Are you ready to dive into the world of observability with Hypertrace? In this guide, we’ll walk you through the steps to get Hypertrace up and running with ease. Whether you’re assessing your distributed systems’ performance or troubleshooting issues, Hypertrace has got you covered.

What is Hypertrace?

Hypertrace is a cloud-native distributed tracing observability platform that provides you with clear visibility into both development and production environments. It translates complex trace data into actionable insights, enabling various teams within your organization to identify issues, diagnose failures, and monitor performance metrics effortlessly.

Features of Hypertrace

• Perform Root Cause Analysis (RCA) on system failures
• Monitor rollouts and compare key metrics
• Identify performance bottlenecks and slow operations
• Observe dependencies across microservices

Quick Start with Docker-Compose

To see Hypertrace in action, you can initiate it quickly using Docker Compose. Here’s how:

Prerequisites

• Docker Engine (version 17.12.0 or higher)
• Docker Compose (version 1.21.0 or higher)
• It’s recommended to increase Docker Desktop memory settings from 2 GB to 4 GB and set the CPU allocation to at least 4 CPUs for optimal performance.

Run with Docker-Compose

To get started, execute the following commands:

bash
git clone https://github.com/hypertrace/hypertrace.git
cd hypertrace
docker/docker-compose pull
docker-compose up --force-recreate

The above commands will initiate all services necessary for Hypertrace. Once you see the Hypertrace-UI start, visit http://localhost:2020 to access the user interface.

Using Existing Instrumentation

If your application is set up to send traces to Zipkin or Jaeger, it will integrate seamlessly with Hypertrace. Otherwise, you can try Hypertrace with the sample application using:

bash
docker-compose -f docker-compose-zipkin-example.yml up

Access the sample app at http://localhost:8081 and make a few requests to generate sample trace data!

Deploy in Production with Kubernetes

For those looking to deploy Hypertrace in a production environment, we offer Helm charts for a simplified installation on Kubernetes. Check the deployments section of the documentation for detailed steps across various operating systems and cloud providers.

Troubleshooting and Community Support

If you encounter any issues while using Hypertrace, here are some troubleshooting ideas:

• Ensure Docker Engine and Docker Compose versions are correct.
• Check memory and CPU allocation settings in Docker Desktop.
• Visit the issues page for reported problems and solutions.
• For further insights or collaboration on AI development projects, stay connected with fxis.ai.

Conclusion

Hypertrace is designed for observability, helping you gain deeper insights into your applications and systems. Following the above steps, you can quickly set up Hypertrace to monitor, analyze, and troubleshoot your distributed systems.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.