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.

Nextjs is a production-ready React framework for building single-page web applications. It enables you to build fast and user-friendly static websites, as well as web applications using Reactjs. Using OpenTelemetry Nextjs libraries, you can set up end-to-end tracing for your Nextjs applications. Nextjs has its own monitoring feature, but it is only limited to measuring the metrics like core web vitals and real-time analytics of the application.

OpenTelemetry can be used to trace Go applications that use Kafka to find performance issues and bugs. OpenTelemetry is an open-source project under the Cloud Native Computing Foundation (CNCF) that aims to standardize the generation and collection of telemetry data. Telemetry data includes logs, metrics, and traces. Apache Kafka introduced the ability to add headers to Kafka messages from version 0.11 onwards.

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. An APM that can ingest telemetry data collected by OpenTelemetry can help you set up a robust observability stack.

Monitoring Redis for performance issues is critical. Redis is famous for its low-latency response while serving a large number of queries. There are certain key metrics that you can monitor to keep track of your Redis instance performance. In this guide, we will go through key Redis metrics that should be monitored and ways to collect these metrics with in-built Redis tools.

ELK is the acronym Elasticsearch, Logstash, and Kibana, and combined, it is one of the most popular log analytics tools. Elastic changed the license of Elasticsearch and Kibana from the fully open Apache 2 license to a proprietary dual license. The ELK stack is also hard to manage at scale. SigNoz can be used as a lightweight alternative to the ELK stack.

We are delighted to share that eG Innovations has become one of a very small number of partners to have achieved AWS’s “Digital Workplace Competency” award following a lengthy and rigorous technical audit process. This designation differentiates eG Innovations from other AWS EUC monitoring vendors as having a solution that meets AWS’s own standards for enterprise software.

Database monitoring is a critical component in your application performance monitoring. Apart from application code issues, database issues are one of the most common reasons for a bad user experience. MySQL is one of the most popular open-source DBMS that businesses have widely adopted. MySQL monitoring tools can help you identify potential issues with your database, keep a continuous check on your database instances, improve performance and detect and alert you about real-time issues.

ELK is the acronym Elasticsearch, Logstash, and Kibana, and combined together, it is one of the most popular log analytics tools. Elastic changed the license of Elasticsearch and Kibana from the fully open Apache 2 license to a proprietary dual license. The ELK stack is also hard to manage at scale. In this article, we will discuss 14 ELK alternatives that you can consider using.

Administrators and IT management are increasingly leveraging simple quantifiable KPI indicators such as “Performance Ratings” to gain rapid overviews and track key outcomes. Modern IT architectures are designed and built to scale and be resilient. Systems are now usually built to handle failover and auto-scale up and down to handle varying demand and workloads with very different properties and needs.