Vishnu N C’s Post

🚀 Join Tech Community -> Guide Others -> Win Exciting Rewards -> https://app.thealpha.dev/ Your Kubernetes cluster is like a bustling city, with containers constantly exchanging information. Kubernetes logging acts as a silent observer in these conversations, offering invaluable insights to help you: 🔍 Troubleshoot problems: Dive into logs to uncover the root cause of application issues. 🏥 Monitor application health: Keep a vigilant eye on logs to ensure your applications are running smoothly and catch any anomalies early. 🚀 Improve performance: Analyze logs to identify bottlenecks and optimize your applications for peak performance. Setting Up Logging: 🔍 Logging agents: These tools are like attentive listeners stationed in each server, capturing and forwarding container logs. 📦 Sidecar containers: Mini-containers dedicated to capturing and transmitting application logs for analysis. 🏆 Benefits: Simplified troubleshooting Enhanced application health monitoring Optimized application performance Effective Kubernetes logging ensures seamless communication among your applications and keeps your cluster operating at its best. 🚀 Join Tech Community -> Guide Others -> Win Exciting Rewards -> https://app.thealpha.dev/ #devops #engineering #softwareengineering #kubernetes #docker

𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ Your Kubernetes cluster is a busy place, with containers constantly chatting. Kubernetes logging eavesdrops on these conversations to help you: 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Logs are like clues, helping you identify why your application isn't working. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐩𝐩 𝐡𝐞𝐚𝐥𝐭𝐡: Keep an eye on logs to see if your applications are healthy and catch issues early. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Analyze logs to find bottlenecks and make your applications run smoother. 𝐒𝐞𝐭𝐭𝐢𝐧𝐠 𝐔𝐩 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐠𝐞𝐧𝐭𝐬:  These tools act like listeners in each server, gathering container logs. 𝐒𝐢𝐝𝐞𝐜𝐚𝐫 𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬: Mini-containers dedicated to capturing and sending application logs for analysis. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: Easier troubleshooting Improved application health monitoring Better application performance Good Kubernetes logging keeps your applications talking and your cluster running smoothly. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ #devops #engineering #softwareengineering #kubernetes #docker

𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ Your Kubernetes cluster is a busy place, with containers constantly chatting. Kubernetes logging eavesdrops on these conversations to help you: 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Logs are like clues, helping you identify why your application isn't working. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐩𝐩 𝐡𝐞𝐚𝐥𝐭𝐡: Keep an eye on logs to see if your applications are healthy and catch issues early. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Analyze logs to find bottlenecks and make your applications run smoother. 𝐒𝐞𝐭𝐭𝐢𝐧𝐠 𝐔𝐩 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐠𝐞𝐧𝐭𝐬:  These tools act like listeners in each server, gathering container logs. 𝐒𝐢𝐝𝐞𝐜𝐚𝐫 𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬: Mini-containers dedicated to capturing and sending application logs for analysis. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: Easier troubleshooting Improved application health monitoring Better application performance Good Kubernetes logging keeps your applications talking and your cluster running smoothly. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ #devops #engineering #softwareengineering #kubernetes #docker

𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ Your Kubernetes cluster is a busy place, with containers constantly chatting. Kubernetes logging eavesdrops on these conversations to help you: 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Logs are like clues, helping you identify why your application isn't working. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐩𝐩 𝐡𝐞𝐚𝐥𝐭𝐡: Keep an eye on logs to see if your applications are healthy and catch issues early. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Analyze logs to find bottlenecks and make your applications run smoother. 𝐒𝐞𝐭𝐭𝐢𝐧𝐠 𝐔𝐩 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐠𝐞𝐧𝐭𝐬:  These tools act like listeners in each server, gathering container logs. 𝐒𝐢𝐝𝐞𝐜𝐚𝐫 𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬: Mini-containers dedicated to capturing and sending application logs for analysis. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: Easier troubleshooting Improved application health monitoring Better application performance Good Kubernetes logging keeps your applications talking and your cluster running smoothly. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ #devops #engineering #softwareengineering #kubernetes #docker

𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ Your Kubernetes cluster is a busy place, with containers constantly chatting. Kubernetes logging eavesdrops on these conversations to help you: 𝐓𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Logs are like clues, helping you identify why your application isn't working. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐩𝐩 𝐡𝐞𝐚𝐥𝐭𝐡: Keep an eye on logs to see if your applications are healthy and catch issues early. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Analyze logs to find bottlenecks and make your applications run smoother. 𝐒𝐞𝐭𝐭𝐢𝐧𝐠 𝐔𝐩 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 𝐚𝐠𝐞𝐧𝐭𝐬:  These tools act like listeners in each server, gathering container logs. 𝐒𝐢𝐝𝐞𝐜𝐚𝐫 𝐜𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬: Mini-containers dedicated to capturing and sending application logs for analysis. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬: Easier troubleshooting Improved application health monitoring Better application performance Good Kubernetes logging keeps your applications talking and your cluster running smoothly. 𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔 -> 𝑾𝒊𝒏 𝑬𝒙𝒄𝒊𝒕𝒊𝒏𝒈 𝑹𝒆𝒘𝒂𝒓𝒅𝒔 ->https://app.thealpha.dev/ #devops #engineering #softwareengineering #kubernetes #docker

🚀 #Mastering_Dockerfile: The Key to Efficient Containerization 🐳 A **Dockerfile** is a simple text file that contains all the commands needed to assemble an image for your container. It plays a critical role in building lightweight, portable applications that run seamlessly across environments. Key components of a Dockerfile: #FROM: Base image #COPY/#ADD: Copy files or directories #RUN: Execute commands inside the image #CMD/#ENTRYPOINT*?: Define the default command or process #EXPOSE: Ports to communicate with the container Using Dockerfile, you can ensure your app runs consistently across different environments. 🚀 #Docker #DevOps #Containerization #Dockerfile #CloudComputing #Automation

🚀 DaemonSets in Kubernetes: A DaemonSet in Kubernetes ensures that a copy of a specific Pod is running on every (or selected) node in a cluster. It is commonly used to deploy cluster-level services that need to run on all nodes or specific ones, ensuring consistency across the Kubernetes environment. ‼️ Challenge As we all know that, Monitoring part is very essential in todays software world 🌍, So we must create logging and monitoring pods on every node of our cluster. Based on that logging info we can easily monitor our cluster and applications. If we create manually then it will create a mess. Because We always scale-in and scale-out the nodes based on requirements. So if we increase the no of nodes (Ex: 3 to 5), its hard to create those monitoring pods every time. Due to the manual deployment there could be a chance of error-prone. 💡Solution: DaemonSet A DaemonSet ensures that the logging or monitoring agent Pod is automatically deployed to every node in the cluster. If a new node is added, Kubernetes ensures the DaemonSet creates a Pod on that node. Similarly, when nodes are removed, the associated Pods are cleaned up. 💠Key Features of DaemonSet Node Affinity: You can target specific nodes (e.g., only worker nodes or nodes with specific labels). Rolling Updates: Supports updates to DaemonSet Pods without downtime. Resource Optimization: Ensures lightweight Pods for essential services. ✅ Command to create a DaemonSet: kubectl create daemonset ds-name --image=image-name ✍Manifest file to create a DaemonSet: apiVersion: apps/v1 kind: DaemonSet metadata: name: myds spec: selector: matchLabels: app: monitor template: metadata: labels: app: monitor spec: containers: - name: cont-1 image: fluentd:latest ports: - containerPort: 80 Apply the YAML File: kubectl apply -f daemonset.yaml DaemonSet doesn’t contains replicas, because it will create only one pod on each node. #DaemonSet #Kubernetes #DevOps

🚀 Excited to share my latest insights on Docker! Docker has transformed the way we build, ship, and run applications, enabling developers and IT teams to work within isolated environments called containers. Here’s why Docker has become a game-changer in the tech world: 🧩 Key Docker Components ✅ Docker Images: These are lightweight packages that include everything needed to run software—code, runtime, libraries, and configurations. Images act as templates for containers and can be stored in repositories like Docker Hub for easy sharing. ✅ Docker Containers: Containers are runnable instances of Docker images, offering isolated environments that share the OS kernel, making them efficient and quick. Unlike virtual machines, containers don’t need their own OS, making them perfect for scalable, microservices-based architectures. Dockerfile: This script automates image creation by defining each step to set up the environment. With a Dockerfile, you ensure consistent, version-controlled environments for your applications. ⚙️ Docker Workflow Overview Create a Dockerfile – Write steps for setting up the app environment. Build an Image – Use docker build to create an image from the Dockerfile. Run a Container – Start an isolated container from the image using docker run. Push/Pull Images – Share images on Docker Hub or pull from others to collaborate easily. 💡 Why Docker? Portability: Run Docker images on any system with Docker installed. Consistency: Achieve uniform app behavior across development, testing, and production. Efficiency: Containers are lightweight, allowing for high-density deployments and optimized resource usage. Docker has redefined how software is developed, deployed, and scaled, ensuring that applications are built and operated in isolated, consistent, and reproducible environments. 🚀 #Docker #Containers #DevOps #Microservices #TechInnovation #CloudComputing #Containerization

In the context of OOP with Docker, an image would be like a class, and the instance of the class would be a container.