of companies. All other trademarks are the property of their respective owners.

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