Dynamic Code Analysis

Resolve performance issues in pre-production, prevent incidents and engineering disruptions

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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.

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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.

AI CODE

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.

Get started with our MCP Server ➔

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Nasim Salmany

Software Engineer

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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.

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Bruno Souza

Principal Consultant

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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.

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Markus Westergren

Staff Consultant

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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 a important part of our work-flow.

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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.

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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.

Engineering study

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.

We Answered

Frequently Asked Questions

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.

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.

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.

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.

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.

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

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.