Labs64.IO Ecosystem Diary

An auth proxy is a specialized service that centralizes authentication and authorization for multiple microservices. Instead of implementing security logic in every service, you can use a single proxy to handle these concerns at the edge. The Traefik Auth Proxy is a great example of this pattern, using Traefik’s forwardAuth middleware to intercept requests and enforce access policies.

Traefik is a powerful cloud-native ingress controller that uses Middleware to modify requests before they’re sent to your services. Middleware can handle crucial tasks like authentication, rate limiting, and header manipulation. By using Helm charts to manage your Traefik configuration, you gain a declarative, version-controlled, and reusable approach that’s perfect for a microservice environment.

Spring Cloud Gateway is a powerful API gateway that efficiently routes incoming traffic to the appropriate downstream microservices. At its core, this functionality relies on routes, which are the fundamental building blocks that define how requests are handled. Understanding how to configure these routes is essential for building a robust and scalable microservice architecture.

When deploying applications on Kubernetes, simply having a container run isn’t enough. For true reliability, you need to make sure your application is both healthy and ready to handle requests. This is where liveness probes and readiness probes come in. These simple health checks are performed by the Kubelet to manage your container’s lifecycle and ensure your service stays available.

Rate limiting is a critical strategy for protecting your backend services from abuse, ensuring fair resource usage, and preventing cascading failures from sudden traffic spikes. Spring Cloud Gateway provides a powerful and flexible way to implement this with its RequestRateLimiter filter. This filter uses a token bucket algorithm to control traffic, making it an excellent choice for a variety of use cases.

In the dynamic and often complex world of Kubernetes, effectively monitoring the resource utilization of your pods is crucial for maintaining application performance, optimizing resource allocation, and troubleshooting issues. While Kubernetes offers powerful orchestration capabilities, gaining insight into CPU and memory usage at the pod level isn’t inherently built into the core API. This is where metrics-server steps in as an indispensable component, providing the necessary data for a comprehensive observability strategy.

For Kubernetes deployments, Helm charts have become the de-facto standard for packaging and deploying applications. As our ecosystem of services grows, so does the complexity of managing their configurations. We’ve recently made a significant architectural shift in how we manage Helm chart overrides, moving them from nested within individual charts to a dedicated, higher-level overrides directory. This article explains the “why” behind this change and how it benefits our development workflow.

As developers working with Kubernetes, Helm charts are indispensable for packaging and deploying applications. However, maintaining up-to-date documentation and ensuring valid values.yaml files can be a tedious and error-prone process. This article introduces two powerful tools that can automate these tasks, making your Helm chart development more efficient and developer-friendly: helm-docs for documentation generation and helm schema for JSON schema generation and validation.

The labs64.io-helm-charts repository is a curated collection of Helm charts aimed at deploying Labs64.IO microservices and their supporting infrastructure. Built with modularity, maintainability, and DevOps automation in mind, it offers a reusable, scalable Kubernetes deployment system for both internal and third-party applications.

This cheatsheet provides a quick reference for common Kubernetes commands, concepts, and YAML configurations. It’s designed to help developers navigate their local and remote Kubernetes clusters efficiently.

Kubernetes has become the de facto standard for deploying, scaling, and managing containerized applications. While often associated with large-scale cloud deployments, having a local Kubernetes setup is invaluable for developers. It allows you to test your applications in a production-like environment, experiment with K8s features, and streamline your development workflow without incurring cloud costs.

Welcome to the Labs64.IO developer community! Our platform is built on a robust microservices architecture, leveraging specific tech stacks for both application development and deployment. Understanding this structure from a technology perspective will empower you to quickly find your way around and contribute effectively.

As developers, we all have those small scripts we write to automate common tasks: build.sh, run_tests.cmd, deploy.sh, and so on. They live in our project’s root, and while they get the job done, they can become a collection of scattered, undocumented, and sometimes platform-specific commands.

Alright, let’s talk about the initial architecture for Labs64.IO Ecosystem! Think of this as the foundational blueprint for our amazing new ecosystem. We’ve designed it to be robust, scalable, and easy for us developers to work with.

Alright, let’s talk about the Labs64.IO Ecosystem from a dev and DevOps perspective. This is where the rubber meets the road, where the code gets written, tested, and deployed, and where all that “agility” and “scalability” truly come to life.

Hello, developers, innovators, and ecosystems enthusiasts! We’re incredibly excited to lift the curtain on something we’ve been passionately building: the Labs64.IO Ecosystem. This isn’t just another platform; it’s a meticulously crafted suite of interconnected microservices designed to be your ultimate powerhouse for agile business workflow automation.