Elevate

At its core, the OpenTelemetry Collector is a pipeline for processing and exporting telemetry data. It sits between your application and your backend observability tools (like Prometheus, , DataDog, Splunk, Jaeger, or Elasticsearch), collecting data from various sources before enriching or transforming it and finally sending it off to the destination of your choice.

In today's data-driven world, managing and processing large volumes of data efficiently is crucial. Logstash is an open-source data processing pipeline from Elastic that ingests data from multiple sources simultaneously, transforms it,

In the era of cloud-native applications and microservices, observability has become a cornerstone of reliable software systems. Prometheus, an open-source monitoring and alerting toolkit, is often the go-to choice for organizations looking to build their own observability platforms. While Prometheus offers a rich feature set and the allure of customization, building an in-house observability

When it comes to telemetry and observability, one of the most important questions is: metrics or logs? These two approaches offer very different ways of understanding the behavior of your systems. Knowing when to use each one is essential to maintaining a high-performing infrastructure and troubleshooting issues effectively. In this post, we’ll explore the key differences between metrics and logs, highlight the “gotchas” to watch out for, and provide guidance on when to use one over the other.

Grafana and Prometheus are two of the most important tools for monitoring and observability. When comparing these two tools, it’s easy to fall into the trap of treating them as direct competitors and evaluating which would be better for your needs.

As an experienced developer, you know that the choice of log management tools can significantly impact the performance and efficiency of your systems. Logstash and Fluentd are two widely used tools in this space, each with its own strengths and limitations.