If you happen to be running multiple clusters, each with a large number of services, you’ll find that it’s rather impractical to use static alerts, such as “number of pods < X” or “ingress requests > Y”, or to simply measure the number of HTTP errors. Values fluctuate for every region, data center, cluster, etc. It’s difficult to manually adjust alerts and, when not done properly, you either get way too many false-positives or you could miss a key event.

There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketers stepped in. Widespread overuse of the terms AI/ML in marketing have managed to thoroughly confuse the meanings of these words.

This is a companion post to a recent webinar with an OpsRamp partner, Flycast Partners. Check out the recorded webinar on YouTube and slides on SlideShare for the potential impacts of ITSM and ITOM silos and how a modern ITOM platform can help improve bi-directional collaboration and reduce mean-time-to-resolution.

I have been super fortunate to work with incredibly innovative, talented teams that create powerful technology to help manage the world's data. When I met with Thomas Hazel, CHAOSSEARCH founder and CTO, and Les Yetton, CHAOSSEARCH co-founder and CEO to talk about CHAOSSEARCH — scalable, performant text search to your object storage without having to move any data — I knew it was special and was eager to join.

Docker and Kubernetes have taken the software world by storm. DevOps, containers, and container management are at the center of most conversations about what’s relevant to technology. Tooling and services that ease running software in containers, therefore, occupy the minds of developers. Great tools and platforms create options and possibilities. They also create challenges in understanding available choices, though.

The next major version of the LogDNA agent is right around the corner, and we’re introducing some significant improvements. Most notably, we’ve completely rewritten the agent using Rust instead of Node.js. As we gear up for the release, we wanted to explain why we chose Rust for the LogDNA agent, the benefits that it offers over other languages, and how it can help you log faster. Rust is a systems programming language that aims to offer both performance and safety.

When developing web services and tuning the infrastructure that runs them, you’ll want to make sure that they handle requests quickly enough, and at a high enough volume, to meet your requirements. ApacheBench (ab) is a benchmarking tool that measures the performance of a web server by inundating it with HTTP requests and recording metrics for latency and success.

HashiCorp Consul is agent-based cluster management software that addresses the challenge of sharing network and configuration details across a distributed system. Consul handles service discovery and configuration for potentially massive clusters of hosts, spread across multiple datacenters.

In Part 1, we looked at metrics and logs that can give you visibility into the health and performance of your Consul cluster. In this post, we’ll show you how to access this data—and other information that can help you troubleshoot your Consul cluster—in four ways: Consul provides a built-in CLI and API that you can use to query the most recent information about your cluster, giving you a high-level read into Consul’s health and performance.

IoT, or the Internet of Things, has made its way into every corner of our lives. Once upon a time, the idea of an inescapable internet may have seemed like a far-off dream. Today, it’s our reality. Internet connected devices are everywhere—from our fitness trackers to our vehicles and appliances. These devices track our sleep patterns, enable us to set our coffee machines remotely, and find our pets after they have wandered off, among countless other tasks.