Avinash Tietler’s Post

🚀 Big shout out to Ahmed Harabi, the creator of this fantastic Kubernetes architecture diagram using Dezyn! 🎉 Your work highlights how simple and effective it is to visualize complex cloud solutions with our tool. With dezyn.io, you can create rich, interactive diagrams for Kubernetes and other cloud architectures with ease, whether you're working with AWS, Azure, or GCP. Super proud to see our platform helping to bring these ideas to life! Keep building, keep innovating! 💡 #Kubernetes #CloudArchitecture #Dezyn #Diagrams #DevOps #Innovation #CloudComputing

I’ve been studying Kubernetes architecture lately, and I put together this diagram to better understand and share knowledge on how its core components function. While many people are familiar with DevOps tools, they often don’t fully grasp the utility or inner workings of Kubernetes. This is my effort to simplify it and show how Kubernetes manages and automates the deployment of containerized applications. Let’s dive into the technical details of what each component does Control Plane: The control plane is the central management layer of a Kubernetes cluster. Its key components are: API Server: Serves as the gateway for all interactions within the cluster, processing API requests and updating the state of the cluster. Scheduler: Responsible for assigning workloads (pods) to worker nodes based on resource availability and other constraints. Controller Manager: Monitors the state of the cluster and ensures it matches the desired state by running controllers that handle routine tasks like scaling and replication. Etcd: The distributed key-value store where all cluster data and configuration are stored and managed. Worker Nodes: Worker nodes execute and manage containerized applications. Each node includes: Kubelet: An agent that ensures containers are running as expected according to the specifications set by the control plane. Kube Proxy: Handles network communication between services and ensures that network traffic is correctly routed to the appropriate containers. Container Runtime: The software (such as Docker or containerd) that actually runs and manages containers on the node. #Kubernetes #K8s #CloudComputing #DevOps #ContainerOrchestration #TechArchitecture #Microservices #API #Kubelet #Scheduler #Etcd #KubeProxy #ContainerRuntime #TechExplained #Infrastructure #Automation #SoftwareEngineering #Containers #ClusterManagement

🚀 𝗗𝗮𝘆 𝟮𝟲: 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗚𝘂𝗶𝗱𝗲 🛠️ Today, we dive into the depths of Kubernetes, exploring advanced topics that every DevOps engineer should master. This guide will help you understand the intricate details of Kubernetes architecture, deployment strategies, and best practices for managing containerized applications at scale. Key Highlights: - Detailed exploration of Kubernetes architecture and components. - Advanced deployment strategies using Helm charts. - Best practices for scaling applications in Kubernetes. - In-depth guide to Kubernetes networking and security. - Practical tips for optimizing performance and resource management. Sample Commands: # Deploy a Kubernetes application kubectl apply -f your-app.yaml # Scale a deployment kubectl scale deployment your-deployment-name --replicas=3 # View logs of a specific pod kubectl logs your-pod-name # Access a running pod kubectl exec -it your-pod-name -- /bin/bash # List all resources in a namespace kubectl get all -n your-namespace Credit - Sagar Choudhary Download the complete guide to get all the insights and step-by-step instructions! #DevOps #SRE #Kubernetes #CloudNative #Containers #Microservices #DevOpsLife #DevOpsCommunity #K8s #KubernetesGuide #TechLearning #AdvancedKubernetes #CloudInfrastructure #ContainerOrchestration #TechSkills #Automation #CI/CD #CloudComputing #SoftwareDevelopment #IT #TechCommunity --- Feel free to modify or add any specific points or commands as needed!

How the Kubernetes Scheduler Chooses a Node? In a Kubernetes cluster, There will be more than one worker node. So how does the scheduler select the node out of all worker nodes? Th scheduler typically has two main phases: - Scheduling cycle - Binding cycle In Scheduling cycle, to choose the best node, the Kube-scheduler uses 𝗳𝗶𝗹𝘁𝗲𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝘀𝗰𝗼𝗿𝗶𝗻𝗴 operations. In filtering, the scheduler finds the best-suited nodes where the pod can be scheduled. It involves narrowing down the list of nodes to only those that meet the requirements specified by the pod's configuration. Essentially, it filters out nodes that are not suitable for running a particular pod. If it is a large cluster, let’s say 𝟭𝟬𝟬 𝘄𝗼𝗿𝗸𝗲𝗿 𝗻𝗼𝗱𝗲𝘀, and the scheduler doesn’t iterate over all the nodes. There is a scheduler configuration parameter called 𝗽𝗲𝗿𝗰𝗲𝗻𝘁𝗮𝗴𝗲𝗢𝗳𝗡𝗼𝗱𝗲𝘀𝗧𝗼𝗦𝗰𝗼𝗿𝗲 (values between 0 and 100). This parameter determines the percentage of nodes that will be evaluated during the scoring phase. In the scoring phase, the scheduler ranks the nodes by assigning a score to the filtered worker nodes. Finally, the worker node with the highest rank will be selected for scheduling the pod. If all the nodes have the same rank, a node will be selected at random. Binding cycle occurs after the filtering and scoring. The scheduler attempts to bind the pod to the highest-scoring node. If binding fails, the scheduler typically moves to the next highest-scoring node. You can find a detailed explanation in the following blog. 𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gnpWERWc ♻️ Repost and share it with the DevOps learning community. #DevOps #Kubernetes #ContinuousLearning

🚀 Enhancing Kubernetes Cluster Performance with Descheduler 🌐 In dynamic Kubernetes environments, maintaining optimal resource utilization and performance can be challenging. One powerful tool to address this is the Kubernetes Descheduler. Here’s how you can leverage it to improve your cluster efficiency: 1. Pod Eviction Based on Node Conditions: The Descheduler can evict pods from nodes that are under high resource pressure or have specific taints. This helps to redistribute workloads and ensure more balanced resource utilization across your cluster. 2. Node Affinity and Anti-Affinity: If your nodes have specific labels or taints, the Descheduler can help in rebalancing pods according to the updated affinity/anti-affinity rules, ensuring that your workload placement adheres to your intended topology. 3. Resource Defragmentation: Over time, the allocation of resources across your nodes can become fragmented. The Descheduler helps in redistributing pods to defragment resource usage, making it easier to accommodate new pods and scale applications efficiently. 4. Evicting Pods Based on Age: For clusters with long-running workloads, some pods may become stale or less optimal for the current state of the cluster. The Descheduler can evict these older pods to make room for newer, more efficient deployments. 5. Evicting Pods with Noisy Neighbors: If certain pods are causing performance degradation for others on the same node (the "noisy neighbor" problem), the Descheduler can help by evicting and redistributing these pods to maintain overall cluster performance. Implementing the Descheduler can lead to significant improvements in your Kubernetes cluster management by continuously optimizing pod placement and resource utilization. 🔗 Learn more about the Kubernetes Descheduler and how to implement it: https://lnkd.in/gDvUGK2c What strategies do you use to optimize your Kubernetes clusters? Share your experiences and tips below! 💡 🔁 Consider a Repost if this is useful. #Kubernetes #Descheduler #CloudComputing #DevOps #ClusterManagement #TechTips #Automation #DevOpsEngineer

𝐅𝐥𝐚𝐬𝐡 𝐅𝐚𝐜𝐭𝐬: 𝐁𝐢𝐠 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬! Kubernetes provides several types of services to meet different use cases: 🔶 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐈𝐏: This is the default type of service in Kubernetes. It provides a stable IP address within the cluster that other pods can use to access the service. 𝑇ℎ𝑖𝑠 𝑡𝑦𝑝𝑒 𝑜𝑓 𝑠𝑒𝑟𝑣𝑖𝑐𝑒 𝑖𝑠 𝑢𝑠𝑒𝑓𝑢𝑙 𝑓𝑜𝑟 𝑰𝒏𝒕𝒆𝒓𝒏𝒂𝒍 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒄𝒂𝒕𝒊𝒐𝒏 𝑤𝑖𝑡ℎ𝑖𝑛 𝑡ℎ𝑒 𝑐𝑙𝑢𝑠𝑡𝑒𝑟. 🔶 𝐍𝐨𝐝𝐞𝐏𝐨𝐫𝐭: This type of service exposes the service on a static port on each node's IP address. It is useful when you need to access the service from outside the cluster. 🔶 𝐋𝐨𝐚𝐝𝐁𝐚𝐥𝐚𝐧𝐜𝐞𝐫: This type of service exposes the service on an external load balancer. This is useful when you need to distribute traffic across multiple nodes. 🔶 𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥𝐍𝐚𝐦𝐞: This type of service maps the service to an external name that is outside the Kubernetes cluster. This is useful when you need to access an external service that is not running inside the cluster. If you liked this post:  💾 Save this post for future reference 🤝 Have questions or insights? Share in the comments below! ♻️ Repost if this helped you—let’s keep supporting the DevOps community! Have anything to add? #DevOps #Containers #Microservices #CICD #SoftwareDevelopment #CloudComputing #Automation #Scalability #kubernetes #k8s

👉 Follow Vinay Sripragada for such more updates ! 📚 Quick reference for Kubernetes jargon    💡 Boost your understanding of container orchestration 🚀 Stay ahead in the dynamic world of DevOps   Ready to dive in? Explore the table here:   Kubernetes: 🚀 Exciting news for the Kubernetes enthusiasts!   🌐 Just created a comprehensive terminology table for all things Kubernetes. 🤓 Check it out and level up your Kubernetes game! 💡     Kubernetes: An open-source platform for automating deployment, scaling, and operations of application containers.   Node: A physical or virtual machine serving as a worker in Kubernetes.   Pod: The smallest deployable unit in Kubernetes, representing one or more containers.   Container: A portable, self-sufficient software package that includes all necessary components to run an application.   ReplicaSet: Ensures a specified number of pod replicas are running at any given time.   Deployment: Manages ReplicaSets and provides declarative updates to Pods and ReplicaSets.   Service:Defines a logical set of Pods and a policy for accessing them.    Ingress: Manages external access to the services in a cluster, typically for HTTP.   Namespace: Divides cluster resources between multiple users, enabling resource quota management.   Volume: A directory containing data accessible to containers in a Pod.   PersistentVolume: Storage in the cluster provisioned by an administrator or dynamically using Storage Classes.   PersistentVolumeClaim: A user's request for storage.   StatefulSet: Manages the deployment and scaling of a set of Pods with guarantees about ordering and uniqueness.   ConfigMap: Stores non-confidential data in key-value pairs.   Secret: Stores and manages sensitive information such as passwords and tokens.   DaemonSet: Ensures all (or some) Nodes run a copy of a Pod.   Job: Manages the completion of a specific task or batch job in the cluster.   What's your favorite Kubernetes term? Share in the comments below! 👇   #Kubernetes #DevOps  #ContainerOrchestration #CloudComputing #LearnK8s #DevOpsTools #ContinuousIntegration #Containerization #DevOpsCulture

🔍 𝐃𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬: 5 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭𝐢𝐧𝐠 𝐓𝐫𝐢𝐜𝐤𝐬 𝐄𝐯𝐞𝐫𝐲 𝐃𝐞𝐯𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐒𝐡𝐨𝐮𝐥𝐝 𝐊𝐧𝐨𝐰 Kubernetes is a crucial infrastructure for modern businesses, but its complexity can lead to time-consuming troubleshooting, requiring mastery of key techniques for smooth operations. 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐟𝐢𝐯𝐞 𝐞𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐭𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭𝐢𝐧𝐠 𝐭𝐫𝐢𝐜𝐤𝐬 𝐞𝐯𝐞𝐫𝐲 𝐃𝐞𝐯𝐎𝐩𝐬 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐬𝐡𝐨𝐮𝐥𝐝 𝐡𝐚𝐯𝐞 𝐢𝐧 𝐭𝐡𝐞𝐢𝐫 𝐭𝐨𝐨𝐥𝐤𝐢𝐭: ✅𝐒𝐭𝐚𝐫𝐭 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐁𝐚𝐬𝐢𝐜𝐬: 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐝𝐞𝐬𝐜𝐫𝐢𝐛𝐞 𝐚𝐧𝐝 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐥𝐨𝐠𝐬 When something goes wrong in your Kubernetes cluster, the first step should always be to gather as much information as possible. 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐝𝐞𝐬𝐜𝐫𝐢𝐛𝐞: The command provides detailed information about a resource, including events, state, and potential issues, providing a starting point for problem diagnosis. 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐥𝐨𝐠𝐬: Use this to access container logs directly. It's essential when you're debugging application-specific issues, allowing you to see what might be happening inside the container itself. These simple commands often provide enough insight to pinpoint the root cause of an issue quickly. ✅𝐔𝐬𝐞 𝐇𝐞𝐚𝐥𝐭𝐡 𝐏𝐫𝐨𝐛𝐞𝐬 𝐭𝐨 𝐘𝐨𝐮𝐫 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞 Kubernetes health probes are essential for monitoring applications and debugging issues related to Kubernetes' health checks, ensuring pods behave as expected. ✅𝐂𝐡𝐞𝐜𝐤 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐐𝐮𝐨𝐭𝐚𝐬 𝐚𝐧𝐝 𝐋𝐢𝐦𝐢𝐭𝐬 Sometimes, your application is functioning fine, but it's starved for resources. Kubernetes allows you to set resource quotas and limits for CPU and memory, and if your pod exceeds these limits, it may be throttled or even evicted. ✅𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐃𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 𝐞𝐱𝐞𝐜 Networking issues can be particularly tricky to debug in Kubernetes. When you're unsure if your pod can reach another service, use kubectl exec to run commands inside the pod, just as you would on a local machine.. ✅𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐏𝐨𝐝 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐢𝐧𝐠 𝐈𝐬𝐬𝐮𝐞𝐬 Kubernetes pods may be stuck in a Pending state due to insufficient resources or node constraints. Check the events section for issues related to CPU/memory or node affinity. 𝐖𝐡𝐲 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 𝐟𝐨𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬 Kubernetes is recommended for organizations for scalability and stability, while effective troubleshooting and debugging tools can improve system dependability and user experience. Is your team ready to tackle Kubernetes issues with confidence? #Devops #Kubernetes #Debuggingkubernetes

🚢 Demystifying Docker Architecture In today’s development landscape, Docker is a game-changer! But how does it actually work under the hood? Let’s take a closer look at its architecture: 1️⃣ Client: Sends commands to the Docker Daemon, such as docker pull, docker build, and docker run. 2️⃣ Docker Daemon: The core of Docker that listens to Docker API requests and manages Docker objects like images, containers, networks, and volumes. 3️⃣ Containers: Lightweight, executable packages that include everything needed to run software. 4️⃣ Images: Immutable files that contain the source code, libraries, and dependencies for applications. 5️⃣ Registry: Centralized location to store and distribute Docker images. With Docker, we can simplify deployment, isolate applications, and boost productivity by using containers that are easily scalable and portable across environments. 🔑 Key benefits of Docker: Continuous Integration / Continuous Deployment (CI/CD) Microservices architecture support Infrastructure as Code (IaC) DevOps automation Kubernetes and orchestration compatibility Enhanced scalability, agility, and cost-efficiency At MoonSys, we help businesses unlock the full potential of containerized applications using Docker, Kubernetes, and other cutting-edge tools. 🚀 Follow: Hamza Ali Khalid #Docker #DevOps #Kubernetes #Microservices #CI_CD #CloudNative #Containerization #AgileDevelopment #CloudComputing #Automation #MoonSys #Scalability

By leveraging 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐨𝐛𝐣𝐞𝐜𝐭𝐬 effectively, Kubernetes ensures a smooth, scalable, and reliable update process for your applications. These are the challenges used to solve by Deployment object: #️⃣ #️⃣ 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐚𝐧𝐝 𝐭𝐡𝐞𝐢𝐫 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬: #️⃣ #️⃣ 🔶 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐨𝐰𝐧𝐭𝐢𝐦𝐞: Use rolling updates or blue-green deployments. 🔶  𝐅𝐚𝐢𝐥𝐞𝐝 𝐔𝐩𝐝𝐚𝐭𝐞𝐬: Rollback using kubectl rollout undo. 🔶 𝐋𝐨𝐧𝐠 𝐔𝐩𝐝𝐚𝐭𝐞 𝐃𝐮𝐫𝐚𝐭𝐢𝐨𝐧𝐬: Adjust maxUnavailable and maxSurge parameters for faster updates. 🔶  𝐓𝐫𝐚𝐟𝐟𝐢𝐜 𝐑𝐨𝐮𝐭𝐢𝐧𝐠 𝐈𝐬𝐬𝐮𝐞𝐬: Use Service objects or ingress controllers to manage traffic properly. If you liked this post:  💾 Save this post for future reference 🤝 Have questions or insights? Share in the comments below! ♻️ Repost if this helped you—let’s keep supporting the DevOps community! Have anything to add? #DevOps #Containers #Microservices #CICD #SoftwareDevelopment #CloudComputing #Automation #Scalability #kubernetes #k8s