Operations | Monitoring | ITSM | DevOps | Cloud

For a game to provide the best user experience, certain elements come into play. These factors can be hardware components in the user’s computer, like the CPU and GPU, operating system settings, or specific game settings. In fact, if there’s misalignment between these components and a game’s intensity, performance issues can crop up. The most common performance issues in gaming include frame rate drops, input lag, stuttering, rendering issues and network latency.

Cloud monitoring tools are utilized to gather an extensive range of metrics and logs from cloud resources and services. Some commonly monitored metrics include CPU utilization, memory usage, network traffic, disk I/O, latency, and response time. By monitoring these metrics, among others, it becomes possible to gain insights into resource utilization, identify performance bottlenecks, and ensure that the infrastructure operates according to expectations.

The Grafana Labs ecosystem is built on a range of different projects that incorporate logs, metrics, traces across load testing, and Kubernetes monitoring. I’ll assume you know all of that data (and more!) can be visualized in Grafana. What made my observability dream become reality, though, is how these systems can work together to help you effectively debug performance issues and operate your system with more confidence.

Today I want to talk about metric queries. More specifically, I want to talk about an important concept that is going to make your queries run faster, give you more accurate results, and make your Grafana Loki operators (like me) much happier. A metric query in Loki looks like this: And the part I want to talk about is that at the end. Now, if you’re like me and have a short attention span and are already bored — I understand.

Health checks are an important factor when working with containerized applications in the cloud and are the source of truth for many applications in terms of their running status. In the context of AWS Elastic Container Service (ECS), health checks are a periodic probe to assess the functioning of containers. In this blog, we will explore how Lumigo, a troubleshooting platform built for microservices, can help provide insights into container crashes and failed health checks.

Can you believe we’re already halfway through 2023? Time flies when you’re busy innovating and having fun (yet somehow also seems so slow when you are waiting for your next vacation!!). At Cribl, we’ve been hard at work releasing wave after wave of incredible new features and capabilities across our entire product suite.

Users with real-time and other analytic workloads want or need to keep large volumes of historical data to aid in important activities, such as ad hoc historical trend analysis and training AI models. However, storing this much data in a way that also makes it easily queryable becomes prohibitively expensive. As a result, users must balance data availability and usability with sacrificing data fidelity and storage costs. That is until now.

Welcome to the latest changelog blog post, where we highlight the recent updates and improvements to our products and services. We've been working hard to enhance your experience. Let's dive into the changes made in June 2023!

Graphios simplifies the process of sending Nagios performance data to backend systems like Graphite. With Graphios, users can easily integrate Nagios with Graphite, eliminating the need for complex scripts. This article explores Graphios' functionality, configuration, and installation process, empowering users to efficiently transfer Nagios data for monitoring and analysis.