You can keep documentation hosted and structured in a platform like DeveloperHub, enable two-way Git sync, and let tools like DeepDocs handle continuous maintenance in the repository. Writers stay in control of clarity and structure, while automation ensures nothing quietly goes stale. - Source: dev.to / 8 months ago

Keep your documentation alive and in sync with your codebase. DeepDocs works seamlessly with GitHub to automatically detect changes, update API references, tutorials, and READMEs, and submit intelligent pull requests. Combine it with Gemini 3 or Google Antigravity to maintain interactive, accurate docs that evolve alongside your project so your code and documentation are always aligned. - Source: dev.to / 9 months ago

Deepdocs focuses on one thing: turning messy, outdated engineering knowledge into clean, accurate documentation  automatically. Instead of relying on developers to write or update docs (which never happens on time), Deepdocs reads your codebase, analyzes your structure, and generates documentation that updates itself as the product evolves. - Source: dev.to / 9 months ago

DeepDocs – A smart documentation automation tool that keeps everything perfectly in sync with the codebase. It automatically updates my READMEs, SDK guides, and tutorials whenever the code changes, ensuring documentation never goes stale. This saves time, reduces manual updates, and guarantees that developers always have accurate, up-to-date references. - Source: dev.to / 10 months ago

DeepDocs is the “AI doc reviewer” you didn’t know you needed. It automatically detects outdated comments, docs, or READMEs when your code changes  then updates them automatically. - Source: dev.to / 11 months ago

On managed Kubernetes platforms like EKS, this has a second benefit: the cluster autoscaler pays attention to resource requests when deciding whether to add new nodes. - Source: dev.to / 3 months ago

After returning from AWS Summit London 2026 I was doing some research on running AI/ML workload in AWS EKS with Karpenter. With some assistance from Gemini I turned some of my notes from various talks into this guide that will talk through the intricacies of deploying and scaling Generative AI (GenAI) workloads on AWS EKS, leveraging the power of Karpenter. - Source: dev.to / 3 months ago

This post is a small step in that direction: serving an LLM using vLLM, deployed on Amazon EKS, provisioned the infra using AWS CDK, and wrapped into a simple chatbot using Streamlit. - Source: dev.to / 4 months ago

In this post, I'll walk you through setting up observability for Spring Boot applications on Amazon EKS - starting with the basics (logs and metrics), diving into distributed tracing, and finishing with Application Signals. Hopefully this saves you some time. - Source: dev.to / 7 months ago

Running Apache Spark on Kubernetes with AWS EMR on EKS brings big benefits – you get the best of both worlds. AWS EMR's optimized Spark runtime and AWS EKS's container orchestration come together in one managed platform. Sure, you could run Spark on Kubernetes yourself, but it's a lot of manual work. You'd need to create a custom container image, set up networking, and handle a bunch of other configurations. But... - Source: dev.to / 9 months ago