Prasanth E.

Introducing Amazon MSK Replicator – Fully Managed Replication across MSK Clusters in Same or Different AWS Regions https://lnkd.in/eMAdqxYG #aws #cloudcomputing #cloud #devops #azure #technology #python #awscloud #cybersecurity #amazonwebservices #linux #coding #software #kubernetes #datascience #developer #tech #java #programming #bigdata #amazon #googlecloud #microsoft #it #docker #machinelearning #javascript #security #devopsengineer #gcp

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Want to explore the potential of Java 22's Foreign Function and Memory API? Check out Per-Åke Minborg's session and delve into how the API enhances native methods and memory access, maintaining high performance and safety. View talk @ devoxx.co.uk/talk?id=4967

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#Z-audit.com-(topic)- CICS transactions secured by RACF In this topic I describe how you can secure CICS transactions by an ESM External Security Manager (RACF). It's a good couple.

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💡 Boosting Application Reliability with the “minReadySeconds” Parameter (Kubernetes) 💡 . Beyond the standard container probing parameters: . 📍startupProbe: Determines when to initiate readiness and liveness probes 📍livenessProbe: Checks if a Pod is still functioning correctly and if it should be restarted 📍readinessProbe: Verifies if a Pod is ready to receive requests and serve traffic Or 📍PreStop hook: This allows you to specify a command or action to be executed before a Pod is terminated. It's often used to introduce a pause or sleep period, enabling other processes, such as updating endpoint configurations (like iptables), to complete before the Pod is shut down 📍terminationGracePeriodSeconds: This parameter sets a time window (in seconds) after which a SIGKILL signal will be sent to forcefully terminate a Pod if it hasn't already terminated gracefully after receiving the initial SIGTERM signal . These parameters contribute to application uptime and facilitate zero-downtime deployments during rolling updates involving image changes or resource setting modifications . Another valuable parameter for enhancing application reliability is 💡minReadySeconds💡 (.spec.minReadySeconds) . What is minReadySeconds? This parameter defines the minimum time (in seconds) a Pod must remain in the "Ready" state (after successfully passing its readinessProbe) before it is considered fully operational and eligible to receive traffic . ℹ️ The `minReadySeconds` value can be specified within various Kubernetes resources, including Deployments, DaemonSets, and StatefulSets ℹ️ The default value for `minReadySeconds` is 0. This means that as soon as a newly created Pod transitions to the "Ready" state, the older Pod will immediately begin its termination process . ℹ️ Use Case: In certain scenarios, merely passing the readinessProbe might not be sufficient for an application to be considered fully prepared. Some applications, such as those built with Java, might require a warm-up period before handling the full traffic load. This is where `minReadySeconds` proves beneficial . For further insights into Kubernetes best practices, you can refer to: https://lnkd.in/gi4WCTdS #kubernetes #reliability #minReadySeconds

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I've never seen micro-service architecture work in a corporate dev shop precisely because of these reasons. In fact, I am now actively hostile to its implementation in such environments... it just never works out well for the business, or the boots on the ground. We should call this "Micro-service fallacies" much like distributed networking. 😂 Especially points 2, 4, 5, and 6.

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In simpler terms 🤔

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A new Kubernetes Enhancement Proposal (KEP) suggests modifying how the platform handles container crash recovery. The current system uses fixed exponential backoff timings, starting at 10 seconds and maxing at 5 minutes. The proposed changes would reduce the initial backoff to 1 second with a 1-minute cap and introduce node-level configuration options. I've struggled with the current rigid backoff settings when trying to rapidly recover workloads, so making this configurable is a welcome change. That said, the dramatic CPU impact means this will need careful consideration before enabling in production environments. #k8s, #kubernetes https://lnkd.in/gqFwgu-p

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🚀Another one of my OSS contributions to #vscode 𝑣𝑠𝑐𝑜𝑑𝑒-𝑠𝑝𝑟𝑖𝑛𝑔-𝑏𝑜𝑜𝑡-𝑑𝑎𝑠ℎ𝑏𝑜𝑎𝑟𝑑 is released as part of 𝐯𝟎.𝟏𝟒.𝟎. Took a while to get it merged as we waited for right STS API and implementation. 🔍 𝐖𝐡𝐚𝐭’𝐬 𝐍𝐞𝐰? The feature I proposed and implemented now displays the profile(s) on which a Spring Boot application was started directly in the Spring Boot Dashboard section. 🙌 𝐀𝐜𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐦𝐞𝐧𝐭𝐬 A huge shoutout to the amazing #VSCode community and the #Microsoft team for their support and collaboration and Alex Boyko for prioritizing the feature/PR. 🔗 𝐂𝐡𝐞𝐜𝐤 𝐈𝐭 𝐎𝐮𝐭 If you haven’t already, grab the latest version of the extension from the VS Code Marketplace and give it a try. Let me know what you think! 😇 𝘩𝘵𝘵𝘱𝘴://𝘨𝘪𝘵𝘩𝘶𝘣.𝘤𝘰𝘮/𝘮𝘪𝘤𝘳𝘰𝘴𝘰𝘧𝘵/𝘷𝘴𝘤𝘰𝘥𝘦-𝘴𝘱𝘳𝘪𝘯𝘨-𝘣𝘰𝘰𝘵-𝘥𝘢𝘴𝘩𝘣𝘰𝘢𝘳𝘥 #vscode #microsoft #java #sts #springboot

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I always play around with ChatGPT to see its thoughts on things and see what it will output. Yesterday it made mistakes on Nginx configuration rules and today it made mistakes on something basic. Last week, it made mistakes in SQL. I can say this, ChatGPT won't replace humans 😜 #chatgpt #bots #ai #technology #coding

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All the Jenkins guides published so far have been organized into a course format. To follow this course, you’ll need a working Kubernetes cluster. We’ve chosen to set up the Jenkins controller and agent in Kubernetes because, in most projects, Jenkins is typically deployed within Kubernetes. This approach ensures you gain hands-on experience running Jenkins in a Kubernetes environment. All the guides in this course are based on real-world project implementations, drawing from our team's experience managing Jenkins in production environments over many years. 𝗖𝗼𝘂𝗿𝘀𝗲 𝗟𝗶𝗻𝗸: https://lnkd.in/gfDwHc7C Everyday one lesson will be added to the course. Tomorrow we will look at pipeline as code tutorial for beginners. ♻️ Dont forget to repost! and share it with the DevOps learning community Have any questions? Discuss in the comments #devops #jenkins #devopsengineer

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Executable (computational) graphs and diagrams in Java I've been using executable/computational graphs to manage complexity for quite a while, including graphs created from Drawio diagrams. This Medium story https://lnkd.in/dfs5e9A9 provides a high-level overview of the approach with links to detailed documentation and code. In my opinion, there are many applications for graphs in the enterprise. They can be used to "connect the dots" between different systems and build a holistic model of how an organization operates.

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AWS Graviton Weekly # 100 https://lnkd.in/egmDqZnb Highlights of the week: ​🗞️ Announcing general availability of Amazon EC2 G6e instances​ ​🗞️ Announcing Karpenter 1.0​ ​🗞️ AWS Batch adds support for cancelling queued jobs​ ​🗞️ New capabilities for Amazon EC2 On-Demand Capacity Reservations: Split, Move, and Modify additional attributes​ ​ ⛏️ How AWS powered Prime Day 2024 for record-breaking sales, by Channy Yun (윤석찬) ​⛏️ 8 Tips for Amazon EKS Cost Optimization In 2024, by CAST AI​ ⛏️ ​Build a serverless data quality pipeline using Deequ on AWS Lambda, by Vivek Mittal, John Cherian, and Uma Ramadoss ​⛏️ ​Unlock Faster Machine Learning with Graviton, by Ying Chen, Lu Wang and Lin Yuan​ ​ ​⛏️ ​AWS: «Los DC con su escalabilidad y su modelo de pago por uso, se han convertido en socios estratégicos para las Startups»​ ​​⛏️ ​Why Gencove uses Graviton for most of their work - it's all about the science​ ​​⛏️ ​Understanding AWS Data Transfer Pricing, by Visak Krishnakumar (CloudOptimo) ​ ​⛏️ ​Prisma Cloud Partners To Secure AWS Graviton Arm-Based Compute Instances, by Derek Rogerson (Palo Alto Networks) ​​⛏️ ​Breaking Technology Barriers, by Sanjay Kodali and Lee Dongwoo (Samsung Electronics) ​​⛏️ ​​Formal verification makes RSA faster — and faster to deploy, by ​Juneyoung Lee, Hanno Becker, and John Harrison ​​​⛏️ ​How we migrated onto K8s in less than 12 months, by Ian VonSeggern (Figma)​ ​​⛏️ Stocks notification: Building multi-arch docker image, by Yap, Han Chiang 叶汉强​ ​​​⛏️ CloudFix AI Chrome Extension 🎙️ Optimize workloads with Databricks Photon and AWS Graviton, by Renji Luke Harold (Databricks) and Ahmed Nada ​🎙️ ​Under the Hood w/ AWS: Creating Multi-Architecture Container Images to support Graviton, by Art Baudo and Nati Cohen ​🎙️ ​Machine Learning Inference Model at Scale with Graviton, by Lorenzo Winfrey (AWS) and Hermant Javeri (2bcloud) #aws #kubernetes #finops

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OpenShift and Kubernetes are today's most widely used container orchestration software options. How do they compare? Watch this video for an in-depth look at their similarities, differences and which is right for your projects. Red Hat

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🚀 Unlock the Full Potential of Terraform! 🚀 Terraform is a game-changer for managing infrastructure as code, but as your usage scales, so does the complexity of your modules. To ensure seamless solutions for our clients, we wanted to highlight a few key strategies: 💡 Simplify by grouping variables into objects 💡 Embrace reusable modules by using local values 💡 Prioritize maintainability by validating your modules Want to dive deeper into these best practices? Check out our latest blog post by Ely Erin Haughie! https://lnkd.in/erC9P2rY #Rearc #Terraform #InfrastructureAsCode

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Kubernetes Janitor processes all namespaces and all namespaced resources, including custom resource definitions, and deletes them if: - A TTL rule indicates the resource as expired. - The janitor/expires annotation marks the resource as expired. More: https://lnkd.in/g_KvQN7t

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Navigating uncertainty and complexity is key in innovation. Discover the surprising parallels between Kafka's 'The Trial' and modern innovation practices in our latest blog post! https://lnkd.in/eTxSbKTi

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