Security in the cloud has become an increasingly important topic over the years, with the move to more managed services, additional trust is being handed over to cloud providers. With this being said, we must begin to pay closer attention to the security surrounding cloud computing, especially when it comes to Kubernetes. Join me as I explore the concept of confidential computing and a new use case we at Civo have been working on related to the Kubernetes control plane in managed clusters.

Overprovisioning or underprovisioning your Kubernetes resources can have significant consequences on both your budget and your app performance. By underprovisioning your Kubernetes infrastructure, you’ll end up with lagging, underperforming, unstable, or non-functional applications. On the opposite end of the spectrum, overprovisioning is a costly issue: Organizations spent almost $500 billion on cloud resources in 2022, yet an estimated 30% of those were wasted.

We are thrilled to announce our partnership with Kubecost, a game-changing provider of cost monitoring for Kubernetes clusters. This collaboration marks a new era in efficiency and cost-effectiveness for DevOps teams everywhere. With Kubecost's advanced monitoring capabilities integrated into our own Kubernetes deployment platform, we are empowering organizations to take control of their cloud-native infrastructure like never before.

Content The Sysdig 2023 Cloud-Native Security and Container Usage Report has shed some light on how organizations are managing their cloud environments. Based on real-world customers, the report is a snapshot of the state of cloud-native in 2023, aggregating data from billions of containers.

You'll notice that monitoring and logging don't appear on the list of core Kubernetes features. However, this is not due to the fact that Kubernetes does not offer any sort of logging or monitoring functionality at all. It does, but it’s complicated. Kubernetes’ kubectl tells us all about the status of the different objects in a cluster and creates logs for certain types of files. But ideally speaking, you won't find a native logging solution embedded in Kubernetes.

Nowadays, it is rather common to see companies adopt several monitoring solutions based on Prometheus, but this is not exempt from pain. A huge number of systems, applications, and third-party software are not instrumented to expose Prometheus metrics natively. Here is where Prometheus exporters come into play.

Deploying and managing applications in the cloud can be complex and time-consuming, especially when using Kubernetes. However, Qovery has made this process much easier with its platform abstracts away the complexity of Kubernetes and provides developers with the tools they need to manage their deployments. But how does Qovery manage thousands of Kubernetes clusters with a single control plane?

One may say that competitive dynamics in the automotive space are constantly changing, and they would not be wrong in the slightest. As retailers face the daily battlefield of getting their customers’ attention with the right mix of products at the right price and on the right platform, their technology infrastructure must be lean and efficient while achieving those goals—and that is no easy feat.

Since the very first version, Epinio has made use of an internal S3 endpoint to store the user’s projects in the form of aggregated tarballs. Those objects are then downloaded and staged by the internal engine’s pipeline and, finally, they are deployed into the Kubernetes cluster as consumable applications. Epinio makes use of S3 as an internal private service. In this scenario, S3 can be thought of as an internal ephemeral cache with the purpose of storing temporary objects.

By kickstarting a monitoring project with Prometheus, you might realize that you get an initial set of out-of-the-box metrics with just Node Exporter and Kube State Metrics. But, this will only get you so far since you will just be performing black box monitoring. How can you go to the next level and observe what’s beyond? They are an essential part of the day-to-day monitoring of cloud-native systems, as they provide an additional dimension to the business and app level.