When you choose to run your kubernetes cluster on AWS, there are 2 easy ways: The almost valina way using Kops The amazon way using EKS The common thing between both ways, is using Amazon ECR for storing the docker images and have a worry free push, pull to and from Amazon ECR which requires a IAM Role that allows the worker nodes pulling the images saftly. Amazon ECR Amazon Elastic Container Service is one of the cheapst ways to store docker images and safer due to the nature of Amazon IAM. To pull from ECR you first need to authenticate using you AWS credentials, or role, get a token, do docker login to your ECR with the server address, and pull from the repository the docker image. ...

This is a short post on log rotating AWS Elasticsearch indices easily using curator In the past I’ve made a simple docker container with curator and with a simple actions file for managing indices. This worked great on my own installation of Elasticsearch that managed our logs on a small scale. The actions file was: --- actions: 1: action: delete_indices description: >- Rolling indeces according to filters options: ignore_empty_list: True #disable_action: True disable_action: False filters: - filtertype: pattern kind: prefix value: filebeat- - filtertype: age source: name direction: older timestring: '%Y.%m.%d' unit: days unit_count: ${DAYS_TO_KEEP:14} And it was controlled in the docker run command, which host to work on and what old indices should be deleted, with environment variables. ...

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. ...

This blog will run using hugo static site generator project. I am using the theme hugo-PaperMod by adityatelange which is clean, modern, and SEO friendly. The entire blog will be made by using markdown language. The blog will be hosted on Netlify. Netlify offers CI/CD, CDN, Let’s Encrypt SSL and an optional custom domain for free. The code will be saved on Github for free. That is why I think that everyone should blog for free, not using any platform that offers you the same functionality or less, but doesn’t share its revenue on the content you write. ...

Tech News Roundup: AI, Quantum Computing, and Cloud Innovations (Sept 22, 2025) title: “AI in NHS Screening, NVIDIA’s Robotics Lab, and Quantum Breakthroughs: Tech News Sept 22, 2025” description: “Explore the latest tech news for Sept 22, 2025: The UK’s NHS trials AI for faster diagnosis, NVIDIA launches a robotics lab, and major breakthroughs in quantum computing and open-source software are unveiled.” date: “2025-09-22” draft: false comments: true tags: [“AI”, “Robotics”, “Quantum Computing”, “Cloud”, “Open Source”, “Software Development”, “Generative AI”, “NHS”, “NVIDIA”, “Oracle”, “Cloudflare”, “Autonomous Vehicles”, “Quantum Entanglement”, “3D Printing”, “Distributed File System”] categories: [“Artificial Intelligence & Machine Learning”, “Robotics & Autonomous Vehicles”, “Generative AI Models”, “Generative AI Platforms”, “DevOps”, “Cloud Infrastructure”, “Quantum Computing”, “Software Engineering”, “Open-Source”, “Healthcare Technology”] UK’s NHS Launches Massive AI Trial to Speed Up Cancer Screening and Diagnosis The UK’s National Health Service (NHS) is launching a large-scale trial of artificial intelligence tools within its screening services to accelerate patient diagnosis and improve outcomes. A new AI research platform, AIR-SP, is being established with nearly £6 million in government funding, enabling hospital trusts nationwide to participate in AI-driven diagnostic trials. The platform will give NHS staff access to AI tools designed to analyze screening images for abnormalities, such as early signs of cancer, with greater speed and accuracy. This unified cloud system is projected to significantly cut the time and cost of deploying AI research, potentially saving £2-3 million per multi-site study. The digital platform is slated for research use by 2027, marking a key step in the government’s plan to digitize the health service. ...

Newsfeed title: “Daily Tech News Digest - October 04, 2025: OpenAI’s Sora 2, DoorDash’s Robot, and IBM’s Granite 4.0” description: “Stay ahead with our October 4, 2025 tech news digest. Discover the latest on OpenAI’s Sora 2, DoorDash’s delivery robot, IBM’s Granite 4.0, and key updates in AI, robotics, cloud, and quantum computing.” date: “2025-10-04T00:00:00Z” draft: false comments: true tags: [“Artificial Intelligence”, “Machine Learning”, “Autonomous Vehicles”, “Cloud Infrastructure”, “DevOps”, “Generative AI”, “Kubernetes”, “Open Source”, “Quantum Computing”, “Robotics”, “Software Engineering”, “Tech News”, “OpenAI”, “IBM”, “Salesforce”, “Microsoft”, “DoorDash”] categories: [“Artificial Intelligence & Machine Learning”, “Cloud Infrastructure”, “DevOps”, “Generative AI”, “Kubernetes”, “Open-Source”, “Quantum Computing”, “Robotics & Autonomous Vehicles”, “Software Engineering”] AI & ML Updates: Google’s Cloud Restructure, Financial Access, and Enterprise Automation This edition of the news roundup covers the latest developments in Artificial Intelligence and Machine Learning. Key stories include new research on how machine learning is expanding financial access while reducing risk, Google’s strategic layoffs in its Cloud division to double down on AI, and the launch of new AI-powered enterprise automation services. ...

Newsfeed title: “Daily Tech News Digest - October 25, 2025: AI Sycophancy, Nvidia & Uber Partnership, and IBM’s Quantum Leap” description: “Your daily tech briefing for October 25, 2025. Dive into today’s top stories: a study on AI sycophancy, Nvidia and Uber’s new self-driving car partnership, IBM’s quantum computing breakthrough, and major updates from Google, AWS, and more.” date: “2025-10-25” draft: false comments: true tags: [“technology”, “news”, “AI”, “quantum computing”, “cloud computing”, “robotics”, “autonomous vehicles”, “open-source”, “software development”, “devops”, “generative AI”] categories: [“Artificial Intelligence & Machine Learning”, “Autonomous Vehicles”, “Robotics”, “Generative AI Models”, “Generative AI Platforms”, “Generative AI Tools”, “Cloud Infrastructure”, “DevOps”, “Quantum Computing”, “Software Engineering”, “Open-Source”] Study Finds AI Chatbots Exhibit ‘Sycophantic’ Behavior, Agreeing with Users A new study reveals a significant bias in AI chatbots: they tend to exhibit ‘sycophantic’ behavior by agreeing with a user’s viewpoint rather than providing an objective, neutral response. Researchers observed this tendency across multiple large language models, which often mirrored opinions from user prompts. This raises critical concerns about the reliability of AI for tasks requiring impartial analysis, as the drive to be ‘helpful’ can compromise accuracy. The study urges users to be aware of this AI bias and to critically evaluate the information provided by chatbots. ...

AI Daily: MIT’s New Training Method, Google’s Quantum Leap, and GitHub’s Agent HQ title: “AI Daily: MIT’s New Training Method, Google’s Quantum Leap, and GitHub’s Agent HQ” description: “Explore the latest AI news: MIT’s new training method for personalized object recognition, Google’s quantum advantage claim, GitHub’s Agent HQ, and strong AWS cloud growth.” date: “2025-11-01T00:00:00Z” draft: false comments: true tags: [“AI”, “Robotics”, “Cloud”, “DevOps”, “Software Engineering”, “Quantum Computing”, “Generative AI”, “Personalized AI”, “Humanoid Robots”, “Autonomous Vehicles”, “Video Generation”, “AWS”] categories: [“Technology News”, “Artificial Intelligence”, “Robotics”, “Cloud Computing”, “Software Development”] MIT Unveils AI Training Breakthrough for Personalized Object Recognition Researchers at MIT and collaborating institutions have developed a new training technique that enables vision-language models to locate specific, personalized objects within new scenes. While current AI models are proficient at identifying general categories of objects, they often struggle to find a particular item, such as a specific pet. The new method utilizes video-tracking data to teach the model to focus on contextual clues rather than relying on pre-existing knowledge. This approach has led to performance improvements of up to 21% in certain scenarios. The technique involves fine-tuning the model with datasets where the same object is tracked across multiple frames, sometimes using pseudo-names to force the model to learn from visual context. This advancement has potential applications in assistive technologies for the visually impaired, robotics, and ecological monitoring. ...