Modern digital businesses have adopted cloud technology and distributed architectures to enable on-demand scaling of resources. Containerization technologies like Kubernetes and Docker have made it possible to handle customer demands at scale. However, orchestrating a complex microservices architecture with Kubernetes is challenging. Monitoring your Kubernetes cluster can give you insights to better manage your cluster.

Welcome back to our monthly product updates - SigNal! Our team shipped some major upgrades to SigNoz last month. We’re elated to share that SigNoz is now available with log management. It’s a major milestone in our journey of democratizing observability for developer teams of all sizes. We also shipped an intuitive alerts builder, attended conferences, and played new games in our Friday chit-chats 🥳 A lot of new open source contributors also helped us in making SigNoz better.

Monitoring tools are only as good as the range and visibility they offer admins into applications’ performance. Prometheus is a metrics monitoring tool that provides a pull-based system to collect and monitor time-series samples. Once the data is collected and stored, you can use Prometheus Queries to interact with the data: select and aggregate across the provided dimensions. This article takes the reader from concept to content state about the Prometheus Query language.

In this guide, we will discuss the different aspects of MongoDB performance monitoring. MongoDB provides a set of tools and command-line utilities to monitor MongoDB instances. But first, you need to know what metrics should be monitored. Once you understand the performance metrics, you can create workflows and processes to keep a check on your MongoDB cluster’s health and performance.

Wherever you read about observability, you are told that there are "3 pillars" of observability - Metrics, Traces and Logs. An image that is generally projected is something like this. But wait a minute, why are there only three pillars, and does it really matter to the end user? At the end of the day, users are just trying to solve their problems fast.

One of the easiest ways to see if the application running in our nodes is in an optimized state or not is by monitoring them. It is the last yet critical stage of any software development lifecycle. It opens up many possible improvements in your application, networking, IT automation, and other miscellaneous configurations. As we move towards microservice architecture, containerization and orchestration tools are rising. Containers are special processes that run in isolation from other processes.

It’s time for our monthly product updates. Closing GitHub issues, fixing bugs, shipping code, and sipping coffee, time flies by every month. Last month, we crossed a major milestone of 7000+ GitHub stargazers. We can not thank the developer community enough for supporting us in our mission to democratize observability.

Docker containers are transient (lasting for a very short time), spawning quickly and in high numbers, which causes metrics bursts. This makes monitoring a challenge due to Docker's scaling and redeployment features. Docker stats is a built-in feature of Docker containers. The docker stats command returns a live data stream of your running containers. Docker is a containerization platform that lets you separate your applications from your infrastructure to deliver software quickly.

Prometheus and the Elasticsearch stack are both used for monitoring applications. But while Prometheus is primarily meant to monitor metrics, the Elasticsearch stack or the ELK stack is mainly used to collect, store, analyze, and visualize application logs. In this article, we will see what Prometheus and ELK stack is and compare their differences. Prometheus is a time-series metrics monitoring tool. Prometheus enables you to capture time-series data as metrics.

Every month, our team works on two major fronts: shipping new features asked by users and iterating on shipped features to make them better for existing users. Last month, our team worked closely with users to ship a lot of product improvements both in UI and backend performance. Alongside that, we have been working on metrics builder and log management, two major feature upgrades to SigNoz.