In a previous blog post, we explained how containers’ CPU and memory requests can affect how they are scheduled. We also introduced some of the effects CPU and memory limits can have on applications, assuming that CPU limits were enforced by the Completely Fair Scheduler (CFS) quota. In this post, we are going to dive a bit deeper into CPU and share some general recommendations for specifying CPU requests and limits.

Tradeoff: a balance achieved between two desirable but incompatible features; a compromise. Schooling often promotes the idea that there is a right and wrong answer to questions… It does little to prepare us for how many times that there are multiple right answers and no definitive best path forward. In a time where we have unlimited information at our fingertips, you can throw a stone and hit a thousand people with an opinion.

This blog post by Grafana Labs Senior Software Engineer Milan Plžík was originally published on the Kubernetes.io blog on Nov. 16, 2023. There’s been quite a lot of posts suggesting that not using Kubernetes resource limits might be a fairly useful thing (for example, For the Love of God, Stop Using CPU Limits on Kubernetes or Kubernetes: Make your services faster by removing CPU limits ).

This is the final article of a three-part series. To start at the beginning, read Part 1: Benefiting from multi-cluster setups requires familiarity with common variations and Part 2: Exploring the facets of a multi-cluster observability strategy. As companies scale software production, they lean on Kubernetes as a crucial container orchestration platform for managing, deploying and ensuring software availability.

As cloud computing continues to grow in popularity, so does the need for accurate cloud cost forecasting. With cloud costs being variable and unpredictable, it can be difficult to know how much you’re going to spend each month, a problem that can lead to budget overruns and financial problems. This makes cloud cost forecasting a necessary step in owning and managing your cloud efficiently. In simple terms, cloud cost forecasting is the process of predicting future cloud costs.

If you’re building apps to run on Kubernetes, chances are you’re using Helm. If you fall into that category, we have good news for you: Helm users will now benefit from JFrog Artifactory’s support of Helm OCI registries in JFrog Artifactory.

Great news for developers who leverage containers — JFrog has expanded its support for the OCI Container standard with dedicated OCI repositories! Before we touch on that, let’s do a quick recap on OCI containers for those unfamiliar with them outside the context of Docker.

As a CTO, you need to come up with new strategies and tools to ensure that your company manages the rapidly changing world of software development. Platform Engineering and Internal Developer Platforms (IDPs) have become essential elements of this journey that change how software is developed and released.

Effective EKS monitoring is crucial for maintaining the health and performance of containerized applications deployed in the cluster. In this tutorial, we will set up EKS monitoring with OpenTelemetry. We will build monitoring dashboards for node and pod-level metrics with data collected by OpenTelemetry. We will use SigNoz, an open-source OpenTelemetry-native APM, as a storage and visualization layer for setting up dashboards.

Imagine a scenario where your developers spend less time waiting for resources and approvals, and more time focusing on the core aspects of building exceptional software. This vision becomes reality with the implementation of an internal developer platform (IDP), a revolutionary tool that acts as a catalyst for innovation within your organization.