Samit Singh

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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Hi All, We are seeking a talented and experienced Grafana Developer to join our dynamic team. 𝐆𝐫𝐚𝐝𝐞: Senior Associate (5-10 yrs) 𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: PAN India 𝐍𝐨𝐭𝐢𝐜𝐞 𝐏𝐞𝐫𝐢𝐨𝐝: Max 90 days 𝐍𝐨. 𝐨𝐟 𝐏𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐬: 2 𝐉𝐨𝐛 𝐃𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧: As a 𝐒𝐢𝐭𝐞 𝐑𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 (𝐒𝐑𝐄) specializing in 𝐆𝐫𝐚𝐟𝐚𝐧𝐚, you will play a crucial role in ensuring the reliability, performance, and observability of our systems. Your mission is to bridge the gap between development and IT operations, making sure our software systems run efficiently and seamlessly. 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: 1. 𝑮𝒓𝒂𝒇𝒂𝒏𝒂 𝑬𝒙𝒑𝒆𝒓𝒕𝒊𝒔𝒆: 𝐈𝐧𝐠𝐞𝐬𝐭𝐢𝐨𝐧 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬: Design and implement robust data ingestion pipelines using Grafana. Ensure efficient and reliable data collection from various sources. 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧: Develop and manage Grafana dashboards to visualize metrics, logs, and traces. Collaborate with application teams to create meaningful visualizations. 𝐀𝐥𝐞𝐫𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: Configure alerts and notifications within Grafana to proactively identify incidents, anomalies, and performance bottlenecks. 2. 𝑶𝒃𝒔𝒆𝒓𝒗𝒂𝒃𝒊𝒍𝒊𝒕𝒚 𝒂𝒏𝒅 𝑻𝒓𝒐𝒖𝒃𝒍𝒆𝒔𝒉𝒐𝒐𝒕𝒊𝒏𝒈: 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: Collaborate with development teams to instrument applications and services for metrics, logs, and traces. Provide insights into application behavior and performance. 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: Monitor infrastructure components (servers, databases, network) using Grafana. Troubleshoot issues and optimize resource utilization. 𝐈𝐧𝐜𝐢𝐝𝐞𝐧𝐭 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞: Investigate incidents, analyze root causes, and contribute to incident response processes. 3. 𝑩𝒆𝒔𝒕 𝑷𝒓𝒂𝒄𝒕𝒊𝒄𝒆𝒔 𝒂𝒏𝒅 𝑨𝒖𝒕𝒐𝒎𝒂𝒕𝒊𝒐𝒏: 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐑𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞: Implement best practices for scaling Grafana deployments. Optimize resource usage and ensure high availability. Automation: Automate routine tasks related to Grafana setup, configuration, and maintenance. 𝐂𝐈/𝐂𝐃 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Integrate Grafana into CI/CD pipelines for seamless deployment and version management. 4. 𝑪𝒐𝒍𝒍𝒂𝒃𝒐𝒓𝒂𝒕𝒊𝒐𝒏 𝒂𝒏𝒅 𝑲𝒏𝒐𝒘𝒍𝒆𝒅𝒈𝒆 𝑺𝒉𝒂𝒓𝒊𝒏𝒈: 𝐂𝐫𝐨𝐬𝐬-𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Work closely with development, operations, and other teams to align Grafana practices with overall system goals. 𝐌𝐞𝐧𝐭𝐨𝐫𝐢𝐧����: Mentor team members on Grafana best practices, troubleshooting techniques, and observability principles. If you are passionate about Grafana development and eager to join our team, please submit your resume to 𝘺𝘰𝘨𝘦𝘴𝘩.𝘴𝘩𝘪𝘳𝘢𝘸𝘢𝘥𝘦𝘬𝘢𝘳@𝘤𝘰𝘨𝘯𝘪𝘻𝘢𝘯𝘵.𝘤𝘰𝘮 #sre #grafana #monitoring #observability #opening #job #cognizant

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✅ #Interview Questions for 2.5 to 4 yrs #𝐀𝐖𝐒 𝐰𝐢𝐭𝐡 #DevOps Role : #Top Practise Set 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐩𝐫𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧 1. What is GIT stash ? 2. What is a branching strategy? 3. What is the command to discard changes in the working dir? 4. How do you debug the exited container? 5. How do you execute jobs parallely in Jenkins? 6. Maven Lifecycle? 7. How do you upgrade Jenkins? 8. What is called a Parameterised Job in Jenkins? 9. What is called Docker Swarm? 10. How do you handle codes in Nexus satisfactory? 11. How do you manage space issues in the Jenkins server? 12. what is called a multibranch project in the Jenkins server ? 13. How do you secure the Jenkins server? 14. How do you manage GITHUB roles? 15. What is called a NULL resource in Terraform? 16. What is called terraform fmt ? 17.What is called Snowball? 18. How do you manage credentials in Terraform? 19. What is called Code Deploy in AWS? 20. Can you attach a single EBS volume to multiple EC2 instances at the same time? 21. Can you use Multiple FROM in DockerFile ? 22. DockerFile runs as which user? 23. How can we pass an argument to DockerFile? 24. What are deployment strategies? 25. What is called an application load balancer? 26. What is Kubernetes architecture ? 27. What is called Fargate service in AWS? 28. What are Register targets in Ansible? 29. How do you pull artifacts from NEXUS? 30. How to access the S3 bucket privately ? 31. What is the difference between a NAT inst and a NAT Gateway? 32. How can you restrict particular IPs accessing EC2 instances? 33. What is called VPC peering? 34. What is called Transit Gateway? 35. What are the types of autoscaling? 36. To prevent DDOS attacks, which load balancer is used ? 37. What is called a sticky session? 38. What is called Lambda? 39. How do you manage tfstate file in Terraform? 40. How do yo create multiple ec2 instances in terraform ? 41. AWS has released a new service, how does Terraform behave? 42. How do you uncommit the changes that have already been pushed to GitHub? 43. What is the difference between git pull and git fetch? 44. What is called Jenkins File? 45. What is called Shared Libraries in Jenkins? 46. What is called docker networking? 47. What is called a Trust relationship in AWS? 48. What is called Public Subnet and Private Subnet? 49. How do you establish a connection between ec2 instance to another ec2 instance? 50. What is realm command ? 51. How do you differentiate within an AWS account dev env, test env, and prod env? 52. Types of ec2 instances? 53. How can you encrypt the already created unencrypted EBS without creating a fresh EC2 instance? 54. How do you install Nginx in the Ansible playbook? 55. How do you recover the deleted object in S3? ✅Repost if found useful Follow for more 💯

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The last few months have been all about making Kubernetes self-serve for organizations who struggle to get started due to DevOps bandwidth and the knowledge gap of Developers. Here’s the first-ever product demo of Scoutflo Deploy v2.0 🚀 3 things that make Developer and DevOps lives easier: 1. Getting started on Kubernetes A simple GUI (graphical user interface) to set up resources. Easily manage your K8s infrastructure through IAC via GitOps. 2. Open-Source Product Deployments You can deploy any open-source product and get it up and running on Kubernetes within minutes. Standardized deployments that make collaboration easier. 🚨 Supporting microservices soon🚨 3. Monitoring and Alerts    Keep track of Infrastructure Cost and Usage metrics to optimize effectiveness. The goal is to reduce points of friction and make Kubernetes management self-serve! Feel free to share your feedback! If you’d like to have a 1:1 demo, just DM me or drop a comment! P.S. Sign up for the waitlist if you haven’t already - link in the comment! 💙 #kubernetes #gitops #opensource #devops

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You will hear from me again soon! on 🗓️ Session Time: 3:45 PM - 4:30 PM IST Join me in session 2 : The data deluge: Navigating multi-region apps and disaster recovery on AWS Registration Link : https://lnkd.in/g6kuUded 🚀 Excited to announce that I'll be speaking at a fantastic talk tailored for our Fintech and FSI customers! 🚀 Join me for "The Data Deluge: Navigating Multi-Region Apps and Disaster Recovery on AWS," we'll dive deep into building resilient applications and disaster recovery using the AWS Mumbai and Hyderabad regions. In this session, you will learn how to leverage the new Hyderabad facility for disaster recovery and optimize application resilience with AWS database services, both RDBMS and NoSQL. We'll cover best practices, architectural patterns, and managed services to safeguard your data and application stack. Key technical areas we'll explore: ✅ AWS Databases: Relational Database Services (Aurora, RDS, RDS for SQL Server) ✅ AWS NoSQL Databases: DynamoDB, DocumentDB, ElastiCache ✅ AWS Streaming Services: Amazon Managed Streaming for Apache Kafka (MSK) ✅ AWS Data and Analytics Platforms ✅ AWS Backup and Replication Methods Don’t miss this opportunity to equip yourself with the tools to build truly resilient applications on AWS! Looking forward to sharing insights and connecting with you all. #AWS #DisasterRecovery #Fintech #FSI #CloudComputing #AWSMumbai #AWSHyderabad #DatabaseServices #NoSQL #RDBMS #MSK #Analytics

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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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Rolling with Resilience: How Kubernetes' Rollback Strategy Helped Me Bounce Back from Weight Loss Setbacks As I reflect on my weight loss journey, I realized it's a perfect analogy for the roll back strategy in Kubernetes deployment! Last two months, I weighed 96kg and thought I was on track. But next month, I hit a setback and tipped the scales at 104kg. It was like a deployment gone wrong! BUT, I didn't give up. I rolled back to my previous "version" (aka my healthy habits) and got back on track. And guess what? This month, I'm back to 96kg! It's a reminder that setbacks happen, but with the right strategy, we can roll back and try again. In Kubernetes, it's about reverting to a previous deployment version. In life, it's about learning from our mistakes and getting back on track. So, remember: when life gives you setbacks, roll back, recharge, and try again! #weightlossjourney #rollbackstrategy #kubernetes #resilience #Kubeadm #devOps #Cloud #AKS #EKS #GKE

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TLDR; No, Devops engineer is not same as SRE or Cloud engineer. No, you can not use them interchangeably. I am fortunate enough to have worked as Devops engineer as well as SRE and well, there are striking differences in both of them. I am glad one of my colleagues asked this and that reminded me how tech recruiters out there mix these terminologies and candidates end up with the job they are not really ready for. Roles of DevOps Engineer, Site Reliability Engineer (SRE), Cloud Engineer, Build Engineer, and Platform Engineer, while overlapping in some areas, have distinct focuses and responsibilities. Let's list out some of them: DevOps Engineer : Bridging the gap between development and operations. 1. Automating and streamlining the software development and deployment processes. 2. Managing CI/CD pipelines. 3. Ensuring reliable and frequent code releases. 4. Collaborating with development, QA, and operations teams to improve system reliability and performance. 5. Monitoring and logging systems to identify and resolve issues. SRE :Ensuring the reliability and performance of production systems. 1. Implementing and maintaining service level objectives (SLOs) and service level agreements (SLAs). 2. Monitoring and alerting for system reliability and performance. 3. Incident response and post-mortem analysis. 4. Automating repetitive tasks and optimizing system operations. 5. Balancing feature development with system reliability. Cloud Engineer : Designing, implementing, and managing cloud infrastructure. 1. Deploying and managing cloud resources (e.g., AWS, Azure, Google Cloud). 2. Ensuring the security and scalability of cloud systems. 3. Implementing cloud services and tools to support applications. 4. Managing cloud-based databases, storage, and networking. 5. Monitoring and optimizing cloud cost and performance. Build Engineer : Managing the build and integration processes for software development. 1. Setting up and maintaining build systems and tools. 2. Automating the build process to ensure efficient and reliable software compilation. 3. Managing dependencies and version control systems. 4. Troubleshooting build issues and ensuring build reproducibility. 5. Integrating various components and ensuring consistent builds across environments. Platform Engineer : Building and maintaining the underlying platform and infrastructure that supports application development and deployment. 1. Developing and managing the infrastructure platform (often PaaS or container orchestration platforms like Kubernetes). 2. Ensuring scalability, reliability, and performance of the platform. 3. Creating tools and frameworks to support developer productivity. 4. Implementing security measures and best practices. 5. Collaborating with development and operations teams to ensure platform effectiveness. Hope this helps with the basic :) #Devops #SRE #cloud

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Running out of cloud credits is such a bittersweet moment. We are not eligible for extension because we crossed the threshold (yea! product usage is growing 🔥 ) but the burn hurts 😩 Is switching to #AWS from #GCP cause of cloud credits worth it? Will we save more than we lose in switching cost? Mainly paying for serverless cloud run , storage and networking

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Container Storage Interface (CSI) in Kubernetes! 💡 As Kubernetes continues to dominate the orchestration landscape, the need for a standardized and flexible storage solution becomes critical. Enter the Container Storage Interface (CSI)—a game-changer in how storage vendors and Kubernetes interact. What is CSI? The Container Storage Interface (CSI) is an open standard that defines how storage systems can expose their capabilities to container orchestration systems like Kubernetes. Before CSI, integrating new storage solutions with Kubernetes required internal modifications, leading to complexity and scalability issues. CSI addresses these challenges by providing a standardized, plugin-based approach. ** Popular CSI Drivers ** Several CSI drivers are available, catering to different storage needs. Amazon EBS CSI Driver: For integrating Amazon Elastic Block Store with Kubernetes, providing scalable and high-performance storage. Google Cloud Filestore CSI Driver: For using Google Cloud's fully managed file storage with Kubernetes clusters. Azure Disk CSI Driver: For leveraging Azure Disks to provide persistent storage for Azure Kubernetes Service (AKS). Ceph-CSI: For integrating Ceph storage systems, offering block, file, and object storage. VMware vSphere CSI Driver: For connecting VMware’s vSphere storage capabilities with Kubernetes. #kubernetes #CSI #ContainerStorageInterface #CloudNative #StorageSolutions #DevOps #Innovation #DataManagement #Scalability #Interoperability #TechAdvancements

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Kubernetes, often abbreviated as K8s, is a container orchestration platform. Let me explain this in straightforward terms. Let's say you have your app, which you have containerised. So you run a bunch of containers to serve your app to users. But how do you manage these different containers? The situation is complicated even more by the fact that these containers needn't necessarily be running on the same machine! This is where K8s comes to the rescue. Kubernetes makes deploying, managing, and scaling containerised workloads a breeze! I want to explicitly call out here that K8s is NOT a container engine like Docker. Rather it is a container orchestrator. Hope you likes the short description of k8s 𝐅𝐫𝐞𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐢𝐧 𝐃𝐞𝐯𝐎𝐩𝐬 - https://lnkd.in/gXFpeyB3  𝐉𝐨𝐢𝐧 𝐡𝐞𝐫𝐞 𝐟𝐨𝐫 𝐅𝐑𝐄𝐄 𝐃𝐞𝐯𝐎𝐩𝐬/𝐒𝐑𝐄 𝐦𝐞𝐧𝐭𝐨𝐫𝐬𝐡𝐢𝐩 - https://t.me/freebootcamp7  [ Join this telegram group ]

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🚀 Exciting News! 🚀 AWS announced the launch of granular cost visibility for Amazon Elastic Kubernetes Service (Amazon EKS) in the AWS Cost and Usage Reports (CUR)! Now, you can analyze, optimize, and charge back costs and usage for your Kubernetes applications like never before. 💡 With AWS Split Cost Allocation Data for Amazon EKS, customers gain the ability to allocate application costs to individual business units and teams based on how Kubernetes applications consume shared EC2 CPU and memory resources. Here's what you can expect: ✨ Granular Cost Visibility: Dive deep into your Kubernetes application costs and usage to understand exactly where your resources are being utilized. ✨ Enhanced Optimization: Identify areas for optimization and efficiency improvements to ensure you're making the most out of your AWS resources. ✨ Streamlined Chargeback: Allocate costs accurately to different business units and teams, empowering you to track expenses and manage budgets effectively. And the best part? Split Cost Allocation Data for Amazon EKS is available to customers in all AWS commercial regions (excluding China regions) at no additional cost! 🌍 Learn more about how AWS Split Cost Allocation Data for Amazon EKS can benefit your organization today. #AWS #AmazonEKS #Kubernetes #CostVisibility #Optimization #CloudComputing #AWSNews #CloudManagement #TechInnovation https://lnkd.in/eDA22N8h

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Hot take: Building a business around open-source software is a lost battle. In last few months, we have seen how companies such as HashiCorp, Redis labs have faced the heat when they adopted business source licensing model. It resulted in their alternatives popping up within few days like OpenTofu, Dragonfly etc. There is no moat for such businesses because the underlying software is open-sourced which means new entrants can easily replicate what they are doing. They can sell it at a cheaper price or with a better ecosystem(if they are cloud vendors) or both. These businesses also face the dilemma of whether to merge a major improvement in the open-source or put it behind the SaaS offering. An alternative to this model is to build the business around consulting & training. The business keeps the software open sourced & provide consulting services to clients who want to use it in the most efficient manner. Pivotal has done a great job with Spring framework using this model. This way your revenue stream is not marginalized by new players easily & the core team can focus on improving the software without worrying whether it makes their core revenue model i.e. SaaS offering less attractive. Especially in the non-ZIRP era, companies are bound to reconsider where they are spending. Hence they will choose the option that burns the smallest hole in their pocket. #opensource

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🌟 Why Terraform is a Game-Changer for Infrastructure as Code (IaC) 🌟 In the rapidly evolving world of DevOps and cloud computing, managing infrastructure efficiently is paramount. One tool that stands out in this domain is Terraform. Here are some key benefits of using Terraform as your IaC tool: 1. Infrastructure as Code (IaC): Terraform enables you to define your entire infrastructure in configuration files. This approach not only enhances visibility but also ensures consistency across environments. 2. Platform Agnostic: With support for multiple providers like AWS, Azure, GCP, and many others, Terraform allows you to manage a diverse set of infrastructures seamlessly. 3. Version Control: Terraform configuration files can be stored in version control systems (like Git), making it easy to track changes, collaborate with team members, and roll back to previous versions if needed. 4. Efficient Change Management: Terraform’s plan and apply workflow lets you preview changes before applying them. This reduces the risk of unintentional modifications and ensures that the changes are executed as intended. 5. Scalability: Terraform’s modular design allows you to break down your infrastructure into reusable components, making it easier to manage and scale complex environments. 6. Community and Ecosystem: Terraform has a robust community and a rich ecosystem of modules and providers. This means you can leverage a wide range of pre-built solutions and best practices to accelerate your infrastructure deployment. 7. State Management: Terraform maintains a state file that tracks your infrastructure's current state. This ensures that your configuration files are always in sync with the actual infrastructure, allowing for precise updates and auditing. 8. Automated Infrastructure Testing: Integrating Terraform with CI/CD pipelines facilitates automated testing of your infrastructure changes, enhancing the reliability and stability of your deployments. 🔗 Whether you're a startup or an enterprise, adopting Terraform can significantly streamline your infrastructure management processes, improve collaboration, and reduce operational overhead: https://www.terraform.io/ Ready to transform your infrastructure management? Dive into Terraform today and experience the future of IaC! 🚀 #devops #cloudcomputing #infrastructureascode #terraform #IaC #cloudinfrastructure #automation #devopstools

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Pub/Sub and queue look the same when you hear it for the first time.😱 Here is a simple explanation of what they are and the differences between them. In the illustration depicted below, 🔴 Messaging Queue: People come to the mall to shop. Before they check out, they must wait in the queue to complete the payment. Here, the mall is like a producer, producing people ( who have shopped and are ready to complete payment) who are sent to the queue to complete the payment. One by one, each person completes payment at the checkout counter. The checkout counter is like a consumer. As the queue grows ( more people join the line), more than one checkout ( one consumer ) is needed, and we will need to add more checkout counters ( more consumers). We have Producers, Queues, and Consumers. 🔴 Pub / Sub - Extending on the above example, after the checkout is completed, this customer data might be required by various services. For instance, in the image below, we have a real-time service that calculates how many people have completed the checkout. Hence, the checkout service has subscribed to receive this data. Likewise, marketing and inventory services might subscribe to receive this data. We have Producers, Topics, and Subscribers. 𝗣𝘂𝗯/𝘀𝘂𝗯:⏹️ The subscribers don’t have to reveal anything to the publishers. Messages are in the topic even after multiple subscribers consume it. Messages are sent to multiple subscribers simultaneously and asynchronously Message ordering and sending to various consumers is not guaranteed Producers and consumers have loose coupling 𝗤𝘂𝗲𝘂𝗲: ⏹️ Queues need to reveal who they are sending messages to Producers would put the messages in the queue, storing them until one of the consumers consumes them Producers put the messages in the queue, typically sent using some ordering and sequentially to a single receiver Message ordering and sending to consumers is guaranteed Producers and consumers have some sort of relationship #engineering #systemdesign #interview #productdevelopment #eventdrivenarchitecture

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Did you know you could autoscale the number of Kubernetes pods for an application in your cluster based on the number of pending messages in the queue ? Read on to understand how. If you have an event driven architecture, you are probably using a queue for async processing. You could be using any queue provider like GCP Pub/Sub, AWS SQS or RabbitMQ. You could be using some monitoring tool like Cloudwatch, Prometheus or Stackdriver for measuring the length of the backlog of the queue. To implement autoscaling for metrics from the above monitoring tools, you would need to install an adapter for that tool on your cluster.  These adapters are available as helm charts. The helm chart installs an implementation for the metrics API on the Kubernetes cluster. What this means is that your Prometheus/Stackdriver/Cloudwatch metrics can be queried using the Kubernetes API. You can then write an HPA manifest that uses these custom metrics to scale the number of pods based on the value of those custom metrics. For example, you could write a rule in your HPA manifest to scale up the number of pods if the average number of pending messages in the queue is 3. So if you have 5 pods running at a given point of time, the moment the number of messages in the queue goes above 15 (>3 messages per pod), your number of pods increase. This ensures a wonderful customer experience because it reduces the delay in the processing of the message. If you liked this content, do give me a follow. I share content related to Devops, Cloud and Kubernetes. #devops #cloud #kubernetes

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Q- Why use PVC when PV is there in Kubernetes???? Ans- PVCs are requests for those resources and also act as claim checks to the resource. So a persistent volume (PV) is the "physical" volume on the host machine that stores your persistent data. A persistent volume claim (PVC) is a request for the platform to create a PV for you, and you attach PVs to your pods via a PVC. Always remember if PVC is "x" units then PV is >="x" units. but never less... If you try to create a PVC that is more than the size of the PV, the PVC claim will fail and the pods that use the PVC will be marked "Pending". However, a PVC can bind to a bigger PV when there is no smaller available PV. Simple????!! 🤠

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