CI

OpenAI & Broadcom Announce Landmark 10GW Custom AI Accelerator Partnership OpenAI and Broadcom have announced a strategic multi-year collaboration to develop and deploy 10 gigawatts of custom AI accelerators. Under this partnership, OpenAI will lead the design of the AI accelerators and systems, while Broadcom will be responsible for their development and deployment. This collaboration will also involve the co-development of systems incorporating Broadcom’s Ethernet and other connectivity solutions to enhance the scalability of next-generation AI clusters. The deployment of these AI accelerator and network system racks is scheduled to commence in the latter half of 2026, with a target completion by the end of 2029. Sam Altman, CEO of OpenAI, stated that this partnership is a crucial step in building the necessary infrastructure to unlock the full potential of AI. ...

Anthropic Unveils Claude Sonnet 4.5 with Advanced Reasoning and Coding Anthropic has officially released its latest large language model, Claude Sonnet 4.5, featuring significant improvements in processing long contexts and performing complex mathematical and logical reasoning tasks. The company claims the model can perform tasks autonomously for over 30 hours and has demonstrated state-of-the-art performance on the SWE-bench Verified evaluation for software coding. Alongside the new model, Anthropic launched Claude Code 2.0, an integrated coding environment for developers with an enhanced UI and performance based on Sonnet 4.5. To facilitate the development of AI agents, the company has also released the Claude Agent SDK. The new model is now available through Anthropic’s API, the Claude app, Amazon Bedrock, and Google Cloud’s Vertex AI. ...

Using AWS Lambda has become very popular. Most of the time using it is fast and just (but not always). When you start having a lot of lambda functions the complexity of managing them can be hard. When a developer can just edit the code inline, it can become the worse manage service use ever chose. So again, the most important thing to do when you start working with Lambda is to have a proper way to deliver the code from git to aws. ...

Docker has become the preferable way and the most easy way to run continuous integration, due to its reproducible nature and fast learning curve. There are multiple ways approaching CI processes using docker. Using docker build, which is the easiest way FROM node:12 ARG NODE_ENV=production COPY . /src RUN npm install WORKDIR /src CMD [ "node", "app.js" ] Using docker multi step build, this usually helps making the final image smaller and safer without all the build binaries FROM maven AS Builder COPY . /src RUN [ "mvn" , "clean" , "install" ] FROM openjdk:12-alpine WORKDIR /srv COPY --from=Builder /src/target ./srv/ CMD [ "java", "-jar", "app.jar" ] Using docker run with a pre-built build image on a volume mount this allows having cache directories and have some more functionality during the build, and will allow multiple commands docker run -v `$pwd`:/src -v `~/.m2`:/root/.m2 maven mvn clean install Using docker in docker, like gitlab, bitbucket etc… This method is more complex than the rest and require you to mount docker socket to the as a volume to the docker container, and can be preformed in 2 ways: There is an official docker in docker image by docker inc that is tagged as docker:dind ...

Overview In this post, I am going to describe how to maintain access to Amazon AWS EKS - Kubernetes cluster with only attaching an IAM Role as an instance profile, without configuring access keys on the EC2 instance. The benefit of course is not storing any Amazon IAM credentials on the EC2 instance, having your infrastructure more secure. Use Case: Jenkins CI/CD Pipeline In my use case, I wanted to have my Jenkins CI server have access to EKS cluster for adding continuous delivery using Jenkins declarative pipeline to my continuous integration process. By doing that, I achieved a full CI/CD process for all the microservices that Jenkins handled. ...