Digma Developer Guide
  • Welcome to the Digma Docs!
  • What is a Continuous Feedback platform?
  • Digma Quickstart
  • Installation
    • Local Install
      • Local Install Architecture
      • Installation Troubleshooting
    • Central (on-prem) Install
      • Resource Requirements
  • INSTRUMENTATION
    • Instrumenting your code for tracing
    • Java
      • Automatic Instrumentation in the IDE (IntelliJ)
      • Spring, Spring Boot, Dropwizard
        • Instrumenting your code in CI/Staging or the terminal
        • Instrumenting your application in Docker Compose
        • Instrumenting your application on Kubernetes
        • Covering more of your code with Observability
        • Using GitHub Actions (beta)
        • Using Micrometer Tracing (Spring Boot 3.x only)
        • Instrumenting code running in CLI
      • Quarkus, Micronaut, OpenLiberty
    • .NET
    • Correlating observability and source code commits
    • Sending Data to Digma using the OTEL Collector
    • Sending Data to Digma Using the Datadog agent
  • Use Cases
    • Design and write code more efficiently by understanding the system flows
    • Get early feedback on bottlenecks and code issues
    • Prioritize Technical Debt
  • Digma Core Concepts
    • Environments
    • Assets
    • Analytics vs. Issues
  • Digma Features
    • Issues
      • Suspected N+1
      • Excessive API calls (chatty API)
      • Bottleneck
      • Scaling Issue
      • Session In View Query Detected
      • Query Optimization Suggested
      • High number of queries
      • Slow Endpoint
    • Analytics
      • Top Usage
      • Request Breakdown
      • Duration
      • Code Nexus
      • Duration Breakdown
      • Endpoint Low/High Usage
    • Performance Impact
    • Test observability
    • Issue Criticality
  • Sample Projects
    • Spring Boot
  • Troubleshooting
    • Reporting Plugin Issues
    • Digma Overload Warning
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On this page
  • Learn of code-related issues, from multiple environments
  • Recheck issues after fixing the source problems
  1. Use Cases

Get early feedback on bottlenecks and code issues

One thing that Digma tries to do is make observability proactive. This means that if there are any issues you shouldn't encounter them when it's already late in the dev/release process

PreviousDesign and write code more efficiently by understanding the system flowsNextPrioritize Technical Debt

Last updated 1 year ago

Learn of code-related issues, from multiple environments

As the code gets executed, either in your local environment, in CI staging, or in production - Digma learns about how it performs, scales, and identifies any process issues or anti-patterns that should be dealt with.

As you work on your code, any newly detected issues will appear in the issues side panel as unread.

Additionally, the code itself will be highlighted to signify whether any critical issues are present:

Recheck issues after fixing the source problems

Once an issue Digma detected is fixed, you can use the recheck option on the issue card. Digma will start re-examining the problem based on new data to determine whether the issue is indeed fixed. This is not mandatory for detecting whether an issue is fixed but can expedite the detection process.