Operations | Monitoring | ITSM | DevOps | Cloud

As an operations engineer (SRE, IT manager, DevOps), you’re always struggling with how to manage technology and data sprawl. Kubernetes is becoming increasingly pervasive and a majority of these deployments will be in Amazon Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), or Azure Kubernetes Service (AKS). Some of you may be on a single cloud while others will have the added burden of managing clusters on multiple Kubernetes cloud services.

Containers have been the buzz among developers in recent years with the adoption of cloud-native orchestration tools like Kubernetes and DevOps workflows centered around containers. At the same time, virtual machines (VMs) still power many enterprise workloads, whether they’re running in a public cloud provider like Azure or an on-premises data center running VMware. In one of my early jobs, we built a private cloud—in 2012. This was a ground-breaking project at the time.

Users live in the sunlit world of what they believe to be reality. But, there is, unseen by most, an underworld. A place that is just as real, but not as brightly lit. The Kernel Parameter side (apologies to George Romero). Kernel parameters aren’t really that scary in actuality, but they can be a dark and cobweb-filled corner of the Linux world. Kernel parameters are the means by which we can pass parameters to the Linux (or Unix-like) kernel to control how that it behaves.

It can be a challenge to measure costs within a SaaS company. While a business with physical inventory can count the number of items sitting on the shelf and the money needed to create, store, and ship those items, operating within the cloud means SaaS companies have to measure their costs through a layer of abstraction. The number of users a given product supports and the resources needed to keep that product up and running could change by the minute.

Over the last few years, containers have been one of the hottest topics when it comes to radically changing the way we develop, operate, and maintain our applications. And it’s no coincidence the rise of containers has occurred right alongside the rise of the cloud and the DevOps movement. This shift in development and operations has brought new challenges as container technologies have evolved.

October has, as usual, been a busy month, and Sysdig announced many new features. In Sysdig Monitor, we announced the release of four new Advisories and Yaml config support for Advisor. In Sysdig Secure, we released Severity filtering in Insights, Pod and Node activity view in Insight and four new Falco rules added to the Rules Library. Each of these are discussed in detail below.

The Kubewarden development team is happy to announce the release of the Kubewarden 1.3 stack. In addition to the usual amount of small fixes, this release focused on the following themes. If you’re not familiar with Kubewarden, it is a policy engine for Kubernetes. Its mission is to simplify the adoption of policy-as-code.

In the second part of our “Kubernetes interview questions” series, we have outlined ten questions to help those that want to take their Kubernetes knowledge to the next level. Read on to learn more about the difference between Kubernetes and Docker Swarm. We’ll also be covering how an organization can keep costs low using Kubernetes. If you missed part one, check it out here.