Since September 2019, the RITlug TeleIRC team is hard at work on the v2.0.0 release of TeleIRC. This blog post is a short update on what is coming in TeleIRC v2.0.0, our progress so far, and when to expect the next major release.
Tagresearch and learning
Recently, I worked on an interesting project to evaluate different container run-times for high-performance computing (HPC) clusters. HPC clusters are what we once knew as supercomputers. Today, instead of giant mainframes, they are hundreds, thousands, or tens of thousands of massively parallel systems. Since performance is critical, virtualization with tools like virtual machines or Docker containers was not realistic. The overhead was too much compared to bare metal.
However, the times are a-changing! Containers are entering as real players in the HPC space. Previously, containers were brushed off as incompatible with most HPC workflows. Now, several open source projects are emerging with unique approaches to enabling containers for HPC workloads. This blog post evaluates four container run-times in an HPC context, as they stand in July 2019:
The needs and demands of infrastructure environments changes every year. With time, systems become more complex and involved. But when infrastructure grows and becomes more complex, it’s meaningless if we don’t understand it and what’s happening in our environment. This is why monitoring tools and software are often used in these environments, so operators and administrators see problems and fix them in real-time. But what if we want to predict problems before they happen? Collecting metrics and data about our environment give us a window into how our infrastructure is performing and lets us make predictions based on data. When we know and understand what’s happening, we can prevent problems before they happen.
But how do we collect and store this data? For example, if we want to collect data on the CPU usage of 100 machines every ten seconds, we’re generating a lot of data. On top of that, what if each machine is running fifteen containers? What if you want to generate data about each of those individual containers too? What about by the process? This is where time-series data becomes helpful. Time-series databases store time-series data. But what does that mean? We’ll explain all of this and more and introduce you to InfluxDB, an open source time-series database. By the end of this article, you will understand…
- What time-series data / databases are
- Quick introduction to InfluxDB and the TICK stack
- How to install InfluxDB and other tools
This article was originally published on the Fedora Magazine.
This article is part of a short series that introduces Kubernetes. This beginner-oriented series covers some higher level concepts and gives examples of using Kubernetes on Fedora.
The information technology world changes daily, and the demands of building scalable infrastructure become more important. Containers aren’t anything new these days, and have various uses and implementations. But what about building scalable, containerized applications? By itself, Docker and other tools don’t quite cut it, as far as building the infrastructure to support containers. How do you deploy, scale, and manage containerized applications in your infrastructure? This is where tools such as Kubernetes comes in. Kubernetes is an open source system that automates deployment, scaling, and management of containerized applications. Kubernetes was originally developed by Google before being donated to the Cloud Native Computing Foundation, a project of the Linux Foundation. This article gives a quick precursor to what Kubernetes is and what some of the buzzwords really mean.
This week, with an initial playbook for creating a WordPress installation created (albeit needing polish), my next focus was to look at the idea of creating a WordPress multi-site network. Creating a multi-site network would offer the benefits of only having to keep up a single base installation, with new sites extending from the same core of WordPress. Before making further refinements to the playbook, I wanted to investigate whether a WordPress network would be the best fit for Fedora.