To help address this challenge, Dynatrace introduced new documentation and best practices for handling sensitive data.

This blog explains why the topic matters, what risks teams are trying to avoid, and how Dynatrace is designed to support privacy-first DEM adoption.

How privacy concerns slow DEM adoption

Across industries, we see the same patterns: Teams want granular and precise visibility to identify meaningful patterns and tailor improvements, while security, privacy, and compliance teams require strong guarantees around sensitive data handling. As a result, DEM adoption can be delayed or remain limited to basic use cases.

This is especially common in regulated environments such as banking and healthcare, where even well-intentioned monitoring can raise questions like:

• Are we collecting more data than necessary?
• Who can access personal data, and under what conditions?
• Are we handling sensitive data appropriately?
• Are we compliant with all our regulatory requirements?

Without clear answers and support, organizations may delay rollout, restrict access too aggressively, or avoid certain capabilities altogether.

Privacy by default in Dynatrace DEM

Dynatrace is designed with privacy-by-design principles:

• User sessions are anonymized out of the box
• Sensitive data can be masked at capture, storage, and read
• Access to sensitive fields is controlled through fine-grained permissions

Privacy settings are configured per frontend (web or mobile) and can be set independently based on each frontend’s risk profile and regulatory context.

Configure Dynatrace DEM for end-to-end compliance

Privacy and compliance should not be blockers to Digital Experience Monitoring, but they do require clear guidance and intentional configuration. Our DEM compliance guide explores two relevant use cases to help organizations identify which configuration options should be considered for their environments:

• Complaint resolution in an e-commerce web app: teams can utilize user tags to quickly identify affected sessions and resolve issues, while access to personal data remains tightly controlled.
• Troubleshooting performance issues in a mobile banking app: teams can gain insights and fix stability or performance issues while fully masking all personally identifying information.

Learn more

To meet data compliance requirements set by industry regulations, organizations must identify specific requirements and outline the steps to protect sensitive data. The new documentation helps organizations to expand or refine their use of Digital Experience Monitoring by demonstrating how to:

• Configure privacy settings for frontends
• Limit data collection
• Control access to sensitive fields
• Support troubleshooting and performance optimization without compromising compliance

The post How to build trust in Digital Experience Monitoring appeared first on Dynatrace news.

If you’ve already wired an AI coding assistant up to Dynatrace, through the MCP server, the Dynatrace CLI (dtctl), or a custom agent you built yourself, you’ve seen your agent have difficulty interpreting data or calling for fields that don’t exist. This makes sense, your agent may be making assumptions based upon training that isn’t relevant. It lacks the skills to understand how to get the best value from Dynatrace. That is where Dynatrace for AI fills the gap.

What are agent skills?

Agent skills are an open format for packaging domain knowledge that AI agents can load on demand. A skill is a folder containing a SKILL.md file with focused instructions, examples, and optional reference material. Compatible agents, such as Claude Code, GitHub Copilot, Cursor, Cline, or others, discover installed skills and load the full content only when it’s relevant to the task at hand.

The net effect: you can install dozens of skills without bloating an agent’s context window. Agents pull in exactly what’s relevant when it’s relevant, and ignore the rest.

Built for agents working with Dynatrace

Dynatrace for AI is a curated set of skills that give an agent the three things it needs to efficiently do real work on Dynatrace:

• Access to Dynatrace data and insights: through DQL queries against Grail®, Smartscape® dependency graph, or problem records.
• Dynatrace expertise: the syntax rules, entity-model distinctions, and query patterns that separate a working query from one that looks correct but returns nothing.
• Task-level starting points: ready-made prompt templates for common engineering workflows, so teams don’t have to invent the approach from scratch.

Skills don’t connect to Dynatrace directly. You have to pair them with the MCP server or dtctl to perform live queries and initiate actions. Together, they turn an agent with generic observability intuition into one that easily extracts value from Dynatrace.

Complement your agent with domain expertise

The first release of Dynatrace for AI agent skills is focused on the workflows that engineering teams run every day:

• DQL fundamentals: covering the pipeline model, core data objects, and when to use fetch, timeseries, or smartscapeNodes to prevent failures that typically come from models trained on generic query-language data.
• Observability across the stack: services, traces, logs, frontends, and problems, each covering the entity model, key fields, and query patterns that make answers correct rather than merely plausible.
• Infrastructure and cloud: covering Kubernetes, AWS, and hosts.
• Platform tasks worth delegating: providing programmatic creation of dashboards and notebooks

Prompt templates for common workflows

Alongside the skills, the repo hosts a small set of prompt templates you can use as structured starting points to invoke the right skills for specific tasks. These save teams from having to design their approach from scratch and make outcomes more consistent across agents and users.

Current templates include:

• Performance regression: walks the agent through comparing RED metrics before and after a deployment, correlating any regression with distributed traces, and summarizing the root cause.
• Daily standup: pulls the last 24 hours of problems, deployment activity, and notable anomalies for a team’s services, so anyone can walk into a standup with the relevant production context already framed.
• Troubleshoot a problem: takes a problem ID and guides the agent through root-cause analysis, including affected entities, correlated events, relevant logs and traces, and creates a structured summary for the incident channel.

These are a starting point, not a ceiling, designed to be forked and shaped to your team’s on-call runbooks.

What Dynatrace for AI is and what it isn’t

Skills and prompts are a knowledge and workflow layer. They don’t connect to your Dynatrace environment, define what actions your agent can take, or set guardrails. That’s the job of the tool you pair them with and your Dynatrace permission model.

The quality of what your agent can produce also depends on the entities your environment is instrumented to capture. Skills help agents ask better questions of data, but they don’t control what data is collected.

Think of this skill as onboarding a smart new hire who already knows software, but needs to learn your platform. The skills are the platform user guide; your observability data is the work itself.

Get started

It’s super simple to install the skills and prompts in one go. Just run:

npx skills add dynatrace/dynatrace-for-ai

…or activate the skills as a Claude Code plugin:

claude plugin marketplace add dynatrace/dynatrace-for-ai
claude plugin install dynatrace@dynatrace-for-ai

Make sure your agent can reach Dynatrace, then try a real agent-skill task. A few good example starting prompts:

• “Compare the error rate of the checkout service over the last hour vs the same hour yesterday.”
• “Are any pods in the production namespace restarting or getting OOM-killed right now?”
• “Use the performance-regression prompt to check the deployment I just shipped.”

The difference in output quality is immediate: fewer corrections, cleaner queries, and answers that accurately reflect how Dynatrace continuously models your environment in real-time.

The Dynatrace for AI project is open source and actively developed. Issues, discussions, and pull requests are all welcome, especially from teams running agent skills against real workloads. We’d love to hear from you.

The post Dynatrace for AI: Teach your AI coding agent how to use Dynatrace appeared first on Dynatrace news.

From generic AI to task‑focused operational agents

Dynatrace ready‑made agents are purpose‑built capabilities that apply Dynatrace intelligence to specific, recurring operational tasks. Each agent focuses on a clearly defined problem, such as explaining why a service is slow, summarizing unusual behavior in an environment, or helping you understand what changed and why it matters. These agents are designed to take a question or a signal based on the exact data that is in your environment and organization and turn it into a useful answer you can act on.

Because Dynatrace agents are ready‑made, there is no need to define prompts, train models, or design behavior from scratch. Each agent already knows:

• What type of input to expect,
• Which Dynatrace signals and context it should use,
• And what output types are most useful for each addressed problem type.

All available ready-made Dynatrace agents can be found in Dynatrace Hub.

Trigger agent actions with Dynatrace Workflows and the Dynatrace MCP Server

Ready‑made agents can be triggered automatically as part of Dynatrace Workflows or available wherever you already work via the Dynatrace MCP Server.

Using agents in Dynatrace Workflows

Dynatrace Workflows lets you run agents in response to events or on a schedule. Instead of manually asking questions about potential problems and remediation steps, the workflow autonomously responds to changes in your environment.

For example, the Kubernetes Troubleshooting Agent runs nine parallel queries for data enrichment, and Dynatrace Intelligence turns all the information into a structured diagnosis. Customize the agents to your needs, including instructions for human approval steps and automated remediation.

The fastest way to get started is with Dynatrace ready-made agentic workflow templates, currently available in a preview release. Instead of building from scratch, you get proven automations that summarize issues, suggest remediation, and deliver insights directly to the tools your teams already use.

Power users can go further by building their own agentic workflows that combine Dynatrace Intelligence actions with any trigger, data source, or integration in Workflows. Use cases range from auto-scaling Kubernetes clusters based on Dynatrace Intelligence forecasts to generating query-cost-optimization recommendations for stakeholders, to virtually any other automation your environment requires.

Using agents through the Dynatrace MCP Server

The Dynatrace MCP Server makes the agents available outside the Dynatrace web UI, without requiring you to deploy or operate any additional infrastructure. You can connect Dynatrace to any MCP‑compatible client in minutes, with no server to install, host, or maintain.

Through the tools exposed by the MCP Server, you can use natural language to query data in Grail®, check system health, and get problem analyses and remediation recommendations. This brings Dynatrace directly into the tools you already use, such as your IDE, Claude Code and Cowork, Microsoft Copilot, Slack, or automation platforms like n8n. The Dynatrace MCP Server also powers integrations with systems like Azure SRE, AWS DevOps, GitHub Copilot, Atlassian Rovo Ops, Amazon Q, and others.

This means agents are no longer tied to a single interface. You can ask Dynatrace questions and get grounded, production‑ready answers wherever you work, using the same agents and intelligence that power Assist and workflows.

Dynatrace Assist: a simple way to test ready-made agents

The quickest way to use a ready‑made agent and see how it works before you start creating a workflow is with . Dynatrace Assist lets you ask questions about your environment using natural language, without switching tools or setting anything up.

A simple way to start is with a real problem you already have. For example, when a service becomes slow, open Assist and ask a question such as “Summarize the open problems and highlight those that need immediate attention.” Assist interprets the question, evaluates the environment you’re working in, and pulls together relevant data and context using Dynatrace Intelligence. Instead of manually navigating metrics, traces, logs, and dependencies, you get an explanation grounded in what is actually happening in your system.

Continuing your conversation with Assist, you can refine the question or follow suggested drill‑downs. Assist supports this as a single flow, helping you move from an initial question to deeper analysis and, where applicable, to next steps. You’re not configuring an agent or defining behavior. You’re simply asking a question and letting Dynatrace coordinate the right intelligence and ready‑made agents behind the scenes.

This makes Assist your lowest‑friction entry point for using Dynatrace agents. You get a concrete result quickly, using the same data and context you already rely on in your daily work.

What’s next?

If you haven’t already, open Dynatrace Playground, or your Dynatrace tenant, and ask Dynatrace Assist a question to see the ready-made agents in action.

The post Dynatrace AI agents begin working for you on day one, and are built to grow with you appeared first on Dynatrace news.

Get immediate production visibility inside Claude Code, the next-gen AI coding assistant from Anthropic. The Dynatrace MCP server can now be used as a ready-to-use connector for Claude Code, Cowork, and Chat. Connect in minutes to query logs, traces, and problems; conduct live debugging from your terminal, and validate AI-first workflows with real data.

Model Context Protocol (MCP) is the standard for connecting AI assistants to live tools and data. The Dynatrace MCP server brings your full observability and security context into every Claude session. This means fewer context switches, less time hunting through dashboards, and better answers that are grounded in what’s actually happening in your environment.

How to connect Claude Code with Dynatrace

Getting started is straightforward. Open Claude, go to Connectors, and search for “Dynatrace.” Install the Dynatrace MCP Server connector, follow the setup steps, and you’re connected.

How Dynatrace MCP Server and Claude give you visibility into your production data

Whether you’re investigating a production issue, reviewing a deployment, or working through a security vulnerability, you can ask Claude in plain language and get answers backed by your actual Dynatrace production data. This is not just documentation summaries or generic guidance, but a real window into production.

Troubleshoot without leaving Claude Code

Let’s say you receive a Jira ticket with details of an error. Instead of switching to dashboards and digging through logs to find out what went wrong, you can now ask Claude. Dynatrace pulls all root-cause information, related logs, metrics, traces, and CPU and memory profiling data from your production environment directly into the session. You can query these details by impact, filter by service, and request remediation suggestions, all without knowing in advance where to look or how to write the DQL query.

This same workflow applies when you’re checking for vulnerabilities in your running workloads, verifying whether a recent deployment introduced regressions, or proactively catching performance issues before they hit production.

You can now also use dtctl, the open source CLI for the Dynatrace platform, in Claude Code alongside the Dynatrace MCP server to manage dashboards, run workflows, and execute DQL from your terminal.

The post Bring real-time production insights into Claude Code with the Dynatrace MCP Server appeared first on Dynatrace news.

What Agent Mode can do with Dynatrace observability data

Once connected with Dynatrace MCP Server, Postman’s Agent Mode works with real runtime data rather than just API requests and responses. When an API test fails or behaves unexpectedly, the agent can correlate the behavior with Dynatrace telemetry such as service metrics, traces, logs, and detected anomalies.

This allows developers to quickly understand whether an issue is caused by the API itself or by what’s happening behind it, such as a slow dependency, a failing backend service, or a recent change impacting runtime behavior. Because this context comes directly from Dynatrace, developers can ask follow‑up questions in natural language and get answers grounded in production data. All of this happens inside the Postman workflow, without switching tools or manually querying observability dashboards.

The result is a faster feedback loop: APIs can be tested, validated, and debugged with awareness of how they actually behave in live environments, not just how they respond in isolation.

Explore Dynatrace use cases with Postman

This integration is most valuable in situations where API behavior needs to be understood in the context of how systems actually run, not just how endpoints respond in isolation.

Common scenarios

Instantly check Dynatrace environment health in Postman

Quickly connect Dynatrace as an MCP server in Postman, set up environment variables, and use natural language prompts to get a real-time overview of open problems in your monitored environment. This streamlines troubleshooting by surfacing actionable issues directly in Postman, saving you time and reducing context switching.

Diagnose and resolve API failures with Dynatrace insights

By running API tests and intentionally triggering failures, you can leverage the MCP server to pinpoint the root causes of errors, such as backend issues or logic bugs, using the real-time insights from Dynatrace. This empowers developers and testers to quickly distinguish between code and infrastructure problems, accelerating debugging and improving application reliability.

Get a holistic application health assessment in Postman

You can ask the MCP server in Postman broad, natural-language questions about the overall health of your application and the services monitored by Dynatrace. The server provides a summary of performance and health across multiple services, highlights slow endpoints, and offers actionable recommendations. This allows you to quickly identify bottlenecks and focus on critical issues, supporting proactive performance management and efficient troubleshooting.

Automate continuous health checks with Postman collections

You can have Postman automatically generate collections that call Dynatrace endpoints on a schedule, enabling ongoing performance and health monitoring between releases. This ensures teams are proactively alerted to issues, supporting continuous delivery and higher service quality.

Reduce guesswork in AI-assisted workflows

AI‑assisted development is only as effective as the context an agent can access. Without reliable runtime data, agents are limited to reasoning from API definitions, test results, and assumptions, making it difficult to distinguish real system issues from surface‑level symptoms.

By connecting Postman’s Agent Mode to Dynatrace through MCP, agents can ground their reasoning in trusted observability data from live systems. This gives the agent access to the same production signals developers rely on today, such as service health, performance trends, errors, and dependencies, rather than relying on inferred behavior alone.

The result is more actionable AI assistance. Instead of guessing why an API behaves a certain way, the agent can explain what is happening in the system and why, reducing false conclusions and improving the quality of recommendations in AI‑driven workflows.

Try Postman’s Agent Mode with Dynatrace

The Dynatrace MCP Server is available in the Postman MCP Catalog and can be connected to Postman’s Agent Mode to bring runtime observability data directly into API workflows.

• Learn more about the Dynatrace MCP Server on Dynatrace Hub

• Try out Agent Mode with the Dynatrace MCP server:

For teams already using Dynatrace and Postman, this is a straightforward way to add production context to AI‑assisted API development. For teams exploring Agent Mode, it provides a practical foundation for grounding agent workflows in real system behavior.

The post Observe API responses to runtime behavior: Connect Postman’s Agent Mode with Dynatrace appeared first on Dynatrace news.

AI is changing the way we work, from boosting our efficiency and executing tasks on our behalf. As AI enters the agentic era, Dynatrace Assist is your trusted partner for working smarter with Dynatrace. Powered by Dynatrace Intelligence, it helps you solve problems faster and brings AI into your daily workflow.

Today, we’re announcing Dynatrace Assist, our next-generation AI chat that goes far beyond answering questions. It lives where you work, understands your environment, and helps you get real work done with the full power of Dynatrace Intelligence behind every interaction.

Dynatrace Assist is the evolution of Davis CoPilot®, but make no mistake: this is much more than a rebranding. It’s a paradigm shift in capability, outcome, and value.

Your agentic partner helps you gather insights

Dynatrace Assist is where the full power of Dynatrace Intelligence, the new Dynatrace agentic operations system, is available at your fingertips. Instead of moving between dashboards, queries, and tools, you can simply start with the conversational interface: ask a question and let Dynatrace Intelligence do the work.

Dynatrace Intelligence interprets your prompt using generative, causal, and predictive AI capabilities to understand what you’re trying to achieve. Like a member of your team, Assist pulls together context from Grail, maps relationships utilizing Smartscape’s dependency graph, and collaborates in real time with Dynatrace agents. As the conversation unfolds, you move from understanding to exploration—following suggested drill-downs, refining your analysis, and understanding the next steps. This allows for a single, seamless flow from question to insight to execution.

Multi-step reasoning that understands your environment

Assist doesn’t just do what you ask—it thinks several steps ahead. It helps you understand the why, decide what to do, and see what comes next. And all of this is fully transparent, showing you exactly which data backs each decision, so you can trust the recommendations and proceed decisively and confidently.

Under the hood, Assist combines Grail’s unified data lakehouse with Smartscape’s dependency graph, layered with our causal and predictive AI. By leveraging the same tools that are hosted on the Dynatrace MCP Server, Assist can pull insights from any part of your environment and kick off deeper analysis when needed.

From incident to remediation in a single flow

AI on its own is meaningless. AI needs context and data to deliver real value, and you need intelligence that understands your environment and helps you move faster with confidence. Dynatrace Assist is built for exactly that. It works alongside you, sharpening decisions, removing friction from investigations, and accelerating the steps that typically slow teams down.

Let’s look at the following example: when a production issue arises, teams waste precious minutes jumping between dashboards, logs, and alerts to reconstruct what went wrong and determine the next steps.

Investigations start with a simple question like “Summarize all open problems and highlight those that need remediation.” Assist immediately pulls together the evidence. It connects Grail data, Smartscape relationships, and real-time signals from Dynatrace agents to piece together a clear explanation of the issue. Instead of scattered clues, Assist collaboratively guides you in selecting a problem to focus on and recommends how to remediate it. This continuous flow compresses investigation time, reduces MTTR, and gives teams a controlled way to move from insight to remediation without breaking focus.

Explain raw data with actionable insights

Logs, signals, and low‑level data points often require deep domain knowledge to interpret. In large digital environments, that knowledge is spread across different teams, which means understanding what a particular message means, how serious it is, and whether it requires action can easily slow teams down.

When you select a log entry (or another signal in Dynatrace) and ask Dynatrace Assist to explain it, it responds like an expert colleague with the necessary domain knowledge and an understanding of the system’s inner workings. It interprets the data in context, highlights what is important, clarifies the potential impact, and outlines likely causes or sensible next steps. Instead of searching for error codes elsewhere or waiting for someone with deeper expertise, teams get immediate clarity. This turns raw, technical signals into practical guidance and shortens the path from confusion to confident action.

Identify and respond to critical vulnerabilities

Vulnerabilities in your system significantly increase the risk of critical incidents, such as data loss or unauthorized access. When a new vulnerability alert appears, teams need immediate clarity about what it means, which services are exposed, and what actions they should take.

With a series of simple prompts, such as described below, Assist pulls in security findings, maps the impacted components across Smartscape, and identifies the root cause. It guides you through the decision-making process, including proposing a fix to the identified problem. All without leaving Dynatrace or switching between tabs, applications, or tools. This tight loop gives teams a faster understanding, more consistent responses, and a significantly reduced risk window.

Prompts used in this use case:

1. Are there any open threats I need to be aware of?
2. Investigate the SQL injection vulnerabilities and provide more details.
3. Show me input for <<add your vulnerability>>.
4. Give me a fixed query.

Dynatrace Assist is here, and it’s just the beginning

Dynatrace Assist doesn’t replace your expertise; it amplifies it, so you can resolve issues sooner, uncover insights more naturally, and move from intention to outcome with far less effort. It is your gateway to Dynatrace Intelligence, which makes you and your teams more productive, accelerates your operations, and uses the full Dynatrace platform to deliver real outcomes.

Ask. Analyze. Act.

And start today with Dynatrace Assist.

The post Dynatrace Assist: Ask, analyze, and act with Dynatrace Intelligence appeared first on Dynatrace news.

Agentic AI is no longer a concept—it’s a catalyst for enterprise transformation. According to the Boston Consulting Group, organizations that embed AI agents into workflows, rather than simply bolting them on, are achieving 30–50% faster processes and reducing low-value work by up to 40%. These gains come when autonomy is balanced with human oversight and governance from day one. Dynatrace is facilitating this shift through an agentic ecosystem that connects trusted, real-time production context to AI agents across development, operations, and security.

AI is only as smart as the data it works with and only as effective as the workflows it’s embedded into.

Agentic ecosystem as part of the agentic operations system

With the launch of Dynatrace Intelligence, the Dynatrace platform has evolved into an agentic operations system that provides autonomous, intelligent collaboration across development, operations, and business workflows. It’s uniquely architected to power real-time, autonomous operations by orchestrating both ready-made Dynatrace agents and external ecosystem agents.

Whether it’s invoking a coding agent, optimizing your cloud or Kubernetes infrastructure, or creating a ticket, Dynatrace Intelligence coordinates bi-directional interactions between agents in the agentic ecosystem, including AWS Kiro, GitHub Copilot, ServiceNow Assist, Azure SRE agent, Atlassian Rovo Ops, and many others.

A trusted ecosystem is one where agents and AI assistants in your IDEs, ITSM suites, and other tools can securely connect to Dynatrace to interact with real-time observability and production data in context (metrics, logs, traces, topology, vulnerabilities), reason with causal intelligence, and take actions based on smart workflows—all under your supervision, and designed to achieve the goals you define.

Ecosystem architecture

Our three-layer architecture provides precision, governance, and extensibility, allowing teams to innovate without compromising control.

• Grail®, the unified data lakehouse, and Smartscape®, Dynatrace’s real-time dependency graph, provide the technical foundation, analyzing dependencies across business, teams, services, processes, infrastructure, and more. They ensure that Dynatrace Intelligence acts based on facts, not guesses, and ensure its AI-powered decisions are accurate and actionable, as a prerequisite for autonomous operations.
• The Dynatrace MCP server provides connectivity to the Dynatrace platform as well as the necessary tools for interacting with Dynatrace Intelligence to automate tasks, triage problems, perform risk assessments, or update business workflows.
• Agentic workflows, ready-made agents, and ecosystem agents address real-world use cases: from crash inspection to vulnerability remediation, Kubernetes optimization, or improving developer productivity.

Real agentic ecosystem use cases for developers, SREs, and IT Ops engineers you can implement today

The selected examples below show how AI‑powered, production‑aware workflows remove friction and accelerate real outcomes across development, operations, and security. For more scenarios and use cases showing what you can already unlock with our agentic ecosystem, explore our Dynatrace agentic ecosystem integration blog posts.

AI-accelerated troubleshooting and development in your IDE

Developers often lack immediate access to deep production context when debugging or optimizing services. Moving between terminals, dashboards, and monitoring tools interrupts flow, slows investigation, and forces teams to rely on partial information. This creates delays in identifying issues, verifying changes, and understanding real performance impact, wasting time to understand what’s happening in production. A single incident forces them out of their IDE and into complex tool‑hunting, increasing cognitive load and slowing onboarding and MTTR.

The Dynatrace integration with Amazon Kiro brings real‑time observability directly into the developer’s terminal. Using natural‑language prompts, developers can instantly retrieve live metrics, logs, traces, problem context, and topology insights from Dynatrace without leaving Kiro. This eliminates context switching, accelerates diagnosis, and allows rapid decision‑making in the exact moment developers need clarity. With production‑accurate insights available inline, teams ship fixes faster, understand impact sooner, and maintain high development velocity with minimal friction.

Or use Dynatrace with GitHub Copilot to bring real‑time production insight—logs, traces, root‑cause details, and security context—directly into VS Code. Copilot retrieves precise Dynatrace intelligence through natural‑language prompts, helping developers diagnose issues, validate vulnerabilities, and verify builds without ever leaving their coding flow. The result is immediate troubleshooting, dramatically reduced context switching, faster fixes, and a smoother, more productive development experience.

AI‑assisted SRE operations with autonomous cloud investigations

SRE teams are under constant pressure to maintain reliability across increasingly complex, distributed cloud environments. When a degradation occurs, they must manually trace symptoms across layers, correlate signals from multiple cloud providers, and determine whether the issue is caused by code, infrastructure, configuration drift, or external dependencies. This slows down detection, clouds impact assessment, and leads to long, expensive recovery cycles, especially when incidents span AWS, Azure, or hybrid environments.

Dynatrace integrates with both the Azure SRE Agent and the AWS DevOps Agent to deliver autonomous, context‑aware cloud investigations. When an issue emerges, these agents surface precise, real‑time intelligence from Dynatrace, such as causal root‑cause analysis, dependency graphs, impact radius, service health, and cloud resource anomalies, all directly where SREs work. The agents evaluate the situation, propose remediation steps, and, when approved, trigger automated fixes using Dynatrace workflows or native cloud actions. This eliminates the slow, manual stitching together of cloud and observability data, accelerates root‑cause identification, and allows for faster, safer recovery. SRE teams gain clear, actionable insights within seconds, reduce MTTR dramatically, and advance toward autonomous operations across multi‑cloud environments.

AI‑powered incident management with real‑time production context

Most incident tickets arrive with almost no meaningful context—just a timestamp, a vague description, or a user complaint. Engineers don’t know the severity, which systems are impacted, or what caused the issue. They waste precious time switching between monitoring tools, dashboards, and logs just to piece together the basics. This slows response times, drives up costs, and keeps MTTR far higher than it should be.

By integrating Dynatrace with Atlassian’s Rovo Ops agent, you get real‑time production insights directly into Jira Service Management. Dynatrace automatically detects problems, ties them to their causal root, maps dependencies, and understands impact across the entire ecosystem. This context is then surfaced directly in Service Manager, with no tool‑switching required. Engineers instantly see what’s happening, who’s affected, and the actions needed to resolve the issue. The result is dramatically faster diagnosis, smarter remediation, and a significant reduction in MTTR—all powered by live, trustworthy production context delivered exactly where teams work.

AI success is about people and processes

Adding agents to legacy processes won’t deliver meaningful outcomes. Successful agentic AI projects require real transformation, not just technology adoption. Such a transformation needs a strong and trusted foundation. A platform that provides trusted, contextual data ready to support enterprise-level requirements for agents to make the right decisions and act intelligently, and trusted ecosystem partners.

Together, Dynatrace provides reliable agentic AI-powered observability, helping organizations build more resilient applications and deliver better customer experiences.

How to get started

Identify a developer or small team to get started. Connect your MCP client with the Dynatrace MCP Server, get inspired by recent agentic ecosystem blog posts covering use cases for developers, SREs, and IT Ops engineers, or have a look at our documentation to learn more.

Go to Dynatrace Hub to connect to Dynatrace MCP server.

The post Dynatrace agentic ecosystem: Drive real outcomes, not AI pilots appeared first on Dynatrace news.

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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As digital transformation accelerates across Europe, data sovereignty has become a growing area of focus for public sector entities, financial institutions, telecom providers, and many other organizations operating in the EU. EU organizations are increasingly seeking to maintain control over their data, striving to ensure compliance with regional regulations and address geopolitical risk considerations. While most sectors don’t require full sovereign cloud solutions, there is an observable trend toward enhanced data sovereignty, encryption control, and transparency into data flows.

Understanding the drivers of EU sovereignty needs

During discussions with our customers, we noticed several developments that are contributing to the increased emphasis on sovereignty in the EU cloud landscape:

• Regulatory: Regulations such as the General Data Protection Regulation (GDPR), Digital Operational Resilience Act (DORA), NIS2 Directive, and national-level data protection laws require organizations to retain control over data access, processing, and storage.
• Geopolitical: Government agencies and regulated sectors seek to increase security and trust by reducing reliance and dependency on foreign jurisdictions, and by placing increased emphasis on minimizing unauthorized access and ensuring that data remains within their jurisdiction.
• Economic: Organizations aim to future-proof their digital systems by increasing customer trust through transparency, autonomy, and improving operational and business resilience.
• Strategic autonomy: EU initiatives, such as GAIA-X and related national programs, reflect policy interest in greater digital and technological independence.

How Dynatrace currently supports sovereignty requirements

Dynatrace provides capabilities designed to help organizations address sovereignty-related expectations while benefiting from SaaS observability:

• EU hosting: Dynatrace allows customers to select data center regions within the EU when deploying on AWS, Azure, or GCP. This supports data residency requirements.
• Security certifications: Dynatrace aligns with internationally recognized standards, including ISO 27001, SOC 2, and CSA STAR, and supports GDPR compliance. Visit the Dynatrace Trust Center for the full list.
• Compliance and governance capabilities: Role-based access control (RBAC), SSO, SCIM provisioning, sensitive data handling, audit logging support, adherence to organizational security and regulatory practices, and more as described in Dynatrace Documentation.
• Observability-driven sovereignty: With PurePath®, Smartscape®, and other core platform capabilities, Dynatrace provides end-to-end tracing, real-time topology mapping, and further support for data visibility and system behavior.
• All data transfers are governed by EU Standard Contractual Clauses (SCCs) in alignment with GDPR requirements

Looking ahead: Enhancing support for data sovereignty

Dynatrace plans to expand support for sovereignty-focused use cases. Some of the upcoming developments include the release of Bring Your Own Key (BYOK) and Sensitive Data Scanner*.

BYOK is expected to allow customers to manage and retain control over the encryption keys used for securing observability data. This is intended to support:

• Jurisdictional control: Customers can benefit from increased governance by managing their own encryption keys.
• Trust and transparency: Organizations can align with internal data protection policies and sector-specific requirements.

Sensitive Data Scanner adds another level of protection to Dynatrace’s existing sensitive data masking capabilities. It monitors Grail for unintentionally ingested sensitive data in logs, allowing customers to validate their masking configuration, quickly identify and respond to inconsistencies, and take precise and targeted corrective action for future data ingestion and sensitive data that has already been ingested, such as adjusting access permissions and retention periods, deleting sensitive data, and updating masking rules to prevent sensitive data types from being stored in the future.

Supporting the public sector and regulated industries

For use cases that require enhanced privacy or offline environments, Dynatrace also offers Dynatrace Managed as an on-premises solution, giving you greater control over operations and data. This alternative can be particularly relevant for highly regulated government entities that require such control.

Dynatrace recognizes that sovereignty requirements vary by sector and region. We’re focused on providing secure and flexible observability solutions that support compliance and transparency in accordance with customer and regulatory expectations.

Sovereignty isn’t just about where your data lives—it’s about who governs it. And Dynatrace can help you govern your data better.

What’s next

Share this blog post with your security or compliance teams to help them understand how Dynatrace supports their data and digital sovereignty requirements. (To email this blog post, select the email icon at the top of the page.)

* This blog post contains forward-looking statements. These statements reflect current views and assumptions, but results might differ due to various risks or plan changes.

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In this blog post, you’ll learn how Dynatrace allows you to manage observability data at scale by providing sensitive data handling capabilities across the entire data lifecycle on the Dynatrace platform. Preventing sensitive data from leaving the customers environment, using OpenPipeline™ to efficiently enrich, contextualize and ingest huge volumes of data, leveraging Grail™ data lakehouse for unified storage for all data types, with a wide range of regions to select from to meet your data residency needs, and leveraging other platform capabilities such as controlling access to data, or enabling to delete only the selected records permanently, helps significantly reduce the complexity of managing different data types typically stored in silos.

Why sensitive data management is important

Whether a bank, government, or airline, observability is no longer optional for any organization’s IT systems that must provide high-quality and secure services to its customers and end-users. These systems generate vast amounts of data, and sensitive data might be embedded in such large-scale volumes of data.

To maintain customer trust and comply with stringent regulatory requirements, such as GDPR or HIPAA, organizations need to manage sensitive data appropriately, not only in their own IT environment but also in their observability platform and other third-party services. Sensitive data isn’t required for the majority of observability use cases. Organizations should control which data is captured, how it’s processed, where it’s stored, and who can access it. Additionally, organizations must promptly address data subject and privacy rights requests and adhere to retention periods, all in line with their privacy policies and regulations.

Manage sensitive data at scale in complex IT environments

Big IT environments often use thousands of apps and digital services managed by different teams. Each app generates a significant amount of observability data, often with different structures and sensitive data types. In such complex environments, it’s essential to not only detect sensitive data and configure how the observability platform handles such data but also validate that the configuration works as intended and permanently remove selected sensitive data, if needed, without compromising the remaining data and the larger dataset.

End-to-end sensitive data handling in Dynatrace

The Dynatrace data lifecycle consists of five steps.

While all data sent to Dynatrace is encrypted in transit and storage, each step provides you with the capabilities and controls needed to manage your sensitive data. While this blog post focuses on privacy controls and managing sensitive data in Dynatrace, you might be interested in how Dynatrace protects your data overall. Check our Trust Center for an overview or Dynatrace Documentation for the complete list and description of security and privacy controls in Dynatrace.

1. Data capture

When using Dynatrace OneAgent® and Dynatrace Collector for OpenTelemetry data, sensitive data matching the masking rules is irreversibly redacted at its first contact with Dynatrace and doesn’t leave the monitored environment.

This is often a crucial requirement for organizations operating in highly regulated industries. Take, for example, a financial institution using Dynatrace Log Analytics to monitor and analyze SWIFT message logs across its global infrastructure. These logs and other user behavioral data are essential for tracking transaction flows, detecting anomalies, and ensuring regulatory compliance. However, given the sensitive nature of the data, such as account identifiers and payment instructions, they must enforce robust privacy controls to comply with regulations like GDPR and other industry standards. One of those rules is that sensitive data must not leave their environment.

To address this, the institution leverages Dynatrace’s multi-layered data masking capabilities. Before log data leaves the environment, Dynatrace OneAgent applies user-configured masking rules at capture to, for example, allow for the redacting of the account number, name, date of birth, and address of the account holder and beneficiaries.

2. Data processing

Data sent to Dynatrace is processed in OpenPipeline™, a powerful solution for ingesting and enriching huge volumes of data quickly and cost-effectively, while allowing configuration to allow secure and compliant collection and processing. With OpenPipeline, organizations can define processing rules that automatically mask or redact sensitive data such as credit card numbers, email addresses, or IP addresses, regardless of the source. This approach allows flexible, centralized masking, protecting sensitive data before it‘s stored or made available for analysis.

3. Data storage

Data localization and residency are becoming increasingly important for organizations to address various strategic, regulatory, and operational requirements. By keeping data within specific geographic regions, organizations can comply with local laws, regulations, and sector-specific requirements. For this purpose, Dynatrace can be deployed to AWS, Azure, and Google Cloud regions across the globe and thus support most of its customers in storing their data within their preferred region.

Data ingested into Dynatrace is stored in the Grail™ data lakehouse, a unified data storage system for unifying and contextually analyzing observability, security, and business data at any scale.

In addition to the location where sensitive data is stored, it’s crucial not to store such data for longer than needed. Dynatrace allows configurable retention periods for custom Grail buckets, such as up to 10 years for logs and distributed traces.

Some customers also store logs for audit purposes. Depending on your country and industry, you might be required to store audit logs for five or even up to 10 years, a practice your Dynatrace tenant supports.

The logs stored in Grail are always accessible by any app and user who has permission to do so. This minimizes the time and cost in case historical data must be accessed by an auditor, as there is no such process of rehydration or concept of hot/cold-storage tiers.

Dynatrace makes subject rights management easy with the Privacy Rights app. Authorized users can efficiently search for all personal data related to a specific individual, review the results, and approve export or deletion requests in a secure, auditable workflow meeting regulatory deadlines. This helps organizations fulfill data subject rights requests, such as those required under GDPR and CCPA.

4. Data access

Granular and configurable data access is essential for protecting sensitive data and ensuring only authorized users can view and interact with stored data. Grail access in Dynatrace is managed through a flexible, fine-grained permission system that allows administrators to control who can access data at multiple levels, from buckets to tables and records down to the field level.

A healthcare diagnostics provider partnered with us to enhance their observability while ensuring HIPAA compliance and protecting PHI/PII. In addition to masking and redacting PHI/PII fields at ingest, they configured granular field-level access controls, allowing their teams to view only the data relevant to their roles. This way, Dynatrace empowers providers with secure, compliant, actionable insights from their logs without compromising patient privacy.

5. Data deletion

Dynatrace allows organizations to meet strict privacy and compliance requirements by supporting hard deletion of individual records in Grail. This capability, available via Grail API and Privacy Rights, ensures that information can be securely and permanently removed at the record level, without impacting the integrity or availability of other valuable data. An audit trail is maintained for deletions directly executed through the API and those orchestrated by the Privacy Rights app. Unlike soft deletion, which might only hide data, hard deletion in Grail guarantees that deleted records are irreversibly erased, reducing the risk of unauthorized access and supporting full regulatory compliance.

Sensitive Data Center

Later this year, Dynatrace will start integrating its sensitive data handling capabilities into the new Sensitive Data Center* to help streamline the management of sensitive data. In the first step, we’ll combine the existing Privacy Rights with the planned, and currently in development, Sensitive Data Scanner*.

Sensitive Data Scanner adds another level of protection to Dynatrace’s existing sensitive data masking capabilities. It monitors Grail for unintentionally ingested sensitive data in logs, allowing customers to validate their masking configuration, quickly identify and respond to inconsistencies, and take precise and targeted corrective action for future data ingestion and sensitive data that has already been ingested, such as adjusting access permissions and retention periods, deleting sensitive data, and updating masking rules to prevent sensitive data types from being stored in the future.

Summary

You’ve learned about how Dynatrace helps you manage sensitive data securely and in compliance with regulations throughout its lifecycle. Dynatrace focuses on privacy from the moment data is captured, using advanced masking techniques to prevent sensitive information from leaving the environment, and through centralized data processing and unified data storage, including supporting data residency and retention controls. Dynatrace supports compliance for many global and industry-specific standards. Fine-grained access controls and hard-deletion capabilities further empower organizations to manage data governance and fulfill privacy obligations like GDPR and CCPA. Overall, Dynatrace offers a comprehensive, privacy-first approach to observability that aligns with operational needs and regulatory demands.

* This blog post contains forward-looking statements. These statements reflect current views and assumptions, but results might differ due to various risks or plan changes.

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Automation can help European banks save 50-70% of effort in DORA compliance

The journey to continuous DORA compliance can be summarized in three steps:

1. Continuous monitoring of IT environments
2. Proactive incident prevention and handling
3. Ongoing management of compliance requirements

These efforts demand significant resources, time, and operational bandwidth. Manual processes are prone to human error and inefficiencies which can lead to compliance gaps, posing substantial risks to financial institutions. The strain on resources can divert attention from core business activities, negatively impacting overall productivity and growth.

“We estimate that with Dynatrace, organizations can automate up to 80% of the technical tasks necessary to be DORA compliant, helping reduce the overall required time and personnel by 50-70%. Unifying observability and security not only helps save significant time and effort, it also provides the necessary visibility into the organization’s IT environment and helps to achieve continuous compliance,” said Bernd Greifeneder, Founder and Chief Technology Officer, Dynatrace.

Customers have shared that our platform has helped them save significant time and increase productivity by reducing mean time to discovery (MTTD) by 99%, time spent on root cause analysis by 80%, and mean time to resolution by 80%, among many other customer success stories with Dynatrace. Taking those into account and understanding how we use Dynatrace for self-monitoring, our analysis suggests that using unified observability and security from Dynatrace can lead to saving up to 50% – 70% of the effort required to manage DORA compliance.

Based on the above, we estimate the following effort needed for DORA compliance in a medium to large bank operating in multiple EU markets, with 5,000 to 20,000 employees.

Estimated effort for DORA compliance with minimum automation

• Initial phase (12 – 24 months): 50 – 100 people
• Ongoing management: 20 – 30 people

Estimated effort for DORA compliance with automation

• Initial phase (6 – 12 months): 20 – 60 people
• Ongoing management: 5 – 10 people

Continuous monitoring of IT environments

Because DORA requires continuous compliance, a snapshot of an institution’s compliance with DORA is often insufficient. In complex IT environments, new services, applications, and other components can be added or removed at any time. Manually monitoring those changes and updating the map of the entire IT environment each time a change occurs is quite labor intensive.

Dynatrace helps cross-functional teams (comprising IT managers, compliance officers, risk managers, and others) save significant amounts of time through real-time monitoring of the entire IT environment. Dynatrace provides up-to-date network maps, identifies critical services, and highlights gaps in coverage.

Proactive incident prevention and handling

Reacting quickly to incidents when they occur isn’t sufficient. Any incident can negatively impact service availability, and even a swift reaction might not prevent financial, reputational, or societal damage from happening. Proactive risk management and prevention are crucial and are reflected in DORA and other similar frameworks.

In a continuously monitored IT environment and leveraging Davis® AI, Dynatrace helps security and incident response teams detect abnormal behavior, identify root causes, and detect vulnerabilities and attacks on your IT environment—all in real time, with prioritization based on business impact. Remediation activities can be triggered automatically, supporting timely and efficient incident handling.

Ongoing management of compliance requirements

DORA comes with technical best practices and standards for IT environments. Tracking, validating, and remediating potential findings is a labor-intensive task necessary to keep the environment compliant and provide evidence for auditing.

Dynatrace helps IT and compliance teams continuously assess their IT environments against DORA standards, at scale, and relative to current and future growth. Dynatrace gathers all relevant findings on security posture with full context and creates a holistic and intuitive way to prioritize, remediate, and report on those findings.

Increase productivity beyond DORA compliance

Dynatrace helps simplify the compliance process and delivers substantial value to organizations. By automating compliance efforts, you can:

• Reduce operational costs: Lower the personnel and time required for compliance.
• Enhance accuracy and efficiency: Minimize human error and increase productivity in achieving continuous compliance.
• Improve operational resilience: Proactively manage compliance and mitigate risks.
• Focus on core business activities: Free up resources to drive growth and innovation.

Based on the above-mentioned use case for DORA compliance, we estimate that adopting Dynatrace can help organizations save significant time and resources needed to achieve and manage DORA, NIS2, PS21/3, CPS 230, and similar cybersecurity and resilience compliance frameworks, translating into substantial cost savings and operational efficiencies.

What next?

In the face of stringent regulatory requirements, automating DORA compliance with Dynatrace offers a strategic advantage for financial institutions. It assists with efforts to achieve continuous compliance and helps enhance operational resilience, reduce costs, and free up resources for core business activities. Integrating Dynatrace into organizations’ compliance strategy can be a valuable step for executives and senior management to help secure their organizations’ future.

Read the blog post, Dynatrace for executives: Security compliance from our CTO, to understand better how integrating Dynatrace into your compliance strategy helps your business be more resilient and compliant and provides a strategic advantage in today’s dynamic regulatory landscape.

Disclaimer: The estimated effort savings are based on analyzing how customers use Dynatrace and on internal research. They are intended for informational purposes only. Actual results may vary depending on individual organizational factors. Organizations should conduct their own assessments and planning to determine the most appropriate approach for achieving and managing DORA compliance. Dynatrace does not guarantee specific outcomes or savings.

The post How automation helps financial institutions efficiently achieve continuous compliance with DORA appeared first on Dynatrace news.

What is TX-RAMP?

The Texas Risk and Authorization Management Program (TX-RAMP) provides a standardized approach for security assessment, certification, and continuous monitoring of cloud computing services that process the data of Texas state agencies. TX-RAMP certification requires cloud service providers to meet the stringent security and privacy standards set by the Texas Department of Information Resources (DIR).

TX-RAMP Level 2 Certification is the required minimum certification level for a cloud computing service that processes, stores, or transmits agency data determined to be confidential and from a moderate or high-impact information resource.

Dynatrace partners with Texas state institutions

Dynatrace partners with public sector agencies in the US and globally to ensure that essential government and educational institutions deliver resilient, efficient, and secure services. Complex IT environments that house these services are often built on hybrid and multicloud architectures. Ensuring application security, resilience, and efficient operations with limited resources in the public sector requires a solution that provides precise answers and intelligent automation from enormous amounts of cloud data while meeting the strictest cybersecurity standards.

Receiving TX-RAMP Level 2 certification confirms that the Dynatrace platform meets these standards and allows Texas state institutions to ensure flawless and secure digital services for its residents.

Unified observability and security accelerate digital transformation initiatives

Satisfaction with services provided by state and local government agencies strongly influences trust in those agencies. The opportunities that digital and cloud-based technologies provide constantly increase expectations for providing these services digitally and without disruptions. To achieve this, state and local government agencies must undergo digital transformation so that their services are cost-efficient, secure, and resilient.

Whether in an enterprise or state agency, technology executives are aware that observability is the foundation for managing the health of cloud and IT services. The right observability platform with observability, security, and other data in context makes the difference in increasing IT productivity, reducing business risks, optimizing costs, and reducing carbon footprint.

Our commitment to enterprise-level security

As shown by our broad range of certifications and accreditations, security is a core value at Dynatrace. Adding TX-RAMP highlights our dedication to excellence. We’re focused on ongoing improvements to maintain the highest security standards and deliver exceptional service, providing our customers with a safe and governed environment.

What’s next

Contact Dynatrace to discuss how we can support your cloud transformation and provide cost-efficient, resilient and secure services for Texas residents.

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The Importance of Resilience in a Complex Regulatory Landscape

In today’s digital age, operational resilience is paramount for businesses striving to maintain seamless operations and safeguard their reputation. The ability to quickly react to incidents is no longer sufficient; organizations must proactively prevent issues and manage risks to ensure continuous service delivery. This need is amplified by an increasingly complex regulatory and compliance landscape, where global standards demand stringent measures to protect data, ensure service continuity, and mitigate risks.

Navigating these regulations while maintaining high performance and security standards is challenging. Non-compliance can lead to operational disruptions, severe penalties, and reputational damage. Therefore, achieving operational resilience is not just about compliance; it’s about ensuring long-term sustainability and protecting the business against potential threats.

Dynatrace: Your Partner in Compliance and Resilience

Compliance and resilience capabilities leverage the industry-leading Dynatrace platform for unified observability and security, including the upcoming Compliance Assistant app for DORA compliance. They offer a comprehensive solution to these challenges, providing functionalities designed to enhance compliance and resilience in IT environments. Here’s how Dynatrace can help automate up to 80% of technical tasks required to manage compliance and resilience:

• Understand the complexity of IT systems in real time
• Proactively prevent, prioritize, and efficiently manage performance and security incidents
• Automate manual and routine tasks to increase your productivity

Understand the complexity of IT systems in real time

Dynatrace helps you comprehensively map the entire IT environment in real time. It gives you visibility into which components are monitored and which are not and helps automate time-consuming compliance configuration checks.

Discovery & Coverage helps prevent unexpected outages by detecting and remediating monitoring coverage gaps across your entire enterprise.

Smartscape topology visualizes the relationships between applications, services, processes, hosts, and data centers, highlighting problems and vulnerabilities.

Security Posture Management helps detect, visualize, analyze, and remediate security posture and compliance findings, including misconfigurations and regulatory compliance assessments.

Compliance Assistant provides a dedicated view tailored for the European Union Digital Operational Resilience Act (DORA).

Proactively prevent and prioritize performance and security incidents

Dynatrace helps you focus on preventing incidents before they occur, managing risks proactively, and prioritizing incidents for remediation when they occur.

Problems utilizes Davis® AI to automatically analyze your system and detect abnormal behavior, such as performance or stability issues. It also investigates an incident’s impact and root cause and reduces the mean time to repair.

Vulnerabilities is our Dynatrace Runtime Vulnerability Analytics platform experience for detecting, visualizing, analyzing, monitoring, and remediating vulnerabilities across your application stack.

Attacks helps you get a real-time overview of all the attacks in your environment. Leveraging code-level insights and transaction analysis, Dynatrace Runtime Application Protection automatically detects attacks on applications in your environment.

Site Reliability Guardian provides an automated change impact analysis to validate service availability, performance, and capacity objectives across various systems. This enables DevOps platform engineers to make the right release decisions for new versions and empowers SREs to apply Service-Level Objectives (SLOs) for their critical services.

Automate manual tasks to increase productivity

Automation in Dynatrace allows you to automate tasks in your IT landscape, remediate problems, and visualize processes to increase productivity and focus on strategic initiatives.

Workflows assembles a series of actions to build processes in graphical representations. Workflows can be triggered manually, on a schedule, or by events in Dynatrace, such as anomalies detected by Davis^® AI.

What’s next

Read Dynatrace for executives: Security compliance, a blog post from our CTO, to learn more about staying ahead of the curve and helping your business be more resilient and compliant in today’s dynamic regulatory landscape. Contact us for a personalized demo to learn more about how Dynatrace can transform your approach to compliance and resilience.

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We’re excited to announce that Dynatrace has successfully achieved CSA Star 2 certification with a Gold Maturity Score. This significant milestone underscores our ongoing commitment to maintaining the highest standards of security and compliance in the cloud and making it easier for our customers to use Dynatrace SaaS.

What is CSA Star 2?

The Cloud Security Alliance (CSA) Security, Trust & Assurance Registry (STAR) is a comprehensive framework for cloud security assurance. The Level 2 certification involves a rigorous third-party assessment based on the CSA’s Cloud Controls Matrix (CCM). This certification is specifically designed for Cloud Service Providers (CSPs) and builds upon the more generic approaches of ISO 27001 and SOC 2 Type II.

CSA Star 2 strengthens Dynatrace cloud security posture

CSA Star 2 certification provides a trusted benchmark for cloud security and thus strengthens the overall Dynatrace security posture. It signifies that a cloud provider has undergone a thorough evaluation by an independent auditor, confirming that their security measures meet or exceed industry standards.

Benefits to Dynatrace customers

The Dynatrace® platform for observability and security with Davis® hypermodal AI provides answers and intelligent automation from data at an enormous scale. This enables innovators to modernize and automate cloud operations, deliver software faster and more securely, and ensure flawless digital experiences. That’s why the world’s largest organizations trust Dynatrace to accelerate digital transformation.

Achieving CSA Star 2 certification is not just a badge of honor for Dynatrace; it’s a testament to our dedication to safeguarding your data. This certification means:

• Enhanced trust: Customers can be assured that Dynatrace adheres to the highest security standards, as validated by CSA Star 2 certification through a third-party audit.
• Risk reduction: The certification process ensures that we have strong controls in place to mitigate security risks significantly, reducing the likelihood of breaches.
• Regulatory compliance: Our certification helps customers meet their own regulatory requirements, simplifying their compliance processes because our certification aligns with international standards and ensures data is handled in compliance with relevant laws and regulations.
• Streamlined audits: Customers can leverage our certification during their own audits, making the process more efficient and providing evidence of our commitment to security.

Our commitment

As shown by our broad range of certifications and accreditations, security is a core value at Dynatrace. Adding CSA Star 2 certification highlights our dedication to excellence. We’re focused on ongoing improvements to maintain the highest security standards and deliver exceptional service, providing a safe and governed environment for our customers.

What’s next

To learn more about Dynatrace data security and privacy, visit our Trust Center.

If you’re an existing Dynatrace Managed customer looking to upgrade to Dynatrace SaaS, see How to start your journey to Dynatrace SaaS.

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What is SOC 1 Type II?

SOC 1 (Service Organization Control 1) is a widely recognized auditing standard developed by the American Institute of Certified Public Accountants (AICPA). It focuses on controls related to financial reporting. The “Type II” designation means that an independent auditor evaluated our controls over a period of time (typically six months) and confirmed the controls’ effectiveness.

Strengthening the Dynatrace security posture

Having SOC 1 Type II certification demonstrates Dynatrace’s robust security practices. Our internal controls have been rigorously assessed, ensuring we meet or exceed industry standards. This certification provides peace of mind to our customers, partners, and stakeholders, who can be confident that their data is safe.

Benefits to Dynatrace customers

Our customers directly benefit from our SOC 1 Type II certification:

1. Increased trust: With this certification, you can trust that Dynatrace adheres to stringent security protocols. We prioritize the confidentiality, integrity, and availability of all customer data.
2. Risk mitigation: By adhering to SOC 1 Type II standards, we minimize the risk of financial misstatements or security breaches. You can confidently rely on Dynatrace for critical operations.
3. Streamlined audits: You can leverage Dynatrace certification during your own internal audits; it simplifies the audit process and provides evidence of our commitment to security.

Our commitment

At Dynatrace, security is at the core of everything we do. Achieving SOC 1 Type II certification reinforces our dedication to excellence. We remain focused on continuous improvement, maintaining the highest security standards while ensuring you receive exceptional service.

What’s next

• To learn more about Dynatrace data security and privacy, visit our Trust Center.
• If you’re an existing Dynatrace Managed customer looking to upgrade to Dynatrace SaaS, see How to start your journey to Dynatrace SaaS.

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“Data Privacy Framework Program (The EU-U.S. DPF, UK Extension to the EU-U.S. DPF, and Swiss-U.S. DPF) was respectively developed by the U.S. Department of Commerce and the European Commission, United Kingdom (UK) Government, and Swiss Federal Administration to provide U.S. organizations with reliable mechanisms for personal data transfers to the United States from the European Economic Area (EEA), UK, and Switzerland while ensuring data protection that is consistent with EU, UK, and Swiss law.”

(Source: https://www.dataprivacyframework.gov/)

Dynatrace is committed to managing all personal data received from the European Economic Area (EEA), U.K., and Switzerland (EU Personal Data) in accordance with its data protection requirements and is now self-certified under the Data Privacy Framework (DPF). This demonstrates Dynatrace’s ongoing commitment to managing all EU Personal Data in compliance with the requirements of the DPF.

Benefits of Data Privacy Framework for Dynatrace customers.

The data Privacy Framework demonstrates our commitment to complying with EU requirements. By participating in the DPF Program and obtaining certifications such as ISO 27001 or TISAX, Dynatrace makes reviewing and validating how Dynatrace meets your security, privacy, and compliance requirements more efficient.

As a Dynatrace customer, you trust Dynatrace with ingesting and processing terabytes of data. You can be assured that cross-border transfers of your personal data fall within the scope of the European Commission adequacy decision under the GDPR. Dynatrace has invested in building its security compliance enhancement to ensure that all your data is protected end-to-end and that you have control and can see how your data is being used. All this enables you to keep expanding the use of Dynatrace to cover use cases that you weren’t able to cover earlier.

What’s next?

• Learn more about Dynatrace participation in the Data Privacy Framework Program.
• To learn more about Dynatrace data security and privacy, visit our Trust Center.
• Contact us for more information.

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