🛠️ 2025-10-26 Tech Update Summary

🔹 Kubernetes - 7 Common Kubernetes Pitfalls (and How I Learned to Avoid Them)

The blog post “7 Common Kubernetes Pitfalls (and How I Learned to Avoid Them)” highlights common mistakes users make when managing Kubernetes clusters and provides tips to avoid them. The author shares personal experiences and solutions for each pitfall. Key pitfalls include:

  1. Skipping Resource Requests and Limits: Not setting CPU and memory requirements can lead to resource starvation or hoarding. It’s advised to start with modest settings and adjust based on real-world usage.

  2. Underestimating Liveness and Readiness Probes: Failing to define health checks for containers can cause issues with unresponsive applications. Simple HTTP probes can help Kubernetes manage container restarts and traffic routing effectively.

  3. Relying Solely on Container Logs: Using only kubectl logs for troubleshooting is unreliable. Centralizing logs with tools like Fluentd and adopting OpenTelemetry for comprehensive monitoring is recommended.

  4. Treating Development and Production Environments the Same: Using identical configurations across environments can lead to performance and security issues. Utilizing overlays and customizing settings for each environment can prevent this.

  5. Leaving Old Resources in the Cluster: Unused resources can accumulate, wasting resources and increasing costs. Regular audits and automated policies can help manage cluster resources efficiently.

  6. Diving Too Deep into Networking Too Soon: Implementing advanced networking without understanding Kubernetes basics can complicate troubleshooting. Start with simple configurations and gradually adopt more complex solutions as needed.

  7. Neglecting Security and RBAC: Insecure configurations and broad permissions can expose clusters to risks. Utilizing RBAC for permissions, pinning image versions, and enforcing security contexts can enhance security.

The post emphasizes learning from mistakes and leveraging Kubernetes documentation and community resources to improve cluster management. 👉 Read more

🔹 Spring Boot - Spring Shell 4.0.0-M1 is available!

The blog post announces the release of Spring Shell 4.0.0-M1, the first milestone of Spring Shell 4.0, now available on Maven Central. This release marks the beginning of a modern version of Spring Shell, aligning it with Spring Framework 7 and Spring Boot 4. It is based on Spring Framework 7.0.0-RC2 and Spring Boot 4.0.0-RC1. The post also outlines future plans, including the release of Spring Shell 4.0 GA in November following Spring Boot 4.0 GA. Upcoming changes include migrating to jSpecify for nullability annotations, improving project modularity, updating test infrastructure to JUnit 6, enhancing build and release infrastructure, and improving documentation. The post invites feedback via GitHub Issues and Discussions and acknowledges contributors to the release. Links for further information and resources are provided. 👉 Read more

🔹 Docker - Docker Hub Incident Report – October 20, 2025

The blog post discusses a major disruption experienced by Docker due to a widespread outage in AWS’s US-East-1 region on October 20, 2025. This incident significantly impacted developers globally who depend on Docker for their daily workflows. The post aims to provide transparency about the event, detailing what occurred, the lessons learned, and the measures Docker is implementing to enhance their systems and prevent future occurrences. 👉 Read more

🔹 Java - Writing GPU-Ready AI Models in Pure Java with Babylon

The blog post discusses Project Babylon, which allows developers to create and execute AI models like LLMs and image classifiers directly in Java. By using Code Reflection, developers can define machine learning logic in Java without relying on Python or external model files. Babylon utilizes the Foreign Function and Memory (FFM) API to connect Java code to native runtimes like ONNX, enabling fast, GPU-accelerated inference. It also introduces the Heterogeneous Accelerator Toolkit (HAT) for writing and composing compute kernels in Java, allowing Java libraries to leverage GPU power for high-performance computing. The session highlights Babylon’s new features and demonstrates how to integrate AI capabilities into the Java ecosystem, appealing to library maintainers and developers interested in adding AI to their Java applications. 👉 Read more

🔹 Golang - Flight Recorder in Go 1.25

The blog post discusses the introduction of a new feature in Go 1.25 called “flight recording.” This tool enhances the diagnostic capabilities of the Go programming language. Flight recording allows developers to capture and analyze execution traces, which can help in identifying and understanding issues in Go applications. It provides a comprehensive view of the program’s behavior over time, making it easier to diagnose performance problems and bugs. The post likely goes into detail about how to use the flight recorder and its benefits for Go developers. 👉 Read more

🔹 Helm - Helm Turns 10

The blog post titled “Helm Turns 10” celebrates the tenth anniversary of Helm, a package manager for Kubernetes. Helm was created during a hackathon shortly after the release of Kubernetes 1.1.0. The first commit for Helm, authored by Matt Butcher, was made on October 19, 2015. This initial version, known as Helm v1, is preserved in the helm-classic Git repository. Helm later merged with Deployment Manager and became part of the Kubernetes project, marking its evolution over the years. 👉 Read more