Agentic AI SRE

Autonomous identification, root cause analysis and remediation of code and infrastructure issues

Cut resolution time by 85%

Digma’s AI SRE pinpoints the root cause, whether in code or infrastructure, and offers precise remediation via pull requests or config updates, eliminating costly investigation cycles and keeping engineers focused on building..

Get accurate, reliable resolutions

Digma’s AI SRE connects to observability stack and key data sources like PostgreSQL, GitHub, and Kubernetes.

This enables precise root cause analysis and trusted fixes, continuously.

Prevent issues before they break production

Digma’s AI SRE identifies and prioritizes issues based on their real impact, before they escalate. It’s powered by our Dynamic Code Analysis (DCA) engine, built to understand system behavior in real time.

Identify code-level issues with Digma’s Dynamic Code Analysis

Digma’s Dynamic Code Analysis (DCA) engine identifies issues at the code level in pre-production environments, allowing teams to prevent them earlier. The DCA engine processes raw observability data to reveal critical, actionable insights, reducing the effort needed to translate data into practical solutions.

Maximize code review effectiveness

Digma MCP server enhances code reviews by identifying runtime issues in staging and production environments. The agent highlights critical performance problems, uncovering bottlenecks, scaling issues, and slow database queries. The MCP server enables the agent to suggest safe, smart, and production-aware fixes, integrating them directly into the pull request.

Digma’s MCP Server makes AI Coding smarter

Using a built in MCP Server Digma leverages the data in your APM dashboards to assist the AI agent during code reviews, code and test generation, fix suggestions etc.

Nasim Salmany

Software Engineer
Watch Review

As a developer, I was seeking to learn about new solutions to obtain feedback in the early stages of development, such as how to improve performance or facilitate refactoring.

This is where Digma came into play, offering valuable insights into component usage and traces, which proved very helpful.

As I continue to explore Digma, I’m pleased to recommend its use to others, finding it to be beneficial in the development process.

Bruno Souza

Principal Consultant
Watch Review

I love the business model of Digma. Free forever to developers, and able to run on my computer without sharing information externally. I can be more productive and build my continuous feedback loop, no matter if the company has decided to use Digma or not. This allows any developer to improve their skills continuously. This is especially great for consultants like myself.

Markus Westergren

Staff Consultant
Watch Review

Digma analyzes generated OpenTelemetry data and identifies possible issues. The plugin makes locating them in the code a breeze, because it will allow you to navigate between identified problems and the actual source code. It takes the guess-work out of finding and fixing performance issues. This plugin is now an important part of our workflow.

Prevent Breaking Changes & Identify Dependencies

Digma MCP server highlights how your code changes impact other services and components during runtime to prevent breaking changes, allowing developers to assess modifications and anticipate issues before they occur.

Improve App Performance with Digma

Digma MCP server improves app performance by identifying the top runtime issues slowing down the application. The Digma’s Dynamic Code Analysis engine analyzes the runtime data, identifies inefficiencies and suggests fixes for the most impactful problems. In the video, it finds database and API endpoint bottlenecks and automatically generates fixes like DB caching and improved scalability.

The state of the shift left

Insights from 280 engineers and managers on their shift-left progress, ability to catch issues early, troubleshoot quickly and minimize wasted engineering time.

Frequently Asked Questions

How is Digma different from traditional monitoring tools like APMs?

Digma is not an alternative to APMs but a complementary solution. Unlike traditional APMs that focus on detecting issues in production, Digma identifies problems earlier in the development cycle using Dynamic Code Analysis. This allows engineering teams to prevent disruptions before they impact production and the organization’s SLOs.

Can Digma help with breaking changes across the team’s codebase?

Yes! Digma analyzes every code change and highlights affected areas before you even merge a Pull Request. That means you’ll know what might break before it actually does, saving you and your team hours of debugging and firefighting.

Does Digma require any code changes? Or setting up a complicated observability system?

Nope! Digma works without requiring any code changes. It’s also OpenTelemetry (OTEL) compliant, so if you’re already using observability tools, Digma just plugs right in and starts helping you out immediately.

How does Digma help reduce infrastructure costs?

Unlike cloud cost optimization tools that focus on infrastructure expenses, Digma identifies inefficient code patterns that increase resource consumption. By pinpointing areas for optimization, it helps engineering teams write cost-efficient code that scales better while reducing infrastructure expenses.

Does Digma use AI, and what happens to our data?

Digma doesn’t use public AI models that could share your data outside your organization. Everything stays local, meaning you stay in full control of your observability data.

What kind of performance issues can Digma detect?

Digma detects a variety of performance-related issues, including:

  1. Code changes that introduce unexpected performance regressions
  2. Slow execution paths in the code
  3. Scalability bottlenecks that may cause failures under load
  4. Inefficient database queries or API calls

Is Digma a replacement for profilers or static analysis tools?

Not really—profilers and static analysis tools have their place, but they usually come into play after something goes wrong. Digma goes further by analyzing real runtime data. It detects performance bottlenecks, scaling issues, and runtime errors that static analysis tools simply cannot catch.