Operations | Monitoring | ITSM | DevOps | Cloud

Sometimes, two concepts overlap so much that it’s hard to view them in isolation. Today, incident management and problem management fit this description to a tee. This wasn’t always the case. For a long time, these two ITIL concepts were seen as distinct—with specialized roles overseeing each. Incident management existed in one corner and problem management in the other. Then came the DevOps movement and the lines suddenly became blurred. So where do they stand today?

In this article, we will be covering how to monitor Kubernetes using Graphite, and we’ll do the visualization with Grafana. The focus will be on monitoring and plotting essential metrics for monitoring Kubernetes clusters. We will download, implement and monitor custom dashboards for Kubernetes that can be downloaded from the Grafana dashboard resources. These dashboards have variables to allow drilling down into the data at a granular level.

Prometheus is becoming a popular tool for monitoring Python applications despite the fact that it was originally designed for single-process multi-threaded applications, rather than multi-process. Prometheus was developed in the Soundcloud environment and was inspired by Google’s Borgmon. In its original environment, Borgmon relies on straightforward methods of service discovery - where Borg can easily find all jobs running on a cluster.

Before we jump into the specifics of Grafana and Datadog, let's look at the main comparison points. Grafana is a great dashboard that allows you to plug in essentially any data source in the world. Grafana is most commonly paired with Prometheus, Graphite, and Elasticsearch to provide a full APM, time-series, and logs monitoring stack.

DevOps is a practice that combines software development and IT operations to improve the speed, quality, and efficiency of software delivery. By breaking down traditional silos between development and operations teams and promoting a culture of continuous improvement, DevOps helps organizations achieve their goals and remain competitive in today’s fast-paced digital landscape. To better understand how we asked engineers what key DevOps benefits they noticed since working with this approach.

A Key Management Service (KMS) is used to create and manage cryptographic keys and control their usage across various platforms and applications. If you are an AWS user, you must have heard of or used its managed Key Management Service called AWS KMS. This service allows users to manage keys across AWS services and hosted applications in a secure way.

This is the first post of a 2 part series where we will set up production-grade Kubernetes logging for applications deployed in the cluster and the cluster itself. We will be using Elasticsearch as the logging backend for this. The Elasticsearch setup will be extremely scalable and fault-tolerant. ‍

In this tutorial, we will learn about configuring Filebeat to run as a DaemonSet in our Kubernetes cluster in order to ship logs to the Elasticsearch backend. We are using Filebeat instead of FluentD or FluentBit because it is an extremely lightweight utility and has a first-class support for Kubernetes. It is best for production-level setups. This blog post is the second in a two-part series. The first post runs through the deployment architecture for the nodes and deploying Kibana and ES-HQ.

AI is booming. The AI market is projected to grow 37.3% annually from 2023 to 2030. With so many organizations adopting or considering AI applications, data centers need to be ready to support the new demand. However, without the right tools and data, it is difficult to understand if your existing facilities have the capacity to support systems like the “gold standard for AI infrastructure,” the NVIDIA DGX H100.