Both OpenTelemetry and Prometheus are open-source projects under the Cloud Native Computing Foundation. OpenTelemetry is a more comprehensive observability framework with support for metrics, traces, and logs. In contrast, Prometheus is focused specifically on time-series metrics. OpenTelemetry is more versatile, and if you’re confused between choosing between the two, go for OpenTelemetry. We will delve deeper into the reason for choosing OpenTelemetry over Prometheus in this article.

Are you looking for a DataDog alternative? Then you have come to the right place. In this article, we will go through top 9 DataDog alternatives. One of the biggest challenge users face with DataDog is its pricing policies. Its complex SKU-based pricing policy leads to unpredicatble bills. DataDog is a cloud monitoring software that provides an array of tools for monitoring different aspects of your application and infrastructure.

DataDog is a paid SaaS tool that provides a range of products for monitoring applications and tech infrastructure. While Grafana is an open-source web visualization tool that can be used with a variety of data sources to create dashboards. If you're looking for a one-stop observability solution and price is not a concern for you, choose Datadog. In case you're looking to visualize data from a lot of different data sources especially time-series data, then choose Grafana.

OpenTelemetry can auto-instrument your Java Spring Boot application to capture telemetry data from a number of popular libraries and frameworks that your application might be using. It can be used to collect logs, metrics, and traces from your Spring Boot application. In this tutorial, we will integrate OpenTelemetry with a Spring Boot application for traces and logs. OpenTelemetry is a vendor-agnostic instrumentation library that is used to generate telemetry data like logs, metrics, and traces.

Log analysis is a very powerful feature for an application when it comes to debugging and finding out which flow is working properly in the application and which is not. In a world of containerization and cloud computing, it is essential to understand logs generated by a Docker environment to maintain healthy performing applications. In this article, we will discuss log analysis in Docker and how logging in Docker containers is different than in other applications.

In the ever-evolving world of software development, one constant remains - the pursuit of better performance. As applications grow in complexity and demand, the need for tools to uncover performance bottlenecks becomes paramount. Flamegraphs, a brainchild of Brendan Gregg, has emerged as an important visualization of insight, showing those dark corners of your codebase that need optimization.

OpenTelemetry Collector is a stand-alone service provided by OpenTelemetry. It can be used as a telemetry-processing system with a lot of flexible configurations to collect and manage telemetry data. Let's do a deep dive on OpenTelemetry Collectors to understand how it works. The first step in setting up observability with OpenTelemetry is instrumentation. The application code is instrumented with OpenTelemetry client libraries that help generate telemetry data like logs, metrics, and traces.

Elasticsearch, or the ELK stack, is a popular log analytics solution. The Loki project was started at Grafana Labs in 2018. Grafana leads the development of Loki, while Elastic is the company behind Elasticsearch. In this article, we will do a detailed comparison between these two tools for log analytics. Log data helps application owners debug their applications while also playing a critical role in cyber security.

Splunk is a powerful unified security and observability tool that analyzes data and logs. Splunk allows you to monitor and visualize data in real-time. It analyzes machine-generated data and logs through a web interface. It was recently acquired by Cisco in a $28 billion deal. While Splunk is a powerful platform, it might not suit your needs. In this post, we discuss 11 top Splunk alternatives that you can consider.

The kubectl logs tail command is a tool that allows users to stream the logs of a pod in real-time while using Kubernetes. This command is particularly useful for debugging and monitoring applications, as it enables users to view log output as it is generated and quickly identify any issues or problems with their application. In this article, we will see how to use the kubectl logs tail command to stream logs, the benefits of using the command, and an advanced tool for streaming logs.