Struggling to switch from Prometheus to Elasticsearch without rewriting your app? This hands-on guide shows how OpenTelemetry decouples your observability backend with zero app changes. Includes working Docker-based examples and step-by-step guidance.

This blog post explores distributed tracing, a technique for gaining deep insights into microservices architectures. It explains why traditional monitoring struggles with complex systems and how distributed tracing provides end-to-end visibility. The benefits include simplified debugging, performance optimization, and faster incident resolution.

The blog details how distributed tracing works with concepts like traces, spans, and context propagation. It also highlights observability tools like Jaeger, Zipkin, Datadog, and Dynatrace. Finally, it provides best practices for successful implementation, including end-to-end instrumentation, focus on SRE golden signals, standardization, and documentation.

In essence, the blog offers a comprehensive guide to leveraging distributed tracing for enhanced observability in microservices architectures.

Learn how to use go-redis client to get started with Apache Kvrocks, a distributed key-value NoSQL database.

OpenTeleletry Collector is an open source data collection pipeline that allows you to monitor CPU, RAM, disk, network metrics, and many more.

Collector itself does not include built-in storage or analysis capabilities, but you can export the data to Uptrace and ClickHouse, using them as a replacement for Grafana and Prometheus.

When compared to Prometheus, ClickHouse can offer small on-disk data size and better query performance when analyzing millions of timeseries.