Anwesha Rath

💻👨‍💻 Day 5 of revising my Kubernetes concepts from Kubesimplify 's kubernetes hindi bootcamp by Saiyam Pathak 🚀 In the fifth video i learned about the following topics ✅ Kubernetes namespaces ✅ Labels and selectors ✅ Node selector ✅ Equity based labels ✅ Set based labels ✅ Grouping of resources logically ✅ Scheduler performance tuning ✅ Pod scheduling redlines ✅ Topology spread ✅ Cordoning of the node ✅ Priority class ✅ Pod overhead ✅ Node affinity ✅ Taints & tolerations Kubernetes Cloud Native Computing Foundation (CNCF)

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💡 Use 𝐫𝐞𝐜𝐮𝐫𝐬𝐢𝐯𝐞 flag along with 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐞𝐱𝐩𝐥𝐚𝐢𝐧 command to get all the fields available for that Kubernetes resource. Following is the example command for deployment resource. >>> 𝘬𝘶𝘣𝘦𝘤𝘵𝘭 𝘦𝘹𝘱𝘭𝘢𝘪𝘯 𝘥𝘦𝘱𝘭𝘰𝘺𝘮𝘦𝘯𝘵 --𝘳𝘦𝘤𝘶𝘳𝘴𝘪𝘷𝘦 and then, If you want to deep dive into any of the field, use following command along with field name. In this scenario, I am looking for 𝘥𝘦𝘱𝘭𝘰𝘺𝘮𝘦𝘯𝘵.𝘴𝘱𝘦𝘤.𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺 >>> 𝘬𝘶𝘣𝘦𝘤𝘵𝘭 𝘦𝘹𝘱𝘭𝘢𝘪𝘯 𝘥𝘦𝘱𝘭𝘰𝘺𝘮𝘦𝘯𝘵.𝘴𝘱𝘦𝘤.𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺 #kubernetes #devops #docker #sre #hackwithharsha #python #java

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Hi everyone! Just completed implementing seamless integration of Amazon S3 and DynamoDB with Terraform. Why i did this 🤔? ->Working with Terraform in a team, use of a local file makes Terraform usage complicated because each user must make sure they always have the latest state data before running Terraform and make sure that nobody else runs Terraform at the same time 😐. Benefits of Using Terraform Remote State 🙂: 1. Shared Storage: Enable seamless collaboration by granting team members access to the same Terraform state files for infrastructure management. 2. Locking: Ensure data integrity with state file locking during changes, preventing conflicts and data loss from concurrent updates. 3. Versioning: Maintain a history of Terraform state file versions, facilitating rollback to previous configurations when necessary. 4. Reduced Manual Errors: Automate state synchronization to mitigate the risk of human errors in managing changes, ensuring consistent state across deployments. A big thanks to Abhishek Veeramalla for such helping content! #Terraform #InfrastructureAsCode #AWS #DevOps #Automation #CloudComputing

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How Mandar Sarfare received 400% hike in DevOps with 90 days notice period https://lnkd.in/g6GBv5Fb There are times when we have a fear on how to tackle the 90 Days notice period or how we have to approach someone to get a job or it might be funny sometimes to put papers without any job in current organisation. But yes we have Mandar with us in this video who reveals all his story about the placement being the BCA graduate background.  In this video he explained about 1) 90 Days notice period tackle 2)Job search portals that helped him 3) Linkedin hacks that he used 4) Finally the BSC graduate becoming DevOps engineer journey Note - This video was recorded along with the Part1 , so if you have missed the part1 it is here https://lnkd.in/gqsQRuTZ If you have read the post till here, do share with your BSC graduate friends :)

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$ kubectl apply -f ckad-certificate.yaml -n bharath-b-s certificates/ckad-certificate-created I’m absolutely over the moon to announce that I’ve earned my first K8s certification! 🚀 A big thank you to #MumshadMannambeth and #KodeKloud for the course and all the dedicated CKAD challenges and labs. Also, big thanks to killer.sh and #Killercoda for their hands-on exercises that prepped me for the real deal. I’m excited to leverage this knowledge to drive innovation and efficiency in my projects. Onward to new challenges and opportunities in the Kubernetes ecosystem #cncf #kubernetes #devops #cloudnativecomputing #continouslearning #ckad #linuxfoundation #containers #cloud #k8scertified #cloudengineering #softwareengineering #cloudnativearchitecture #KodeKloud #MumshadMannambeth #TechJourney

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💻👨‍💻 Day 6 of revising my Kubernetes concepts from Kubesimplify's kubernetes hindi bootcamp by Saiyam Pathak 🚀 In the sixth video i learned about the following topics ✅ Replicasets ✅ Gateway API ✅ Ingress controllers ✅ Deployment ✅ Non homogenous pods ✅ Propagation policies - Foreground - Background - Orphan ✅ Deployment Strategies - Rolling update - Recreate update - Blue-green :- version/service change - Canary :- Traffic splitting ✅ Rollout command use ✅ Probes - Readiness - Startup - Liveness Kubernetes Cloud Native Computing Foundation (CNCF)

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𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗢𝗽𝗲𝗻 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 (𝗢𝗖𝗜, 𝗖𝗥𝗜, 𝗖𝗡𝗜, 𝗖𝗦𝗜, 𝗦𝗠𝗜, 𝗖𝗜𝗟) Kubernetes, the de facto standard for container orchestration, relies on a robust ecosystem of open standards. These standards are developed and maintained by the community and define how different components interact within the system 𝗞𝗲𝘆 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 🔶 𝙄𝙣𝙩𝙚𝙧𝙤𝙥𝙚𝙧𝙖𝙗𝙞𝙡𝙞𝙩𝙮: Different vendors can create products adhering to the same standard, ensuring seamless integration. 🔶 𝙁𝙡𝙚𝙭𝙞𝙗𝙞𝙡𝙞𝙩𝙮: You can choose components and plugins from various vendors based on your specific needs. 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀 : 🔶 𝙊𝙥𝙚𝙣 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙄𝙣𝙞𝙩𝙞𝙖𝙩𝙞𝙫𝙚 (𝙊𝘾𝙄): Defines a standard for container image formats and runtimes. Popular examples include 𝘋𝘰𝘤𝘬𝘦𝘳, 𝘊𝘙𝘐-𝘖, 𝘢𝘯𝘥 𝘙𝘒𝘛 images. 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙍𝙪𝙣𝙩𝙞𝙢𝙚 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙍𝙄): Establishes a consistent way for Kubernetes to interact with different container runtimes. CRI utilizes a plugin architecture, allowing support for various Runtime options like 𝘊𝘙𝘐-𝘖, c𝘰𝘯𝘵𝘢𝘪𝘯𝘦𝘳𝘥 etc 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙉𝙚𝙩𝙬𝙤𝙧𝙠 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙉𝙄): Provides a specification and toolset for configuring network interfaces within containers. This plugin architecture enables Kubernetes to integrate with various network plugins like 𝘍𝘭𝘢𝘯𝘯𝘦𝘭, 𝘊𝘢𝘭𝘪𝘤𝘰, 𝘢𝘯𝘥 𝘞𝘦𝘢𝘷𝘦 𝘕𝘦𝘵. 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙎𝙩𝙤𝙧𝙖𝙜𝙚 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝘾𝙎𝙄): Facilitates communication between Kubernetes and diverse storage providers. Storage providers can develop CSI plugins that are compatible with various container orchestration systems. Examples 𝘈𝘞𝘚 𝘌𝘭𝘢𝘴𝘵𝘪𝘤 𝘉𝘭𝘰𝘤𝘬 𝘚𝘵𝘰𝘳𝘢𝘨𝘦, 𝘕𝘦𝘵𝘈𝘱𝘱 etc. 🔶 𝙎𝙚𝙧𝙫𝙞𝙘𝙚 𝙈𝙚𝙨𝙝 𝙄𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 (𝙎𝙈𝙄): Defines a standard for service meshes on Kubernetes, allowing consistent interaction with different service mesh implementations like 𝘐𝘴𝘵𝘪𝘰, 𝘓𝘪𝘯𝘬𝘦𝘳𝘥 etc 🔶 𝘾𝙤𝙣𝙩𝙖𝙞𝙣𝙚𝙧 𝙄𝙢𝙖𝙜𝙚 𝙇𝙞𝙗𝙧𝙖𝙧𝙮 (𝘾𝙄𝙇): This set of specifications defines how container images are stored, indexed, and distributed. Major container registries like 𝘋𝘰𝘤𝘬𝘦𝘳 𝘏𝘶𝘣, 𝘘𝘶𝘢𝘺.𝘪𝘰, 𝘢𝘯𝘥 𝘏𝘢𝘳𝘣𝘰𝘳 leverage CIL for sharing and reusing container images across various platforms and environments. #kubernetes #Containerization #Cloud

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Kubernets 1.31 now truly vendor neutral platform !! What is it mean and how things going to affect The release of Kubernetes 1.31 marks the culmination of a significant migration effort to remove in-tree cloud provider integrations. Previously, Kubernetes supported cloud providers like AWS, Azure, and Google Cloud directly within its core code, which created vendor dependencies, increased complexity, and bloated the system. With the removal of these in-tree integrations, Kubernetes now relies on external cloud controller managers (CCMs), requiring users to deploy them separately for each cloud provider. This transition was a massive undertaking, involving the development of new subsystems such as the kubelet credential provider and storage migration. The migration successfully reduced the Kubernetes core by 1.5 million lines of code and decreased binary sizes by 40%. While it simplifies future Kubernetes development and makes the platform more cloud-neutral, it may require organizations to adjust their existing configurations and scripts to accommodate these changes. Key takeaways: 1. Removal of in-tree cloud providers in Kubernetes 1.31 simplifies the platform but breaks backward compatibility for cloud-provider arguments. 2. Users must deploy cloud controller managers (CCMs) separately for cloud integration. 3. The migration cut code size significantly, making Kubernetes more lightweight and secure. 4. Organizations need to adapt to new deployment methods, especially with the updated kubelet behavior and external integrations. #Kubernetes #Devops #cloud #AWS #Azure #GCP #docker #Security

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𝗥𝘂𝗻 𝗟𝗲𝗮𝗱𝗲𝗿 𝗘𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗔𝗺𝗼𝗻𝗴 𝗣𝗼𝗱𝘀 𝗶𝗻 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗟𝗲𝗮𝗱𝗲𝗿 𝗘𝗹𝗲𝗰𝘁𝗶𝗼𝗻: Some applications require specific processes to run only on a single Pod instance to avoid duplicate tasks. Kubernetes Deployments with multiple Pod replicas require a leader election process outside the Pods to ensure only one Pod performs these tasks. 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝗨𝘀𝗲 𝗰𝗮𝘀𝗲𝘀: 🔶  𝙎𝙘𝙝𝙚𝙙𝙪𝙡𝙚𝙙 𝙏𝙖𝙨𝙠𝙨: Only one Pod should run batch processing, cache updates, etc. 🔶  𝙇𝙚𝙖𝙙𝙚𝙧-𝙊𝙣𝙡𝙮 𝙎𝙚𝙧𝙫𝙞𝙘𝙚𝙨: Sending notifications or triggering specific APIs that shouldn't be called multiple times. 𝘒𝘶𝘣𝘦𝘳𝘯𝘦𝘵𝘦𝘴 𝗟𝗲𝗮𝘀𝗲 𝘖𝘣𝘫𝘦𝘤𝘵 𝘤𝘰𝘮𝘦𝘴 𝘵𝘰 𝘵𝘩𝘦 𝘳𝘦𝘴𝘤𝘶𝘦!! Here's how leader election works using Leases: 🔶  𝙇𝙚𝙖𝙨𝙚 𝘾𝙧𝙚𝙖𝙩𝙞𝙤𝙣: The first Pod creates a Lease object using configurations such as Lease name, Pod name & namespace and updates the current timestamp along with the Lease duration. 🔶  𝙇𝙚𝙖𝙨𝙚 𝙏𝙧𝙖𝙘𝙠𝙞𝙣𝙜: The Lease object keeps track of the current leader Pod's name. 🔶  𝙇𝙚𝙖𝙙𝙚𝙧 𝙍𝙚𝙣𝙚𝙬𝙖𝙡: If the Leader Pod is still active, it renews the lease by updating the timestamp before it expires. 🔶  𝙇𝙚𝙖𝙙𝙚𝙧 𝙀𝙡𝙚𝙘𝙩𝙞𝙤𝙣: If the timestamp isn't updated, inactive replicas race to acquire the lock with its identity and assume the leader role. This process leverages the 𝙖𝙩𝙤𝙢𝙞𝙘 𝙣𝙖𝙩𝙪𝙧𝙚 𝙤𝙛 𝙆𝙪𝙗𝙚𝙧𝙣𝙚𝙩𝙚𝙨 operations to ensure that no two replicas can acquire the Lease simultaneously by keeping track of the 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘝𝘦𝘳𝘴𝘪𝘰𝘯 field. Read more and Code snippet: https://lnkd.in/gatVJGzP & https://lnkd.in/gWNGht3J #Kubernetes #LeaderElection #Containerization

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My Story of How I improved single server pod efficiency to handle 150 concurrent users operating at 100% cpu usage to 900 concurrent users operating at 85% cpu usage It has been a long day and a long time since I had posted so here's some of my recent venture into servers, server-side latency and infra costs. So the story starts with a load test request for one of our apis on a Friday morning looking forward to push a new feature to prod by evening. My mind goes well that's a double edged sword when it comes to critical requests on a Friday :) Anyways It's a simple request with a small twist to it since I wanted to publish the results for both cached and non-cached behavior of the same api. I build my jmeter scripts and run it on Azure Load Runner and bam first surprise.... As the number of virtual users increased, our poor little single pod taking up the huge loads suffered and the latency gradually went up until certain breaking point where it couldn't handle the said number of concurrent users. Surprisingly the same pod could handle same rps with way less number of users! This pod had a spec of 2 cpu and 4G memory. The server could handle merely 29 users at 191ms which is < 200ms (standards) and this seemed too low.  Moreover at ~150 users the latency shot upto 48s and at ~200 users it had reached 3mins! This led me into a rabbithole trying to debug what might be issue which led me into profiling the memory and cpu usage during such loads and long story short the cpu usage was pretty high i.e., 100% but low memory. After a live profiling of such pods via VisualVm I was able to conclude the following: 1. Number of threads must be improved. 2. Threads must be efficiently used i.e., less waiting time on threads. 3. Reduce the cpu usage. The solution for the above problem was: 1. Tomcat thread and queue management for best use of available resources. 2. Server change from BIO to NIO mode (Non-Blocking IO) 3. Connection pooling 4. Increase Heap memory and set min and max to handle throttling. Now the trick is to not over-do the number of threads and tasks handled by a thread since it can increase the memory usage again trggering gc events which is bad. After fine ballet of all above mentioned fixes lo and behold a single pod could handle  900 concurrent users 1k RPS at 950ms with cpu as low as 85% and low gc activity!! #springboot #jmeter #backend #infra #costcutting

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Today is #day22 as part #cka program. In this blog, we will explore KubeConfig in Kubernetes in Kubernetes with practical example to demonstrate their usage. TABLE OF CONTENTS 🗼What is a KubeConfig File? 🗼Structure of a KubeConfig File 🗼Managing KubeConfig 🗼Conclusion Special Thanks for Inspiring me throughout my journey: Prasad Suman Mohan, Shubham Londhe, Savinder Puri Thank you for your continued support, and let's embark on this CKA journey together! 🌐📚💡 #kubeconfig #authentication #security #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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Day 1/ #365: Routing, Switching, Security & Automation Today was a productive day filled with learning about routing, switching, and advancing my work in automation. Routing and Switching: I covered the basics of network interfaces, how flooding works, and learned about SVIs (Switch Virtual Interfaces), which are crucial when connecting devices across different VLANs in the same network. To switch between VLANs, we use Layer 3 switches. Why VLANs?: In large data centers, many devices are connected. VLANs help organize and speed up communication by grouping devices into smaller, more manageable networks. By default, everything falls under VLAN 1, but we can create separate VLANs to improve efficiency. Types of Routers: Wired Routers Wireless Routers Dual-Band Routers (I use this at home, operating at both 2.4GHz and 5GHz) Tri-Band Routers Core Routers Edge Routers Physical Routers Virtual Routers VPN Routers – These include IPsec and L2TP protocols to keep internet traffic secure. Key Point: Routers use IP addresses to forward packets across different networks. Switches use MAC addresses, which are 48-bit unique identifiers for devices. On the security front, I started exploring TOR browsing and the Tails operating system. TOR (The Onion Router) is essential for anonymous browsing by encrypting and bouncing your traffic through different nodes, making it difficult to trace. Tails OS is a privacy-focused operating system designed to be run live from a USB stick, leaving no trace of your activity. Both are key tools for those interested in network security and privacy. On the automation front, I’m working on a personal project—a bot that identifies missing data and tries to fill in the gaps. If it can’t, it generates a report with the missing entries. I’m in the implementation phase and using Kaggle datasets for testing. Additionally, I solved two HashSet questions on LeetCode to keep sharpening my logical thinking. It’s going to be a very interesting journey—this is just Day 1, and no one knows what Day 365 will look like. But one thing’s for sure: Consistency breaks everything, and I’m committed to staying consistent throughout. What type of router do you use at home? Let me know in the comments! Looking forward to learning more tomorrow. Note If you are not able to understand the Notes - I have uploaded the documentation for Day-1 Learning in my github. https://lnkd.in/dWfmbaVj If you are interested in Cloud so I have made a project where using the API's of our cloud I have created my own space in Arduino cloud and connected it. Here is the link of project : https://shorturl.at/uK8Cg #Networking #CyberSecurity #Routing #Switching #VLAN #LeetCode #Automation #BotDevelopment #DataDriven #AutomationEngineer #CoderJava #DSA #pepsicoproud

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Learning Kubernetes is like solving a Rubik's cube. It may seem overwhelming and complex at first, But with patience to go through required fundamentals, hands-on practice, and a solid understanding of its core concepts. It becomes very easy. If you are interested in learning the k8s concepts with real-world examples and preparing for the CKA certification, you can join the waitlist for my CKA course. 𝗝𝗼𝗶𝗻 𝗖𝗞𝗔 𝗖𝗼𝘂𝗿𝘀𝗲 𝗪𝗮𝗶𝘁𝗹𝗶𝘀𝘁: https://lnkd.in/e-fzXFZ3 #kubernetes

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Hello connections, Azure Container Instances (ACI) is a serverless container service offered by Microsoft Azure. It allows you to run containers quickly without managing any virtual machines or higher-level services. ACI is designed for scenarios where you need to run containers on-demand or for short periods of time, making it a suitable choice for bursting, batch processing, or task-based workloads. *Key Features of Azure Container Instances 1. *Serverless Computing*: ACI is a serverless offering, which means you don't need to provision or manage any virtual machines or higher-level services. Azure handles the underlying infrastructure, allowing you to focus on your application. 2. Rapid Deployment: Containers can be deployed and started in Azure Container Instances within seconds, providing near-instant responsiveness. 3. Pay-Per-Second Billing: You are billed for each second that your container group was running, allowing for cost-effective usage. 4. Persistent Storage: ACI supports mounting Azure File shares and Azure Disks for persistent storage. 5. Virtual Network Integration: Container groups can be deployed into an Azure Virtual Network, enabling secure communication with other resources in the same virtual network. 6. Environmental Parity: ACI supports the same container images and runtimes as other Azure services, ensuring consistent behavior across different environments. Use Cases for Azure Container Instances - Batch Processing*: Run containerized batch jobs on-demand without the need to manage a long-running cluster. - Task Automation*: Automate tasks and scripts within containers, triggered by events or schedules. - Microservices: Run microservices or lightweight applications in containers without the overhead of managing virtual machines or clusters. - Data Processing: Process data streams or files using containerized applications. - Burst Workloads: Handle spikes in demand or traffic by quickly spinning up additional container instances. Deploying Containers with Azure Container Instances You can deploy containers to ACI using various methods, including: - Azure Portal - Azure CLI - Azure PowerShell - Azure Resource Manager templates - Azure Container Instance REST API When deploying containers, you can specify container settings, resource requirements, environment variables, and other configurations. Monitoring and Logging Azure Container Instances provides monitoring and logging capabilities through Azure Monitor. You can view container logs, performance metrics, and set up alerts for your container instances. Reach out Ratheesh Kumar Certified ☁ Cloud Architect & ⚙ DevOps Expert 📞 +91 94463 30906  🌐. www.ratheeshtech.com #Azure #CloudJourney #CloudArchitecture #Cybersecurity #DevOps #AzureLandingZones #TechInnovation #azurecloud

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Hello connections, Azure Container Instances (ACI) is a serverless container service offered by Microsoft Azure. It allows you to run containers quickly without managing any virtual machines or higher-level services. ACI is designed for scenarios where you need to run containers on-demand or for short periods of time, making it a suitable choice for bursting, batch processing, or task-based workloads. *Key Features of Azure Container Instances 1. *Serverless Computing*: ACI is a serverless offering, which means you don't need to provision or manage any virtual machines or higher-level services. Azure handles the underlying infrastructure, allowing you to focus on your application. 2. Rapid Deployment: Containers can be deployed and started in Azure Container Instances within seconds, providing near-instant responsiveness. 3. Pay-Per-Second Billing: You are billed for each second that your container group was running, allowing for cost-effective usage. 4. Persistent Storage: ACI supports mounting Azure File shares and Azure Disks for persistent storage. 5. Virtual Network Integration: Container groups can be deployed into an Azure Virtual Network, enabling secure communication with other resources in the same virtual network. 6. Environmental Parity: ACI supports the same container images and runtimes as other Azure services, ensuring consistent behavior across different environments. Use Cases for Azure Container Instances - Batch Processing*: Run containerized batch jobs on-demand without the need to manage a long-running cluster. - Task Automation*: Automate tasks and scripts within containers, triggered by events or schedules. - Microservices: Run microservices or lightweight applications in containers without the overhead of managing virtual machines or clusters. - Data Processing: Process data streams or files using containerized applications. - Burst Workloads: Handle spikes in demand or traffic by quickly spinning up additional container instances. Deploying Containers with Azure Container Instances You can deploy containers to ACI using various methods, including: - Azure Portal - Azure CLI - Azure PowerShell - Azure Resource Manager templates - Azure Container Instance REST API When deploying containers, you can specify container settings, resource requirements, environment variables, and other configurations. Monitoring and Logging Azure Container Instances provides monitoring and logging capabilities through Azure Monitor. You can view container logs, performance metrics, and set up alerts for your container instances. Reach out Ratheesh Kumar Certified ☁ Cloud Architect & ⚙ DevOps Expert 📞 +91 94463 30906  🌐. www.ratheeshcloud.com #Azure #CloudJourney #CloudArchitecture #Cybersecurity #DevOps #AzureLandingZones #TechInnovation #azurecloud

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Hello connections, Azure Container Instances (ACI) is a serverless container service offered by Microsoft Azure. It allows you to run containers quickly without managing any virtual machines or higher-level services. ACI is designed for scenarios where you need to run containers on-demand or for short periods of time, making it a suitable choice for bursting, batch processing, or task-based workloads. *Key Features of Azure Container Instances 1. *Serverless Computing*: ACI is a serverless offering, which means you don't need to provision or manage any virtual machines or higher-level services. Azure handles the underlying infrastructure, allowing you to focus on your application. 2. Rapid Deployment: Containers can be deployed and started in Azure Container Instances within seconds, providing near-instant responsiveness. 3. Pay-Per-Second Billing: You are billed for each second that your container group was running, allowing for cost-effective usage. 4. Persistent Storage: ACI supports mounting Azure File shares and Azure Disks for persistent storage. 5. Virtual Network Integration: Container groups can be deployed into an Azure Virtual Network, enabling secure communication with other resources in the same virtual network. 6. Environmental Parity: ACI supports the same container images and runtimes as other Azure services, ensuring consistent behavior across different environments. Use Cases for Azure Container Instances - Batch Processing*: Run containerized batch jobs on-demand without the need to manage a long-running cluster. - Task Automation*: Automate tasks and scripts within containers, triggered by events or schedules. - Microservices: Run microservices or lightweight applications in containers without the overhead of managing virtual machines or clusters. - Data Processing: Process data streams or files using containerized applications. - Burst Workloads: Handle spikes in demand or traffic by quickly spinning up additional container instances. Deploying Containers with Azure Container Instances You can deploy containers to ACI using various methods, including: - Azure Portal - Azure CLI - Azure PowerShell - Azure Resource Manager templates - Azure Container Instance REST API When deploying containers, you can specify container settings, resource requirements, environment variables, and other configurations. Monitoring and Logging Azure Container Instances provides monitoring and logging capabilities through Azure Monitor. You can view container logs, performance metrics, and set up alerts for your container instances. Reach out Ratheesh Kumar Certified ☁ Cloud Architect & ⚙ DevOps Expert 📞 +91 94463 30906  🌐. www.ratheeshcloud.com #Azure #CloudJourney #CloudArchitecture #Cybersecurity #DevOps #AzureLandingZones #TechInnovation #azurecloud

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Hello connections, Azure Container Instances (ACI) is a serverless container service offered by Microsoft Azure. It allows you to run containers quickly without managing any virtual machines or higher-level services. ACI is designed for scenarios where you need to run containers on-demand or for short periods of time, making it a suitable choice for bursting, batch processing, or task-based workloads. *Key Features of Azure Container Instances 1. *Serverless Computing*: ACI is a serverless offering, which means you don't need to provision or manage any virtual machines or higher-level services. Azure handles the underlying infrastructure, allowing you to focus on your application. 2. Rapid Deployment: Containers can be deployed and started in Azure Container Instances within seconds, providing near-instant responsiveness. 3. Pay-Per-Second Billing: You are billed for each second that your container group was running, allowing for cost-effective usage. 4. Persistent Storage: ACI supports mounting Azure File shares and Azure Disks for persistent storage. 5. Virtual Network Integration: Container groups can be deployed into an Azure Virtual Network, enabling secure communication with other resources in the same virtual network. 6. Environmental Parity: ACI supports the same container images and runtimes as other Azure services, ensuring consistent behavior across different environments. Use Cases for Azure Container Instances - Batch Processing*: Run containerized batch jobs on-demand without the need to manage a long-running cluster. - Task Automation*: Automate tasks and scripts within containers, triggered by events or schedules. - Microservices: Run microservices or lightweight applications in containers without the overhead of managing virtual machines or clusters. - Data Processing: Process data streams or files using containerized applications. - Burst Workloads: Handle spikes in demand or traffic by quickly spinning up additional container instances. Deploying Containers with Azure Container Instances You can deploy containers to ACI using various methods, including: - Azure Portal - Azure CLI - Azure PowerShell - Azure Resource Manager templates - Azure Container Instance REST API When deploying containers, you can specify container settings, resource requirements, environment variables, and other configurations. Monitoring and Logging Azure Container Instances provides monitoring and logging capabilities through Azure Monitor. You can view container logs, performance metrics, and set up alerts for your container instances. Reach out Ratheesh Kumar Certified ☁ Cloud Architect & ⚙ DevOps Expert 📞 +91 94463 30906  🌐. www.ratheeshcloud.com #Azure #CloudJourney #CloudArchitecture #Cybersecurity #DevOps #AzureLandingZones #TechInnovation #azureclou

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New Blog Alert 🚀 AWS Challenge Day 7 Task Completed. Today, I Learned AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy, AWS CodePipeline From Guidance Shubham Londhe Sir, TrainWithShubham ▶️ AWS CodeCommit: AWS CodeCommit is a fully managed source control service that hosts secure and scalable Git repositories. Whether you're managing a large team or working solo, CodeCommit simplifies version control and collaboration. ● High Availability: Your repositories are highly available and durable. ● Security: Integrated with AWS Identity and Access Management (IAM) for secure access control. ● Scalability: Automatically scales with your needs, without the hassle of managing infrastructure. ▶️ AWS CodeBuild: AWS CodeBuild automates the process of compiling source code, running tests, and producing deployment-ready artifacts. It’s designed to integrate seamlessly with your CI/CD pipeline. ● No Server Management: Fully managed service that eliminates the need to provision and manage build servers. ● Scalability: Handles concurrent builds and scales according to demand. ● Customizable Builds: Use buildspec.yml to define build commands and phases tailored to your project. ▶️ AWS CodeDeploy: AWS CodeDeploy automates application deployments across various compute services, including Amazon EC2, AWS Lambda, and on-premises servers. ● Deployment Strategies: Supports rolling deployments, blue/green deployments, and canary releases. ● Automated Rollbacks: Automatically reverts to the previous version in case of deployment failures. ● Flexibility: Can be used with a wide range of application architectures. ▶️ AWS CodePipeline: AWS CodePipeline is a fully managed CI/CD service that automates the end-to-end software release process. It integrates seamlessly with CodeCommit, CodeBuild, and CodeDeploy, allowing you to: ● Define Workflows: Create pipelines that automate source code retrieval, build, test, and deployment stages. ● Customizable: Easily configure stages and actions to fit your specific development needs. ● Integration: Works with other AWS services and third-party tools to provide a comprehensive CI/CD solution. 🌟 Why Leverage AWS CI/CD Tools? ● Efficiency: Automate and accelerate your development process with minimal manual intervention. ●Reliability: Ensure consistent and error-free deployments with integrated testing and rollback capabilities. ● Scalability: Easily scale your infrastructure and workflows to meet growing demands. ● Integration: Benefit from seamless integration with a wide range of AWS and third-party services. Happy Learning 😊. #Day31 #AWSwithTWS #7DaysOfAWS #90DaysOfDevOps #TrainWithShubham #CodeCommit #CodeBuild #CodeDeploy #CodePipeline

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🌍Hello all ! Integrating Apache Tomcat with Jenkins for Seamless Deployment. In the world of DevOps, streamlined and efficient deployments are critical. One powerful combination that many engineers use for deploying Java applications is Apache Tomcat and Jenkins. Here’s a quick guide on how to integrate these tools and a look at some key uses. 🔗 Why Integrate Tomcat with Jenkins? Tomcat is a widely-used Java application server, and Jenkins, with its robust CI/CD capabilities, makes it easier to automate deployments. By integrating Tomcat with Jenkins, you can: Automate the deployment process for Java applications. Enable continuous integration and delivery (CI/CD) for faster releases. Simplify code deployment across different environments. 🔧 Integration Steps 1. Install Jenkins and Tomcat: Ensure both Jenkins and Tomcat are up and running. Tomcat should be accessible at a specified URL, and Jenkins must have the necessary plugins installed. 2. Install the Deploy to Container Plugin in Jenkins: Go to Jenkins > Manage Jenkins > Manage Plugins. Search for and install the Deploy to Container Plugin. This plugin allows Jenkins to deploy .war files directly to the Tomcat server. 3. Configure Jenkins Job: Set up a Pipeline job (or Freestyle if preferred) in Jenkins. In your job configuration, choose the Post-Build Actions and select Deploy war/ear to a container. Configure the following: WAR/EAR File: Path to your .war file generated by the build. Containers: Choose Tomcat 7+ (or as per your version). Credentials: Add your Tomcat manager credentials to allow Jenkins to deploy. 4. Add Tomcat Server Details: Specify the Tomcat server’s URL (e.g., http://localhost:8080) and credentials. Ensure your Tomcat user has permissions to upload the application (manager-gui role). 5. Run the Job: Now, every time you build, Jenkins will deploy the latest .war file to Tomcat. You can view the application directly on the configured Tomcat server. 🎯 Key Uses of Jenkins-Tomcat Integration: Automated Deployments: Deploy new features, bug fixes, or updates faster. Testing & Staging Environments: Set up continuous delivery to testing or staging servers for QA. Rollback: Simplify rollback processes by tracking deployment history in Jenkins. #DevOps #Jenkins #Tomcat #ContinuousDeployment #CICD #JavaDevelopment #Automation #SoftwareEngineering #DeploymentPipeline #TechTips #DevOpsTools #CloudComputing #ApplicationDeployment #TechInnovation

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