Operations | Monitoring | ITSM | DevOps | Cloud

Have you ever used the term bandwidth? Probably. Have you ever used the term network throughput? Maybe. Have you used them interchangeably? Most likely. So let’s see where we get these mixed up. Namely, let’s look at the key differences between network throughput and bandwidth. And while we’re at it, let’s cover the fundamentals of throughput and how to measure it, so you can keep your network flowing efficiently and cleanly.

Cloud-native and serverless come hand in hand. One of the initial motivations to move business workflows to the cloud was related to cutting costs related to provisioning infrastructure and elasticity that on-demand allocation of resources is offering.

Kubernetes is hard, but lets make monitoring and alerting for Kubernetes simple! At iLert we are creating architectures composed of microservices and serverless functions that scale massively and seamlessly to guarantee our customers uninterrupted access to our services. As many others in the industry we are relying on Kubernetes when it comes to the orchestration of our services.

I’m a fresh starter here at Grafana Labs, leading one of our teams working on the Grafana Enterprise Stack. As a longtime user of Grafana, I couldn’t wait to see what’s new in versions 1.1 and 1.2 of Grafana Enterprise Metrics (GEM), our scalable, self-hosted Prometheus service. I tried out the shiny features and wanted to share some of the cool things I found.

Technology and end users have an almost dichotomous relationship; as technology gets more complex, end users expect a more seamless experience. At the same time, end users are also looking for maximized application availability and performance. How can a federal IT team meet these increasing demands? The answer is monitoring. Most monitoring instances have been implemented as an afterthought or as a way to solve a single, specific problem.

How would you like it if your application shut down or started running slow without any warning? Let’s say, for instance, users who like your application try to access it, but aren’t able to. How would you know whether low traffic to your site is because users weren’t satisfied or because they simply weren’t able to access it? Users definitely won’t be satisfied when your application starts crawling with long response times.

When you want to stay ahead and on top of things in a fast-moving industry, machine learning (ML) is surely one of the trending solutions. Today, innovative companies already have leading Machine Learning tools well-integrated into their processes. In comparison, your start could seem dreadfully slow. Or maybe you just don’t have the time or resources to invest in running your own Machine Learning training infrastructure.