Operations | Monitoring | ITSM | DevOps | Cloud

Today, many companies generate and store huge amounts of data. To give you an idea, decades ago, the size of the Internet was measured in Terabytes (TB) and now it is measured in Zettabytes (ZB). Relational databases were designed to meet the storage and information management needs of the time. Today we have a new scenario where social networks, IoT devices and Edge Computing generate millions of unstructured and highly variable data.

CPU utilization is a crucial metric for measuring system performance and identifying potential bottlenecks in Linux systems. This article explores the concept of CPU utilization, factors contributing to high CPU usage, and various command-line tools and graphical utilities for monitoring and troubleshooting CPU utilization in Linux environments.

Rootly On-Call streamlines incident management with automated scheduling, noise reduction, and centralized documentation. It mitigates on-call fatigue with features like flexible overrides, shift visibility, and shadow rotations, enhancing team well-being and preventing burnout.

One of the real successes of the Agile Software development movement has been the push to have regular, frequent deployments. This has manifested as build and deployment automation and the general adoption of CI/CD. As engineers automate more processes of their software release lifecycle, an important question is how to automate Quality Assurance, which includes resilience testing and, more specifically, Fault Injection.

Real User Monitoring (RUM) is a type of performance monitoring that involves tracking and analyzing user interactions with a website or web application in real-time. RUM provides valuable insights into how users experience a website or an application by collecting data directly from their browsers and devices during these interactions. Unlike traditional performance monitoring methods that focus on server-side metrics, RUM provides real-time insights into actual user behaviors.

Over the last five years we’ve seen our customers run 583,954 incidents more efficiently thanks to a shared workspace, powerful Runbook automations, and auto-captured data. Yet despite a great deal of progress, incident efficiency hasn’t achieved peak potential. We talk to a lot of folks that are still stuck in the muck: new responders struggle to get up to speed quickly, incident commanders wade through post-incident drudgery, and knowledge silos prevent comprehensive improvements.

Kubernetes has emerged as a pivotal force in shaping modern cloud infrastructure. Originating as a brainchild of Google, Kubernetes has evolved into an open-source platform that has revolutionized how applications are deployed, scaled, and managed across a vast network of machines. Its ability to orchestrate containerized applications efficiently makes it an indispensable tool within cloud computing. However, with great power comes great responsibility, particularly in the realm of cost management.

In this post, we delve into the comparative analysis of the commercial offerings of five leading monitoring solutions—Dynatrace, Datadog, Instana, Grafana, and Netdata. Our objective is to unravel the intrinsic value each of these services offers when applied to a real-world scenario.