Digma’s DCA Engine

Unlike traditional observability tools focused on alerting to problems in retrospect, Digma leverages a Dynamic Code Analysis (DCA) engine that identifies issues at the code level in pre-prod environments, allowing teams to prevent them earlier

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Dynamic Code Analysis Engine - Continuous over Manual

Continuous over Manual

The DCA engine identifies issues automatically, as the developer works, and does not rely on manual processes

Dynamic Code Analysis Engine - Issues over raw data

Insights over raw data

Raw observability data takes too much effort to translate into something practical. The DCA engine process the raw data to reveal critical actionable insights

Dynamic Code Analysis Engine - Focus on code not services

Focus on code

Traditional APMs focus on the infrastructure and APIs, whereas the DCA engine focuses on code-level issues and patterns

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Dynamic Code Analysis Engine - architecture 1
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Tour the product

The Digma Sandbox lets you explore the use of Dynamic Code Analysis during development, providing a clearer understanding of its benefits. No deployment or installation is needed.

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The Dynamic Code Analysis engine

Digma’s Dynamic Code Analysis (DCA) engine introduces an advanced approach to observability by proactively identifying potential issues before they materialize in production.

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It achieves this by analyzing observability tracing data, even when data volumes are low. Leveraging pattern matching and anomaly detection techniques, Digma’s algorithm extrapolates expected application performance metrics, enabling it to detect deviations or potential problems that have not yet impacted the application. In analyzing the tracing data, Digma pinpoints the issue to the specific responsible code and commits.

How to identify code issues with Dynamic Code Analysis

We’ve curated a list of blog posts about concepts and practices. We also published an Udemy course which you can access below.

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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.

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Frequently Asked Questions

Most observability tools focus on monitoring production environments, meaning you only find out about issues after they impact users. Digma works at the code level in pre-production, inside your IDE, identifying issues before they appear in production. This means fewer rollbacks, less rework, and a smoother development process.

Yes! Digma detects which areas of the code and components are affected by each change or pull request, ensuring no one accidentally introduces breaking changes. This reduces the risk of regressions and disruptions, helping the team move faster with confidence.

Unlike traditional performance monitoring tools that require heavy instrumentation, Digma analyzes lightweight tracing data and identifies inefficient code patterns before they hit production. This means your team gets actionable insights on slow execution paths, scalability bottlenecks, and inefficient queries—without impacting development speed.

No. Digma runs locally and does not require code modifications, manual profiling, or additional observability setup. It’s OTEL-compliant, so it fits right into your existing observability stack without adding friction.

Getting started is easy—just install the Digma plugin, and it immediately starts analyzing your code in real-time. Want to learn more? Check out our documentation, blog, or Udemy course to see how Digma can fit into your team’s workflow.

Digma proactively identifies breaking changes, performance regressions, and scalability issues while your team is still developing. Instead of reacting to production incidents, your engineers can address problems earlier—saving debugging time, reducing deployment risks, and keeping the team focused on delivering features.

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Digma is the first platform to leverage a Dynamic Code Analysis (DCA) engine, identifying code-level issues in pre-production to prevent disruptions and reduce firefighting, ensuring smoother development cycles. Any questions?

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