Bhavuk Bhardwaj

✨ Engineering, specially deploying and managing applications at scale is a very big challenging task. 🤔 Managed Kubernetes - EKS, AKS and GKE only solves half of the problem of managing the control plane of Kubernetes. It's still the work of your Devops / SRE / Backend engineers to do all these - - Upgrade K8s and node versions frequently - Build, manage, update Helm Charts as needed - Maintain and monitor your application status, debug any node/infra/network failures - Build and maintain a full logging, monitoring stack Devops is costly, either hire experienced devops engineers, or make your backend engineers learn all this (developer time cost) 💰💰

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Kubernetes Bin Packing ⚡ First lest understand what is bin packing. In simple terms, bin packing is a way of arranging items so that you use the least number of containers (or bins) possible. Imagine you have a bunch of items of different sizes and you need to pack them into boxes. Bin packing is about figuring out the best way to put those items into the boxes so that you use as few boxes as possible. In Kubernetes, bin packing works similarly but with resources. It means trying to use the available resources on each server or node as efficiently as possible, packing as many workloads as you can onto each node to minimize the number of nodes needed. In today blog, we will look at the following. 𝗡𝗼𝗱𝗲𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀𝗙𝗶𝘁 𝗽𝗹𝘂𝗴𝗶𝗻: It is part of the Kubernetes scheduler framework. Its primary function is to check if a node has sufficient resources to meet a pod's resource requests. For scoring, the NodeResourcesFit plugin can be configured to use any of the following scoring strategies 1. 𝗟𝗲𝗮𝘀𝘁𝗔𝗹𝗹𝗼𝗰𝗮𝘁𝗲𝗱 (Default strategy): This strategy aims to spread out the workload evenly across nodes to prevent any single node from being overloaded. 3. 𝗠𝗼𝘀𝘁𝗔𝗹𝗹𝗼𝗰𝗮𝘁𝗲𝗱 : In this, the scheduler will pick a node that is already using more resources but still has enough available resources for the new pod. 4. 𝗥𝗲𝗾𝘂𝗲𝘀𝘁𝗲𝗱𝗧𝗼𝗖𝗮𝗽𝗮𝗰𝗶𝘁𝘆𝗥𝗮𝘁𝗶𝗼: In this you can give different importance (weights) to different resources like CPUs and memory. For example, you might decide that CPUs are more important than memory for a particular pod. 𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gpNM_car ♻️ PS: Dont forget to Repost and share with the community. If you have any insights to share, feel free to leave a comment on this post or the blog. 𝗡𝗼𝘁𝗲: Scheduling in Kubernetes is a complex topic with many variables and intricacies. The content here is meant to serve as a starting point and may not cover every aspect or scenario related to pod scheduling. #DevOps #Kubernetes

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Was mind boggling to see how everyone in the industry suffers from Terraform upgrades. This journey was filled with so much learning. Read this amazing blog by Anuj Gupta on Razorpay's journey of upgrading our TF. #terraform #upgrades #razorpaydevops

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Day 27 of #90DaysOfDevOps with TrainWithShubham & Day 3 of #KubeWeek to ace the Kubernetes *Kubernetes Workload* 1. Deployments 2. StatefulSets 3. DaemonSets 4. Jobs & CronJobs #90daysofdevops #KubeWeek #kubernetes #trainwithshubham #devops

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🤔 DevOps Engineer vs Platform Engineer vs SRE - What’s the Deal? Ever wondered how DevOps Engineers, Platform Engineers, and SREs differ? Here's a quick rundown to clear up the distinctions between these roles: 🔹 DevOps Engineer – Think of DevOps Engineers as the bridge between development and operations. Their focus is on automating workflows, CI/CD pipelines, and speeding up software delivery. It's all about getting code from development to production faster and smoother. 🔹 Platform Engineer – Platform Engineers are the architects behind the scenes. They build and manage the infrastructure that development teams use to deploy applications. Imagine them as designers of the playground where the apps live—working with Kubernetes, cloud environments, and more. 🔹 SRE (Site Reliability Engineer) – SREs are the guardians of reliability. They ensure systems are dependable and scalable. When issues arise (and they will!), SREs handle incident responses and automate fixes to keep everything running smoothly. Even though all three roles might use similar tools—like Terraform, Docker, and Kubernetes—their purposes differ. Whether it’s automating deployments, managing infrastructure, or ensuring reliability, the goal of these tools varies by role. Which role resonates most with your interests or current focus? #DevOps #PlatformEngineering #SRE #TechRoles #CloudComputing #Infrastructure

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Test Driving SonarCloud on Kubernetes to understand the bugs it reports in Golang applications. https://lnkd.in/gm7WyNen * SonarCloud found 16,244 bugs with 16,244 false warnings/WONTFIX issues (100%). * Not a single serious bug is found. * SonarCloud missed one known high severity data race bug (https://lnkd.in/gVaxbNK2). * Triaging cost 2,707 hours ($351,910). * No improvement in quality. #sast #testdrive #sonarcloud #golang #opensource #sonarqube

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New Meetup alert!! Many of you know the upcoming Grafana & Friends Mumbai Meetup For those who aren't, what are you waiting for?

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🚀 We are excited to share our journey upgrading Terraform from version 0.11.11 to 1.0.7 at Razorpay! ⭐ Here are the key steps and approaches we took: 🔎Key Points Before Starting: - Understanding the upgrade process is crucial; refer to Terraform's upgrade guide for specific instructions. - Upgrade one major release at a time; avoid skipping intermediate versions for smoother transitions. 💡Approaches Used: - Manual Way (Production Environment): Ensured infrastructure was up-to-date, followed version-specific upgrade processes step-by-step. - Import via Script (Staging Environment): Automated the upgrade process for staging. - Terraformer POC: Explored alternative methods; open to hearing about other approaches! 🎉Outcome: Successfully upgraded to Terraform 1.0.7, enabling enhanced infrastructure management and efficiency gains! 💬 Have you encountered different upgrade methods? Share your insights below! Let's continue the conversation. Read more by our DevOps Engineer Anuj Gupta here: https://lnkd.in/dnXD-9wt

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Post 15 of Series: "How to Explain Kubernetes to a 5-year-old" 🌞How to explain a 5-year-old concept of Resource Quotas in K8s? 🌞 Imagine it's your birthday, and your mom has brought a delicious cake and a variety of chocolates to share with your friends. To make sure everyone gets a fair share of the chocolates, your mom decides to wrap them in small boxes gift boxes. This way, no one takes too many chocolates, and everyone gets a fair amount, preventing anyone from feeling left out or sad. Similarly in case of Resource Quotas ensure the fair distribution of resources like CPU, Memory and can provide Limits for different application in Kubernetes Cluster in certain Namespaces 🤗 Analogies: 🤗 Cake and Chocolates ==> Pods containing the Applications Chocolates wrapped in Gift-Box ==> Application applied with the Specific Resource Quotas(based on the CPU and Memory); It can be cluster-wide or namespace wide Friends not getting Gift Box ==> The scenario where Resource Quotas are not applied they are prone to the Pod not getting enough resources to run leading to OOM Kill Error 🔥 Best Practices 🔥 - The Resource Quotas must be used for wrapping the Applications to the specified CPU, Memory, Storage(Optional). - Should be used Namespace Wide so as to avoid the OOM Killed Error; As its harder to detect which Pod in certain namespace is causing the trouble. - Defining Hard-limits can be a good option if the Application is not Critical. - Further usage of the `scopes` can be made like `BestEffort`, `NotBestEffort`, `Terminating` and `NonTerminating` `BestEfforts` ==> Applies to Pods that do not have resource and request limits defined ==> They get the lowest priority for resources in cluster. `NotBestEffort` ==> Applies to Pods that have at-least one of the Resource Limits or REquest Limits Defined ==> Gets higher priority compared to BestEfforts `Terminating` ==> Applies to pod that are running with `spec.restartPolicy`: `Never`; typically used for batch jobs or short lived jobs `NotTerminating` ==> Applies to pod that are running with the `spec.restartPolicy`: `Always`; typically used for long-running services or applications. 🔥 Conclusion: 🔥 Resource Quotas ensures that resources are fairly and efficiently distributed, maintaining the stability and performance of the Cluster. If you feel this is helpful; then a REPOST is appreciated! For more such Dope Knowledge Bits Follow: ADITYA DHOPADE 👨‍💻

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Flipkart and ShareChat serve content at massive scale, thanks to Kubernetes. Running 1000s of K8s nodes at their scale is just BAU. How did the roadmap look like for running Kubernetes at such scale, what design choices were made to ensure resilience - what were some lessons learnt along the way? If similar questions come to your mind, ask away at the Online AMA with Neeraj and Arya: http://has.gy/2dCI Are you ready for K8s adoption? #Rootconf #RootconfSRE #OnlineAMA #Kubernetes #K8s #Flipkart #ShareChat #BAU #Resilience #DevOps #SRE

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𝐓𝐨𝐩 10 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐀𝐝𝐝-𝐨𝐧𝐬 𝐭𝐨 𝐓𝐫𝐲 𝐢𝐧 𝟐𝟎𝟐𝟒 Elevate Your Kubernetes Game with Must-Have Add-ons Venture into the future of Kubernetes with the latest in our Top 10 Add-ons series for 2024—spotlighting essential tools for Storage Solutions. 𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐲: Storage Solutions 𝐓𝐨𝐨𝐥: Kube-s3 Kube-s3 is making waves by simplifying the integration of AWS S3 storage solutions with Kubernetes clusters, offering a streamlined approach to data management within the cloud-native ecosystem. Next, we'll delve into the world of Observability and Monitoring—vital components for maintaining the health and performance of your Kubernetes environment. #StayTuned for more insights and innovative tools to elevate your Kubernetes setup! #Kubernetes #StorageSolutions #KubeS3 #Atmosly #CloudStorage #Cloud #Solution #CloudSolution #SquareOps #KubernetesTools #TryNow

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In this article, you'll learn how the PvcAutoscaler: - Improves cost efficiency and reduces toil for stateful workloads in Kubernetes. - Addresses StatefulSet and PVC limitations, enabling volume expansion, shrinking, and modification. More: https://lnkd.in/gbMPHRzZ

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In Kubernetes, ensuring critical applications are scheduled on the appropriate nodes is crucial. This is where taints and tolerations come into play, working together to prevent pods from being scheduled on unsuitable nodes. • Taints are applied to nodes, allowing them to repel specific pods. • Tolerations are applied to pods, enabling them to be scheduled on nodes with matching taints. Without a matching toleration, a pod won't be scheduled on a tainted node and will be placed on the next available node instead. There are three taint effects that takes place: (1) NoSchedule: Pods without matching tolerations won’t be scheduled on the node, but existing pods remain unaffected. (2) PreferNoSchedule: The control plane avoids scheduling pods without matching tolerations on the node, but it’s not guaranteed. (3) NoExecute: Pods already running on the node without matching tolerations are immediately evicted. Taints and tolerations provide the control needed to keep critical workloads running on the most appropriate nodes. Hope you find this useful! Feel free to share. Follow along for more insights on DevOps and cloud insights. Thanks for the reading :) #devops #kubernetes #Containers #K8s

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In this overview, Nikhil Vaidyar explains what Kyverno is, how it works, and why we need it besides why we need policies to support Kubernetes resources. Kyverno also orchestrates and manages various policies for Kubernetes resources to maintain a secure, compliant and consistent environment. https://hubs.ly/Q02Rq-wB0 #kubernetes #devops

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Today is #day16 as part #cka program. In this blog, we will explore Rollout and Versioning in Kubernetes with practical example to demonstrate their usage. TABLE OF CONTENTS 🗼Rollout and Versioning 🎗️Viewing Rollout Status 🎗️Viewing Deployment History 🎗️Updating the Deployment Image 🎗️How Deployment Upgrades Work 🎗️Undoing Deployment Changes 🗼Blue-Green Deployment 🎗️Example Commands for Blue-Green Deployment 🗼Conclusion Special Thanks for Inspiring me throughout my journey: Prasad Suman Mohan, Abhishek Veeramalla, Shubham Londhe. Thank you for your continued support, and let's embark on this CKA journey together! 🌐📚💡 #versioning #rollout #updates #bluegreendeployment #server #logs #kubernetes #architecture #docker #CKA #Kubernetes #ApplicationDevelopment #BlogSeries #LearningJourney #CloudNative #devops #cloud #learning #experience #management #connections #developer #security #power #engineers #techblog #kubernetesobjects

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🔔 My another Blog published on DevOps evolutionary journey at Covalensedigital, thanks to our team and my mentor and leader Mr. Pankaj Gulati 📚 Have a happy reading :) #blog #DevOps #digital #DevSecOps #CICD https://lnkd.in/gCww4BdK

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From Commit to Cluster: CI/CD Strategy for EKS Success https://lnkd.in/gVEweFbU #ArgoCD #cicdpipelines #cicd #eks #aws

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