Redis Archives - DEVOPS DONE RIGHT.

How to Monitor Open Telemetry Collector Performance: A Complete, Production -Grade Guide

In modern distributed systems, observability is not a luxury—it’s a necessity. At the center of this landscape stands the Open Telemetry Collector, acting as the critical data pipeline responsible for receiving, processing, and exporting telemetry signals (traces, metrics, logs).

However, monitoring the monitor itself presents unique challenges. When your OpenTelemetry Collector becomes a bottleneck or fails silently, your entire observability stack suffers. This comprehensive guide will walk you through production-tested strategies for monitoring your OpenTelemetry Collector’s performance, ensuring your observability infrastructure remains robust and reliable.

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Redis Observability with Open Telemetry

Redis is a cornerstone of many modern applications, valued for its high speed and flexibility. However, Redis systems are not “set-and-forget.” Maintaining operational excellence requires careful monitoring of critical metrics to detect early signs of performance degradation, resource exhaustion, or failures.

In this blog, we learn how to monitor Redis directly using Open Telemetry Collector’s Redis receiver, without relying on a separate Redis Exporter.

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Continuation Of Redis Throughput and Management

As promised in our previous blog on Redis Performance tunning and Best practices, we have explored more best practices and optimizations in Redis as a cache and database management system. This blog will share some new findings and optimizations we learned in our previous blog’s delta period.

We know that Redis is a high-speed and flexible data storage that can fulfill different cache and database requirements. But if a system is not configured and tested correctly, even a fast and reliable one can quickly become limited. Here we will talk about the different needs of Redis as a system and how we can optimize it further to fully use it.

So while consulting and collaborating with different Redis architects from Redis Labs, I learned different ways of designing a performance-grade, highly available, and secure Redis architecture. Based on my learning, I would like to categorize it into these dimensions:-

Right-sizing and deployment of Redis setup.
Proxy and connection pooling.
Use the correct data type for storing keys.
Sharding and replication strategy.

All Redis Setup Under 7 Minutes!

Redis is a popular open-source in-memory database that supports multiple data structures like strings, hashes, lists, and sets. But similar to other tools, we can scale standalone Redis to a particular extent, but not beyond that. That’s why we have a cluster mode setup in which we can scale Redis nodes horizontally and then distribute data among those nodes.

Generally, we categorize the Redis setup into three different types:

Standalone
Leader-Follower (Replication)
Leader-Leader(Sharding)

Standalone Setup

In a Standalone setup, the complexity is minimal, but we cannot scale the solution if the data increases. Also, the fail-over and high availability will not be supported inside it.

Redis Setup on Kubernetes

Redis is a popular and opensource in-memory database that supports multiple data structures like strings, hashes, lists, and sets. But similar to other tools, we can scale standalone redis to a particular extent and not beyond that. That’s why we have a cluster mode setup in which we can scale Redis nodes horizontally and then distribute data among those nodes.

Since Kubernetes is becoming buzz technology and people are using it to manage their applications, databases, and middlewares at a single place. So in this blog, we will see how we can deploy the Redis cluster in production mode in the Kubernetes cluster and test failover.

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