Thundra APM
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Thundra APM
Welcome to Thundra APM
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Getting Started
Getting Started with Thundra APM
Quick Start Guide
FAQ
Performance Benchmarks
Thundra Web Console
Introduction
Functions List Page
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Node.js
Integration Options for Node.js SDK
Integration Options for Node.js SDK in Containers and VMs
Configuration Options for Node.js
Enrich Tracing in Node.js
AWS Lambda Debugging for Serverless Node.js
TTD (Time Travel Debugging) for NodeJS
Node.js Example Projects
FAQ for Node.js SDK
Python
Integration Options for Python SDK
Configuration Options for Python
Enrich Tracing in Python
AWS Lambda Debugging for Serverless Python
Python Example Projects
FAQ for Python SDK
Java
Integration Options for Java SDK
Integration Options for Java SDK in Containers and VMs
Configuration Options for Java
Configuring Java SDK
Configuring Traces for Java SDK
Configuring Logs for Java SDK
Configuring Metrics for Java SDK
Chaos Injection in Java SDK
Sampling in Java SDK
Tagging in Java SDK
Enrich Tracing in Java
AWS Lambda Debugging for Serverless Java
Java Example Projects
FAQ for Java SDK
Go
Integration Options for Go SDK
Configuration Options for Go
Enrich Tracing in Go
Golang Example Projects
FAQ for Go SDK
.Net
Integration Options for .NET SDK
Integration Options for .NET SDK in Containers and VMs
Upgrading from v1.x to v2.x
Configuration Options for .NET SDK
Enrich Tracing in .NET
.NET Example Projects
FAQ for .NET SDK
Web Frameworks
Spring
Express.js
Hapi
Koa.js
Django
Flask
.NET Core 2.1
.NET Core 3.1
Fastapi
Tornado
Debugging
Time-Travel Debugging
AWS Lambda Debugger
IDE Integrations
VSCode Plugin
IntelliJ IDEA Plugin
Others
Observability
Root Cause Analysis of Outliers
Architectural View to Check The Issues at a Glance
Tracking Serverless Transactions End-to-End
Staying Aware of Issues with Alerts
How to Respond Alerts in Thundra
Reducing Data Size with Sampling
Chaos Engineering with Thundra
Three Pillars of Observability
Seamless Monitoring
Digging Observability Data with Thundra Queries
Performance
Zero Overhead with Lambda Extensions
Zero Overhead with Asynchronous Monitoring
Dealing with Cold Starts
Deployment Integrations
AWS SAM
Serverless Framework
Step by Step Migration Guide from Epsagon to Thundra
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Configuring Metrics for Java SDK

Provided Metrics

Metric support provides all essential information regarding the performance of your Java Lambda functions, which translate to carefully calculated statistics. You can examine:
  • Loaded class counts
  • Memory usages
  • Memory usages by pool
  • CPU percentages
  • GC CPU percentages
  • GC counts
  • GC durations
  • Thread count

Configuring Metrics

If you use Thundra’s Java layer (or custom runtime), the metric plugin is disabled by default; however, you can enable it by setting the thundra_agent_lambda_metric_disable environment variable to false.
Metrics are provided and reported periodically. With the following environment variables, the reporting period can be configured. If just one of the following periods reaches its configured limit, the metric is published.
  • thundra_agent_metric_sample_sampler_timeAware_timeFreq: Configures the time frequency in milliseconds to trigger metric reporting. Metrics are provided only once during the specified time period. The default value is 300,000 milliseconds (5 minutes).
    ​
  • thundra_agent_metric_sample_sampler_countAware_countFreq: Configures the invocation count to trigger metric reporting. Metrics are provided only once for each of the specified invocation counts. The default value is 100.
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Provided Metrics
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