Operations | Monitoring | ITSM | DevOps | Cloud

This year’s AWS Summits are more than a little different. Despite being virtual due to the COVID-19 pandemic, AWS is packing these events with lots of content. I’ve had a great time attending virtually, trying out hands-on labs, and sitting in on the technical sessions. As I work primarily with cost management and optimization for cloud compute services, this has been my main interest in attending the conferences. Here are my main takeaways around better managing your AWS cloud costs.

Red Hat OpenShift and JFrog Artifactory are a smooth fit together for cloud native, containerized software development at enterprise scale. With the new availability of OpenShift operators certified for JFrog Enterprise, that fit now fastens tight.

Installing Artifactory on GKE, or on any Kubernetes cluster for that matter, can be complex. You have to think through several scenarios, switch back and forth between UI and command line, create a lengthy Helm command, search for acceptable parameters … and so on. All this before you have to configure certificates, licenses, database settings, node settings. But there’s more, what about future proofing it?

So, let's say you had a service or application that was built on an orchestration platform such as Kubernetes. In doing so, you must also address an overflowing array of architectural issues, including security, multi-tenancy, API gateways, CLI, configuration management, and logging. Wouldn't you like to save some manpower and development time and focus on creating something unique to your problem? Well, it just so happens that your solution lies in what's called a Custom Resource Definition, or CRD.

Editor’s note: This is a follow up to a recent post on how to use Cloud Logging with containerized applications running in Google Kubernetes Engine. In this post, we’ll focus on how DevOps teams can use Cloud Monitoring and Logging to find issues quickly. Running containerized apps on Google Kubernetes Engine (GKE) is a way for a DevOps team to focus on developing apps, rather than on the operational tasks required to run a secure, scalable and highly available Kubernetes cluster.

Yeah, Kubernetes is great at making sure your workloads run as needed. But another of its amazing benefits is its ability to recover from failure all by itself. On an everyday basis, Kubernetes takes care of the complicated task of container orchestration. However, as with any complicated system, there is always the chance that you’ll experience failures and downtime.

Microsoft Azure is a cloud computing platform for building, deploying, and managing global-scale applications. With a wide range of offerings, including dozens of different services, Azure provides tools for users to create large and sophisticated systems for hosting any type of workload. But with the huge number of configuration options and resource types, understanding the health and performance of your applications in Azure can be challenging.