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
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Thundra Web Console
Introduction
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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
Configuring Node.js SDK
Configuring Metrics for Node.js
Configuring Logs for Node.js
Configuring Traces for Node.js SDK
Tagging in Node.js SDK
Sampling in Node.js SDK
Chaos Injection in Node.js SDK
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
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 Node.js

Thundra Node.js Metrics

Metric support provides essential information regarding the performance of your Node.js Lambda functions, which translate to carefully calculated statistics. You can examine:
  • Invocation Counts
  • Invocation Durations
  • Memory Usages
  • Process Memory Usages
  • CPU Percentages
  • Disk IO
  • Thread Count

Configuring Metrics

By simply importing thundra from @thundra/core, all the metrics mentioned above are ready to be collected; however, metrics are disabled by default. You need to enable them programmatically or through environment variables.

Enabling Sending Metrics

Metric monitoring can be enabled by setting the relevant configuration parameters. These parameters include the thundra_agent_lambda_metric_disable environment variable and the disable_metric object initialization parameter.

Enabling metric programmatically on agent initialization

Programmatic Metric Configuration
const thundra = require("@thundra/core")({
metricConfig: {
enabled: true,
},
});

Enabling metric using environment variables

Metric Configuration via Environment Variables
thundra_apiKey: ${self:custom.thundraApiKey}
thundra_agent_lambda_metric_disable: false
​
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Thundra Node.js Metrics
Configuring Metrics
Enabling Sending Metrics