Cloud Native Weekly: Deletions, deprecations, and major changes in Kubernetes 1.29 | 2023.11.27

Open source project recommendations

Orphaned ConfigMaps

This repository contains a script to identify orphaned configuration mappings in the Kubernetes namespace. Orphaned configuration maps are those that are not referenced by any active Pod or container in the namespace.

Kubernetes Multi Cooker

The project consists of a small Kubernetes controller that monitors the CPU pressure of each node; when it exceeds a certain threshold, the node will be polluted (so that no additional workload is scheduled on an already overloaded node), and finally controls The server will begin evicting Pods from this node.

Reflector

Reflector is a Kubernetes plugin designed to monitor changes to resources (secrets and configuration maps) and reflect changes to mirrored resources in the same or other namespaces.

Article recommendations

Removals, deprecations, and major changes in Kubernetes 1.29

Like every other release, Kubernetes v1.29 will deprecate and remove features. The ability to consistently produce high-quality releases is evidence of a robust development cycle and a healthy community. This article lists some deprecations and removals in the upcoming Kubernetes 1.29.

Top 5 Storage Provider Tools for Kubernetes

This article introduces the five storage provider tools for Kubernetes: SeaweedFS, Vitess, TiKV, Rook, and OpenEBS. These tools help manage data workloads on Kubernetes, including functions such as volume provisioning, replication, backup, encryption, compression, and performance tuning. They integrate seamlessly with Kubernetes APIs and concepts and support Persistent Volumes (PV), Persistent Volume Claims (PVC), and Storage Classes. This article details how each tool works, its advantages, as well as practical use cases and success stories. By reading this article, readers can learn about the storage provider options available on Kubernetes and choose the most appropriate tool based on their needs.

Troubleshoot Kubernetes deployments at all levels

This article is a guide to troubleshooting Kubernetes deployment issues at all levels. The article first introduces Kubernetes as the de facto standard for container orchestration and mentions its ability to automate the deployment, scaling and management of containerized applications. However, even with best practices and expertise in place, Kubernetes deployment can sometimes be a complex and challenging process. The article explores the deployment troubleshooting process at every level, from application code to infrastructure and Kubernetes components, and introduces some common issues and challenges such as container image pull errors, Pod scheduling issues, network connectivity issues, and storage issues. The article also discusses some best practices and tools for diagnosing and resolving these issues. By reading this article, readers will better understand how to troubleshoot every level of a Kubernetes deployment and better manage their applications.

Cloud native dynamics

CNCF Platform Engineering Maturity Model Released

The platform engineering maturity model of CNCF (Cloud Native Computing Foundation) was released for the first time. The model provides concrete application of platform engineering maturity and is an extension of a popular white paper released in April this year. The model defines platform engineering as the practice of delivering internal platforms as products that drive business results by investing in all aspects of building the platform and its capabilities, including people, processes, strategy, and technology.

Microsoft expands Azure Kubernetes service scope

Microsoft has generally rolled out Azure Kubernetes Fleet Manager to make it easier to centrally manage multiple clusters, in phases, along with a set of tools for optimizing costs.

Meanwhile, in addition to previewing an extension to the Azure Container App Platform to add support for events, Microsoft is using Kubernetes AI toolchain operators to simplify the process of deploying large language models (LLM) on Azure Kubernetes Service (AKS). It is a driver framework for training AI models, and also supports open source Qdrant, Milvus and Weaviate vector databases.

This article is published by OpenWrite, a blog that publishes multiple articles !

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