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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  • Description
  1. Digma Features
  2. Issues

High number of queries

This insight identifies endpoints that trigger an abnormal amount of queries. This can be caused by abstraction issues or not using bulk queries when applicable

PreviousQuery Optimization SuggestedNextSlow Endpoint

Last updated 1 year ago

Description

The high number of queries insight indicates that the current endpoint/consumer is triggering an abnormal number of DB queries. This can be typically resolved with caching or using more optimal queries.