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Jaeger vs Elastic APM - key differences, features and alternatives

Jaeger is an open-source end-to-end distributed tracing tool for microservices architecture. On the other hand, Elastic APM is an application performance monitoring system that is built on top of the ELK Stack (Elasticsearch, Logstash, Kibana, Beats). In this article, let's explore their key features, differences, and alternatives. Application performance monitoring is the process of keeping your app's health in check. APM tools enable you to be proactive about meeting the demands of your customers.

Jaeger vs New Relic - Key differences, use-cases and alternatives

Jaeger and New Relic are tools used in the application monitoring and observability domain. While Jaeger is an open source tool under Cloud Native Computing Foundation, New Relic is a SaaS vendor in the observability domain. Let us explore the key differences between Jaeger and New Relic in this article. New Relic is an extensive SaaS tool and provides application performance as well as infrastructure monitoring. Jaeger provides an open-source solution for end-to-end distributed tracing.

Jaeger vs OpenTracing - Key differences, use-cases and alternatives

Jaeger and OpenTracing are both open-source projects. Jaeger was originally built by teams at Uber and then open-sourced. The OpenTracing project was also started by teams at Uber, and hence they are compatible with each other. While Jaeger is an end-to-end distributed tracing tool, OpenTracing is a set of APIs and libraries that can be used to instrument your application.

Tracing AWS Lambdas with OpenTelemetry and Elastic Observability

Open Telemetry represents an effort to combine distributed tracing, metrics and logging into a single set of system components and language-specific libraries. Recently, OpenTelemetry became a CNCF incubating project, but it already enjoys quite a significant community and vendor support. OpenTelemetry defines itself as “an observability framework for cloud-native software”, although it should be able to cover more than what we know as “cloud-native software”.

OpenTelemetry tracing - things you need to know before implementing

Setting up observability and robust monitoring for distributed systems is a challenging task. Engineering teams need access to different pieces of information to understand what's happening with their application. Is OpenTelemetry a step in the right direction for distributed tracing? Let's find out. Nothing can guarantee how your systems will behave in production. Things will go wrong, and it's critical to monitor your application for any signs that need troubleshooting.

An Introduction to Distributed Tracing

There’s no strict definition of a distributed system. But generally speaking, if you have reached a point where you’re running more than five interdependent services at once, that means you’re running a distributed system. It also means you are more than likely experiencing difficulties when troubleshooting using traditional debugging tools. Unfortunately, pulling up multiple tools, each built for a monolithic world, doesn’t help pinpoint the problem.

Java Application Manual Instrumentation for Distributed Traces

In this blog series, we are covering application instrumentation steps for distributed tracing with OpenTelemetry standards across multiple languages. Earlier, we covered Golang Application Instrumentation for Distributed Traces and DotNet Application Instrumentation for Distributed Traces. Here we are going to cover the instrumentation for Java.

The Stanza Story

We launched the Stanza log agent just over one year ago. Stanza is the result of an uncompromising stance on performance, processing, and configurability for log telemetry. It took mere days for friends and colleagues in the space to raise the obvious objection – there are already so many logging agents, so why spend time on a *new* one? We also heard from competitors who had a snarkier take…

Distributed Tracing for C++ Applications with OpenTelemetry & Logz.io

Many organizations are moving from monolithic to microservices-based architectures. Microservices allow them to improve their agility and provide features more quickly. Although developing a single microservice is simpler, the complexity of the overall system is much greater. Here, we’ll review how to add distributed tracing to C++ with the OpenTelemetry collector and send to Logz.io. One of the biggest challenges is finding efficient tools to quickly debug and solve production problems.