Gineesh Madapparambath

I wouldn’t have left being self-employed if I didn’t believe in what Codiac is doing. It’s not even just the product, but the people… and yeah, I know that’s cliche, however it’s the truth. After the idea of Kubernetes, there haven’t been any changes other than “trying to make Kubernetes easier”, but that doesn’t be where our idea of innovation exists. It should be in the process of thinking about the next thing… And I’m a firm believer that the “next thing” is removing the general DevOps practices that we know and focusing on value-driven work instead of putting out fires. If you have any questions about the video below, definitely let me know. #kubernetes #devops #platformengineering

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Kick-start VCF Projects Series | Ep 2 | Kubernetes In and On VCF | Supervisor Clusters in TKGs

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AI/ML Innovation in the Kubernetes Ecosystem https://ift.tt/K0bD8QI As organizations put artificial intelligence and machine learning (AI/ML) workloads into continuous development and production deployment, they need to have the same levels of manageability, speed, and accountability as regular software code. The popular way to deploy these workloads is Kubernetes, and the Kubeflow and KServe projects enable them there. Recent innovations like the Model Registry, ModelCars feature, and TrustyAI integrations in this ecosystem are delivering these improvements for users who rely on AI/ML. These, and other improvements, have made open source AI/ML ready for use in production. More improvements are coming in the future. Better Model Management AI/ML analyzes data and produces output using machine learning "models," which consist of code, data, and tuning information. In 2023, the Kubeflow community identified a key requirement to have better ways of distributing tuned models across large Kubernetes clusters. Engineers working on Red Hat's OpenShift AI agreed and started work on a new Kubeflow component, Model Registry. via DZone AI/ML Zone https://dzone.com/ai-ml October 22, 2024 at 07:00AM

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My interview for The New Stack on Kubernetes v1.32; big thanks for Joab Jackson for the enjoyable conversation and excellent article: do give it a read to learn more about the importance of achieving 100% Conformance Testing coverage, the DRA updates and what that means for workloads like AI, the release theme, and plenty more. https://lnkd.in/de4npPrf

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#Azure #APICenter For better API Governance for your organisation, this Azure API Center is a great choice! We're ready for you to have: * Azure API Center * Azure API Center Analyzer: https://lnkd.in/gdzNPckz * Azure API Center Portal: https://lnkd.in/g4iqc4Sy, and * API Center reference: https://lnkd.in/gf4ZqJ4Q Everything is `azd` friendly, so all you need to do is to run this single command: azd up Please take a look! #azure #apicenter #apicenteranalyzer #apicenterportal #apicentersample #api #governance #azd #azdevfy

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With AWS Machine Learning capabilities now easily accessible, individuals can build cutting-edge models that deliver real value with minimal effort. However, once you’ve proven a small use case, how do you scale and operationalize your models for enterprise use? To take a project from concept to production-ready, organizations need to incorporate enterprise-grade functionality—like tracking code changes, enforcing security standards, and ensuring policy and governance compliance. Using Terraform to build and manage the lifecycle of an ML/AI platform on AWS provides a scalable approach to address these requirements. Terraform can help orchestrate your infrastructure, ensuring your ML models are production-ready and enterprise-compliant. #MachineLearning #AWS #Terraform #AIOps #DevOps #CloudInnovation

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Make sure to join us for an exciting virtual event, Secure software development with Red Hat OpenShift Service on AWS April 24, 2024 | 1:00 PM - 2:00 PM ET https://lnkd.in/da728-FN OVERVIEW: Developers are frequently challenged with navigating the complexities of application development while striving to deliver exceptional business value rapidly. Red Hat® Developer Hub is designed to counter this challenge head-on. As an enterprise-grade, open developer platform tailor-made for building developer portals, it uses a supported and opinionated framework to reduce friction for engineering teams and enhance your organization's competitive advantage. In this workshop, we’ll look at the historical software development model, with all of its complexities, and translate this into a simplified, easy to use, process where development team members can be added. Instantly become useful contributors to the software architecture by leveraging the features of Red Hat Developer Hub. This workshop provides a live illustration of how the robust features of the Developer Hub translate into real-world impact, accelerating the software development process. The following topics will be discussed during the workshop. 1. GitOps The workshop will provide a first-hand experience of the seamless integration of GitOps within our operations promoting efficiency and traceability. You will witness how it amplifies productivity and accelerates development velocity on your development projects. 2. CI/CD Pipelines with Tekton The workshop dives deep into the operational efficiencies of Tekton, an open-source framework for creating CI/CD systems, illustrating how it helps to alleviate the cognitive load, allowing developers to focus on innovation and problem-solving. 3. Quay Image Registry A workshop highlight is a tour of the Red Hat Quay, our private container registry for scanning images for vulnerabilities. This continuous checking and reporting of potential security threats underscore our commitment to secure, resilient applications, workshop demonstrating the lengths we go to in safeguarding your software. 4. Golden Paths An integral part of our Red Hat Developer Hub workshop is the showcase of the 'Golden Paths.' These are tried and tested pathways, meticulously crafted to guide developers through the best practices for software deployment in our ecosystem. Golden Paths represent a template for success, providing developers with a repository template for quick startups, a foolproof pipeline for deployment, sets of manifests for application deployment, and baked-in observability capabilities. #redhat #aws #rosa #openshift #devops #developers #cloud #gitops #tekton #cicd #quay

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In the state of Kubernetes cluster management, we have to pick and choose what we want the environment to look like. This is great for engineers who want flexibility, but that flexibility isn't always wanted or needed. Sometimes, engineers just want a cluster that works with the best practices out of the box. In this video, I break down one method with AKS Automatic. https://buff.ly/4dIGh0J #kubernetes #devops #platformengineering

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In the world of Kubernetes, Node Affinity ensures your pods only run on designated nodes. Imagine a pod requiring a special GPU labeled node for processing power. Carpenter, an infrastructure management tool for AWS EKS, helps with this by automatically scaling your cluster based on these needs. This video showcases how to leverage Node Affinity with Carpenter on AWS EKS. It guides you through: 1. Setting up an EKS cluster and configuring Carpenter 2. Creating a deployment with a node affinity rule (e.g., requiring a node labeled eks:immersion-team=my-team) 3. Carpenter automatically provisioning a new node with the required label 4. Modifying the deployment to demand a different instance type. Carpenter responds by deleting the old node and creating a new one meeting the new specifications By the end, your pods are up and running on the newly created node. This video is a great resource for anyone using Kubernetes on AWS EKS, especially if you're looking to streamline pod placement and cluster scaling using Node Affinity and Carpenter.     #Kubernetes #EKS #NodeAffinity #Carpenter #CloudNative #Carpenter   https://lnkd.in/eehZh_C7

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🚀 New Article Alert! 🚀 Want to understand YAML in a simple and easy-to-digest way? 🤔 In my latest article, I break down what YAML is, why it's used, and where you can find it with some fun analogies to make it super clear! From Kubernetes configurations to Docker and CI/CD pipelines, YAML is everywhere — and it’s much easier to work with than you might think! Check out the full article and get a solid grasp of this powerful, human-readable data format! 📄 #YAML #DevOps #Kubernetes #Docker #ConfigurationFiles #TechSimplified #LearningTogether #DeveloperLife

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Kubernetes v1.32: a sneak peak into the removals, deprecations, and new features that we can expect to have come December. Thanks to Matteo Bianchi (Release Comms Lead) and the Release Comms team in particular for bringing us this glimpse into what the Kubernetes v1.32 has in store. The changes in DRA (Dynamic Resource Allocation) are interesting, not the least because they show the dynamic nature of the Kubernetes enhancements lifecycle: initial ways to do things can get replaced by other approaches that better fit the requirements. We're on week 9 of 14 weeks that make up the v1.32 release cycle. https://lnkd.in/d_dNdc6U

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𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐯1.30 𝐢𝐬 𝐡𝐞𝐫𝐞 ~ 𝐔𝐰𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 😺 ☸ The release brings 45 enhancements, out of which 17 graduated to Stable, 18 entering to Beta and 10 graduated to Alpha Interesting features to look out for: ✅ Memory Swap Support (#2400) ✍ Improves system stability by modifying swap memory behavior on Linux nodes to better manage memory usage and system performance, thereby preventing unprecedented crashes ✅ Robust VolumeManager reconstruction after kubelet restart (#3756) ✍ Addresses the issues with kubelet’s handling of mounted volumes after a restart, where it currently loses track of volumes for running Pods and attempts to reconstruct this state from the API server and the host OS – a process known to be flawed.  ✅ Prevent unauthorized volume mode conversion during volume restore (#3141) ✍ Addresses a potential security gap in #Kubernetes VolumeSnapshot feature by introducing safeguards against unauthorized changes in volume mode during the creation of a PersistentVolumeClaim (PVC) from a VolumeSnapshot ✅ Container Resource based Pod Autoscaling (#1610) ✍ Accesses Horizontal Pod Autoscaler’s (HPA) functionality, specifically allowing it to scale resources based on the usage metrics of individual containers within a pod ✅ Metric cardinality enforcement (#2305) ✍ This enhancement addresses the issue of unbounded metric dimensions causing memory problems in instrumented components by introducing a dynamic, runtime-configurable allowlist for metric label values ✅ Interactive flag added to kubectl delete command (#3895) ✍ Introducing an interactive mode (-i) for the kubectl delete command to enhance safety measures for cluster administrators against accidental deletions of critical resources More such enhancements & updates are listed here https://lnkd.in/ga2wk4zd #cncf #paas #cloudnative #k8s #release #devops #devsecops #platform #solutionengineer #sysadmin #developer

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One pod in Kubernetes calling another pod via a service DNS is a non-cloud native approach. It's basically Kubernetes supporting apps that isn't cloud native by serving a legacy way of doing it. The problem is, nobody stopped using the legacy way and became cloud native. People are stuck in legacy. This is something i made a video about many years ago but it never got published as to many people got confused. Everyone who saw the video said it was wrong until i explained why it wasn't. It could be my video wasn't good enough at explaining it, but i think this is still a problem today where people think if you run stuff in Kubernetes et automatically becomes cloud native. The kubernetes project describes in their documentation what they mean by cloud native approaches and non cloud native approaches on this exact topic. And if you have ever made your own operator your know why the above is not cloud native, and what is. https://lnkd.in/e9KJPpmg

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Today, let's look at how to use External Secrets Operator in OpenShift to synchronize the secrets from AWS Secrets Manager! https://lnkd.in/gfMqPTZn #externalsecretsoperator #openshift #cloudnative #devops

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Containerization is a powerful tool for managing workloads. However, not all workloads are suitable for containerization. In this tech talk I cover out how to handle virtualized workloads that don’t make sense to containerize while leveraging the robust self-healing capabilities of Kubernetes.

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