Distributed System Debugging with OpenTelemetry and Teletrace: Real-World Examples

Long Story Short: To effectively debug applications, consider utilizing powerful tools such as Teletrace and OpenTelemetry. These tools provide comprehensive tracing and telemetry capabilities, enabling you to pinpoint and resolve issues and making your debugging process highly efficient and effective.

Introduction

In the world of distributed systems and microservices architecture, debugging and root cause analysis can be challenging. With numerous services, dependencies, and data flowing through different components, finding the cause of an issue can seem like finding a needle in a haystack. However, thanks to modern observability tools like OpenTelemetry and Teletrace, developers can now debug and troubleshoot complex systems with ease and efficiency. In this blog post, we will explore how you can debug applications using OpenTelemetry and Teletrace, along with real-world use cases from a demo.

What are OpenTelemetry and Teletrace?

OpenTelemetry is a set of APIs, libraries, agents, instrumentation, and integrations for observability in distributed systems. It provides a standardized way to collect, observe, and analyze telemetry data, including traces, metrics, and logs, from applications and services. OpenTelemetry supports multiple programming languages, frameworks, and platforms, making it a versatile choice for observability in diverse environments.

Teletrace, on the other hand, is an open-source distributed tracing system used as a backend service to receive traces from OpenTelemetry SDK. This helps monitor and troubleshoot transactions across microservices. It provides end-to-end distributed tracing, allowing developers to visualize and understand the flow of requests across services and identify performance bottlenecks or errors.

Debugging with OpenTelemetry and Teletrace

OpenTelemetry and Teletrace can be used together to gather detailed telemetry data from your applications and services, and visualize the data in a distributed tracing format to help with debugging and root cause analysis. Here are some steps you can follow to debug with OpenTelemetry and Teletrace:

1. Instrument your applications: Begin by instrumenting your applications and services using the OpenTelemetry libraries and agents for your programming language or framework of choice. This will enable your applications to generate traces, metrics, and logs that capture important information about the flow of requests, dependencies, and errors.
2. Configure and deploy Teletrace: Set up a Teletrace instance to receive and store the telemetry data (traces only) from your applications. You can deploy Teletrace as a standalone service that uses the popular data store Elasticsearch. Elasticsearch stores traces and spans behind the scenes. Teletrace can be deployed to K8S via helm chart or with docker image on your local machine.
3. Generate traces and view in Teletrace UI: Once your applications are instrumented, and Teletrace is configured, you can generate sample requests or actual requests to your applications to start capturing telemetry data. You can then view the generated traces in the Teletrace UI, which provides a visual representation of the flow of requests and their associated spans, showing the latency, errors, and dependencies between services.
4. Analyze traces and identify issues: In the Teletrace UI, you can analyze the captured traces to identify any performance bottlenecks or errors. You can drill down into individual spans to see detailed information about the duration and tags associated with each span. This allows you to pinpoint the root cause of an issue and understand the interactions between different services in your distributed system.
5. Add custom tags: OpenTelemetry allows you to add custom tags to your spans, which can provide additional context and insights for debugging. You can add tags to capture information such as request parameters, headers, or payload parameters. These custom tags can help you gain more visibility into the behavior of your applications and services and aid in root cause analysis.

Analyze traces in Teletrace

Real-world Use Cases

Let’s take a look at some real-world use cases that happened to my team to illustrate how OpenTelemetry and Teletrace can be used for effective debugging and root cause analysis.

1. Troubleshooting performance issues: In this use case, a microservices architecture was experiencing performance issues with high latency and increased error rates. By using OpenTelemetry and Teletrace, the team was able to identify the root cause of the issue. They analyzed the traces captured by OpenTelemetry and visualized them in Teletrace UI. They identified that one of the microservices was making multiple unnecessary calls to an external API, causing the performance degradation. They were able to pinpoint the issue by looking at the latency and error rates in the spans of the affected service, and then used custom tags to capture the relevant information about the external API calls.
2. Diagnosing error patterns: In another use case, the team was dealing with a production issue where errors were occurring sporadically across multiple services. They used OpenTelemetry and Teletrace to capture traces and spans from the affected services. They then analyzed the traces in Teletrace UI and identified a common pattern in the errors. By correlating the errors and spans in Teletrace, they were able to determine that the issue was caused by an intermittent failure in an external authentication service, which was affecting multiple services. This allowed them to quickly identify the root cause and take appropriate action to resolve the issue.
3. Investigating distributed transactions: In a complex distributed transaction scenario, the team used OpenTelemetry and Teletrace to trace the flow of requests across multiple services. They captured traces from all the services involved in the transaction and visualized them in Teletrace UI. By looking at the spans and dependencies between services, they were able to identify a missing step in the transaction flow, which was causing transaction failures. They used custom tags to capture additional context about the transaction, such as transaction IDs and relevant parameters, which helped them in their investigation and resolution of the issue.

Conclusion

In conclusion, using OpenTelemetry and Teletrace can greatly enhance your ability to debug and troubleshoot complex distributed systems. By capturing detailed telemetry data and visualizing it in a distributed tracing format, you can gain insights into the flow of requests, dependencies, and errors across your services. Custom tags can provide additional context for effective root cause analysis. Real-world use case examples illustrate how OpenTelemetry and Teletrace can be used to identify and resolve performance issues, diagnose error patterns, and investigate distributed transactions. So, if you want to debug your microservices architecture, consider leveraging the power of OpenTelemetry and Teletrace for observability and troubleshooting. Happy debugging!