Operations | Monitoring | ITSM | DevOps | Cloud

September 2021

Using Jaeger for your microservices

Jaeger is a popular open-source tool used for distributed tracing in a microservice architecture. In a microservice architecture, a user request or transaction can travel across hundreds of services before serving what a user wants. Distributed tracing helps to track the performance of a transaction across multiple services. Before we deep dive into how Jaeger accomplishes distributed tracing for microservices-based architecture, let's take a short detour to understand distributed tracing.

AWS X-Ray vs Jaeger - key features, differences and alternatives

Both AWS X-Ray and Jaeger are distributed tracing tools used for performance monitoring in a microservices architecture. Jaeger was originally built by teams at Uber and then open-sourced in 2015. On the other hand, AWS X-Ray is a distributed tracing tool provided by AWS specifically focused on distributed tracing for applications using Amazon Cloud Services. Jaeger is a popular open-source tool that graduated as a project from Cloud Native Computing Foundation.

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.

Metrics first look, more robust frontend and much more - Signal 04

Folks! Great to have you over for our monthly product update aka Signal #04. This month we made great strides in both our frontend and backend pods. Metrics ingestion, testing frameworks, improved tracking features for gRPC calls and much more! We also crossed 200+ members on our slack community 🎉🎉🎉 Let's dive in to see what humans at SigNoz have been upto!

Observability 101 using OpenTelemetry & SigNoz @ Kubernetes Community Day

In this workshop, we will learn about the basics of observability and its benefits. We will take a hands on approach and actually instrument an application with OpenTelemetry, which is a vendor neutral instrumentation library. Then we will visualise the data sent by open telemetry with SigNoz, which is a full stack observability platform. In the last section, we will take an example of a real world issue and how this observability stack can be used to find the root cause of the issue.

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.