Enhancing APISIX Ingress Observability: Master Metrics with Mimir, Traces with Tempo, and Logs with Loki

In today’s complex microservices architecture, monitoring and observing your API gateway and ingress controller is more critical than ever. APISIX, a high-performance, cloud-native API gateway, offers robust features for API management and traffic orchestration. However, to make the most out of its capabilities, effective observability is a must. In this blog post, we’ll dive deep into how you can achieve a comprehensive observability stack for APISIX Ingress Controller by leveraging Grafana Mimir for metrics, Grafana Tempo for traces, and Loki for logs.

Why Observability Matters for APISIX Ingress

Observability allows DevOps teams to understand the internal state of the system based on its external outputs. For an API gateway like APISIX, which serves as the entry point for all incoming traffic, observability is crucial for:

  • Monitoring performance and health
  • Troubleshooting issues quickly
  • Optimizing resource utilization
  • Ensuring the security and reliability of your APIs

To make an observability stack work for APISIX Ingress, integrating a full suite of tools for metrics, logs, and traces can make a significant difference.

Metrics with Grafana Mimir

Grafana Mimir is a highly scalable and cost-efficient time series database for Prometheus metrics. Since APISIX generates a wealth of metrics such as request rates, latency, error rates, and upstream server health status, Mimir helps us store and query this large volume of metrics efficiently.

How to Set Up Mimir for APISIX Metrics

  1. Install Mimir: First, set up a Grafana Mimir instance. You can refer to the [official Mimir documentation](https://grafana.com/docs/mimir/latest/) for a detailed guide on installation and configuration.
  2. Configure Prometheus to Write to Mimir: APISIX metrics can be scraped by Prometheus. To make Prometheus write data to Mimir, you need to configure Prometheus' "remote write" feature: 
    
remote_write:
  - url: http://mimir.address:9009/api/v1/push
    Remember to replace `http://mimir.address:9009` with your actual Mimir endpoint.
  3. Verify Data in Grafana: Connect Grafana to your Mimir instance as a data source. Once connected, you can import pre-built APISIX dashboards or create custom dashboards to visualize the collected APISIX metrics.

Traces with Grafana Tempo

Distributed tracing is an invaluable tool for analyzing application performance and diagnosing issues in microservices architectures. Grafana Tempo is an open-source, high-scale distributed tracing backend that integrates seamlessly with common open-source tracing protocols such as Jaeger, Zipkin, and OpenTelemetry.

Integrating Tempo with APISIX

  1. Install and Configure Tempo: Follow the [Tempo installation guide](https://grafana.com/docs/tempo/latest/) to set up a Tempo instance.
  2. Configure APISIX to Send Traces to Tempo: APISIX supports sending traces to various backends via plugins such as the `zipkin` plugin. To send traces to Tempo which supports the Jaeger, Zipkin, and OpenTelemetry protocols, you need to enable and configure the `zipkin` plugin in your APISIX configuration: 
    
plugins:
  - zipkin
plugin_attr:
  zipkin:
    endpoint: http://tempo.address:9411/api/v2/spans
    sample_ratio: 1
    Replace `http://tempo.address:9411` with your actual Tempo endpoint. The `sample_ratio` can be adjusted based on your tracing needs (1 means 100% of requests will be traced).
  3. Visualize Traces in Grafana: After connecting Grafana to Tempo as a data source, you can use Grafana’s built-in tracing capabilities to visualize and analyze the traces generated by APISIX.

Logs with Grafana Loki

Logging is another crucial part of the observability trifecta. Grafana Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus.

Concentrating APISIX Logs with Loki

  1. Install Loki: Set up a Loki instance based on the [Loki installation guide](https://grafana.com/docs/loki/latest/).
  2. Forward APISIX Logs to Loki: APISIX can be configured to send logs to various backends such as Kafka, Elasticsearch, or even directly to Loki via the `http-logger` plugin. To send logs to Loki: 
    
plugins:
  - http-logger
plugin_attr:
  http-logger:
    uri: http://loki.address:3100/loki/api/v1/push
    Replace `http://loki.address:3100` with your actual Loki endpoint. You need to make sure that the `http-logger` plugin is enabled in your APISIX configuration.
  3. Analyze Logs in Grafana: Once Grafana is connected to your Loki data source, you can create log queries and visualize logs directly within Grafana for a unified observability experience.

Conclusion

Implementing a robust observability stack for APISIX Ingress Controller using Grafana Mimir for metrics, Tempo for traces, and Loki for logs will provide you with a comprehensive view of your API gateway’s performance and health. By leveraging these powerful tools, you can gain deeper insights, respond to issues proactively, and ensure that your API infrastructure is running smoothly and efficiently. Thus, team up APISIX with an observability stack that provides full visibility into metrics, traces, and logs to achieve a truly cloud-native, high-performing API gateway.

Remember to make sure all components are well-configured and properly integrated for a seamless and insightful observability experience. Happy monitoring!