Operations | Monitoring | ITSM | DevOps | Cloud

A robust observability strategy forms the backbone of a successful cloud environment. By understanding cloud observability and its benefits, businesses gain the ability to closely monitor and comprehend the health and performance of various systems, applications, and services in use. This becomes particularly critical in the context of cloud computing. The resources and services are hosted in the cloud and accessed through different tools and interfaces.

IDC published a Market Perspective report discussing implementations to leverage Generative AI. The report calls out the Elastic AI Assistant, its value, and the functionality it provides. Of the various AI Assistants launched across the industry, many of them have not been made available to the broader practitioner ecosystem and therefore have not been tested. With Elastic AI Assistant, we’ve scaled out of that trend to provide working capabilities now.

Businesses are increasingly turning to cloud computing to drive innovation, scalability, and cost efficiencies. For many, managing cloud costs becomes a complex and daunting task, especially as organizations scale their cloud infrastructure and workloads. In turn, cloud cost management tools can help teams gain better visibility, control, and cost optimization of their cloud spending. These tools not only provide comprehensive solutions to track and analyze, they also optimize cloud expenses.

“How can we turn our DevOps data into useful DevSecOps data? There is so much of it! It can come from anywhere! It’s in all sorts of different formats!” While these statements are all true, there are some similarities in different parts of the DevOps lifecycle that can be used to make sense of and unify all of that data. How can we bring order to this data chaos? The same way scientists study complex phenomena — by making a conceptual model of the data.

This article will outline what Redis database monitoring is and how to set up a Redis database monitoring system with MetricFire. Then we’ll show what the final graphs and dashboards look like when displayed on Grafana. We will be using Prometheus and Grafana to power the monitoring, and we'll use a simulated Redis DB to generate the data for the Grafana dashboards. ‍ ‍

In recent years, employees have grown increasingly accustomed to the untethered connectivity of Wi-Fi. For many, the days of having a computer tethered to an ethernet cable can seem like a distant memory. That was true when employees were working in an office, and it is all the more the case as we’ve moved to a hybrid work world.

Managing containerized applications efficiently in the dynamic realm of Kubernetes is essential for smooth deployments and optimal performance. Kubernetes empowers us with powerful orchestration capabilities, enabling seamless scaling and deployment of applications. However, in real-world scenarios, there are situations that necessitate the restarting of Pods, whether to apply configuration changes, recover from failures, or address misbehaving applications.

With Infrastructure as Code and service-oriented development, a modern web app can consist of countless moving parts developed by multiple development and DevOps teams. When establishing a high-velocity development environment, the main question is, "How can you guarantee a stellar end-user experience when lots of engineers are constantly pushing and deploying code?" Solid, easy-to-write, and clearly defined monitoring practices are the only answer to this question.

The rapid adoption of software-defined wide-area networking (SD-WAN) has revolutionized how organizations connect their distributed networks. As businesses strive for improved performance, cost efficiency, and enhanced security, SD-WAN solutions have emerged as a game-changer. However, orchestrating a successful SD-WAN migration at a global scale presents numerous challenges that demand careful planning, meticulous execution, and robust network performance monitoring (NPM) capabilities.