Nitesh Singh’s Post

Containers, Kubernetes, and Docker are technologies that often work together to manage and orchestrate containerized applications at scale. Here's how they are correlated. 🧵🧵 Docker: - Containerization Platform: Docker is primarily known for popularizing container technology. It provides a platform to build, ship, and run applications inside containers. - Docker's Role: - Container Creation: Docker allows developers to package applications into containers using Dockerfiles, which define what goes into the container (e.g., the application code, libraries, dependencies, and runtime). - Distribution: Docker images can be shared via Docker Hub or any other container registry, making it easy to distribute containerized applications. - Local Development: Developers can run these containers on their local machines, ensuring consistency between development, testing, and production environments. Kubernetes: - Container Orchestration: While Docker focuses on creating and running containers, Kubernetes (often abbreviated as K8s) is a system for automating deployment, scaling, and management of containerized applications. Kubernetes' Role: - Orchestration: Kubernetes manages where and when containers are run on a cluster of machines. It handles scaling, failover, deployment patterns, and more. - Service Discovery and Load Balancing: Kubernetes can expose a container using a DNS name or an IP address, and it can load balance traffic to ensure high availability. - Self-Healing: If a container goes down, Kubernetes can restart it. If a node fails, it can move containers to healthy nodes. - Resource Management: It provides ways to define CPU and memory requirements for containers, ensuring optimal resource allocation. In essence, Docker provides the container runtime and tooling to create and run containers, while Kubernetes offers the framework to operate these containers at scale in a production environment, providing robust orchestration capabilities. Together, they form a powerful combination for modern application deployment, management, and scaling. #Docker #Kubernetes #K8s #Containeraization #DevOps #DevSecOps #AWS #Azure #GCP #Oracle

Excited to share some insights into Kubernetes components and how they work together to streamline application deployment and management! 🚀 Kubernetes Components: Master Node: Manages the cluster and makes global decisions about the cluster. Worker Node: Executes the tasks assigned by the master node and runs containers. etcd: A distributed key-value store used to store the cluster's configuration data. Kubelet: An agent that runs on each node and ensures containers are running. Kube-proxy: Maintains network rules on nodes. Container runtime: Software responsible for running containers. Deployment: Desired State Declaration: Describes the desired state for the deployment. ReplicaSet: Ensures that the specified number of pod replicas are running. Pod Template: Defines the pod specification, including the container image and resources. Scaling: Allows scaling the number of replicas up or down based on demand. Rolling Updates: Enables updating the application without downtime. Service: Load Balancing: Distributes incoming traffic across multiple pods. Service Discovery: Enables pods to find and communicate with each other. ClusterIP: Exposes the service on an internal IP within the cluster. NodePort: Exposes the service on each node's IP at a static port. LoadBalancer: Exposes the service externally using a cloud provider's load balancer. Ingress: HTTP and HTTPS Routing: Routes external HTTP(S) traffic to services inside the Kubernetes cluster. TLS Termination: Terminates TLS encryption at the edge of the cluster. Path-Based Routing: Routes traffic based on URL paths. Virtual Hosting: Supports multiple host names on a single IP address. Controller: Manages rules and configurations for traffic routing. Understanding these components is crucial for efficient Kubernetes deployment and management. Excited to dive deeper into this fascinating topic! 💡 #Kubernetes #DevOps #CloudNative #Containerization

How to enable a new cluster quickly and efficiently using GitOps, Flux, and Linode Kubernetes Engine: https://lin0.de/54qosH #DistributedCloud

How to enable a new cluster quickly and efficiently using GitOps, Flux, and Linode Kubernetes Engine: https://lin0.de/BKkA3l #DistributedCloud

🚨 𝟭𝟮 𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 ⚡️ 𝗗𝗼𝗰𝗸𝗲𝗿  - Manages containers through Docker Daemon.  - Uses a registry to store container images.  - Clients can interact with the service or host to deploy containers. ⚡️ 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻  - Manages multiple containers and nodes.  - Example: Kubernetes is the orchestrator for deploying and managing containerized applications. ⚡️ 𝗖𝗮𝗰𝗵𝗶𝗻𝗴  - Improves application performance by using distributed caches.  - Reduces database load by temporarily storing frequently accessed data. ⚡️ 𝗦𝗶𝗻𝗴𝗹𝗲 𝗗𝗕  - Multiple services (Service A, Service B, Service C) connect to a single, shared database.  - Simplifies data consistency but can create a bottleneck. ⚡️ 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗧𝗿𝗮𝗰𝗶𝗻𝗴  - Tracks requests across multiple services in a microservices architecture.  - Useful for troubleshooting and monitoring service interactions. ⚡️ 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗧𝗿𝗮𝗰𝗶𝗻𝗴  - Provides visibility across frontend and backend components.  - Ensures performance monitoring and issue detection across services. ⚡️ 𝗟𝗼𝗴𝗴𝗶𝗻𝗴  - Centralizes logs from different microservices (Microservice 1, Microservice 2).  - Allows for easier tracking and troubleshooting of issues. ⚡️ 𝗘𝘃𝗲𝗻𝘁 𝗕𝘂𝘀  - Facilitates communication between microservices through an event-driven architecture.  - Ensures asynchronous processing of events across services. ⚡️ 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆  - Helps services find each other automatically.  - Uses a service registry and load balancer to connect service providers and consumers. ⚡️ 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴  - Distributes incoming requests evenly across multiple servers.  - Improves application scalability and fault tolerance. ⚡️ 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆  - Acts as a single entry point for clients to access multiple services.  - Handles routing, authentication, and rate limiting. ⚡️ 𝗖𝗹𝗼𝘂𝗱 𝗣𝗿𝗼𝘃𝗶𝗱𝗲𝗿  - Hosts infrastructure in the cloud for scalability.  - Allows for flexible resource provisioning and management. 📱 𝗙𝗼𝗹𝗹𝗼𝘄 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! #devops #docker #containerization #docker #microservices #k8s

#vmware Migrating Legacy Applications to Containerized Environments: Pre-Migration Steps: 1. Identify candidate applications 2. Assess application complexity and dependencies 3. Choose a containerization platform (e.g., Docker, Kubernetes) 4. Plan for networking, storage, and security 5. Develop a migration strategy Migration Steps: 1. Containerize the application:   - Create a Dockerfile   - Build a container image   - Push image to registry (e.g., Docker Hub) 2. Refactor application architecture:   - Break down monolithic apps into microservices   - Implement service discovery and communication 3. Address dependencies and integrations:   - Identify and containerize dependent services   - Configure service orchestration (e.g., Kubernetes) 4. Test and validate:   - Unit testing, integration testing, and end-to-end testing   - Validate performance, scalability, and security 5. Deploy and monitor:   - Deploy containerized application to production   - Monitor performance, logs, and security Tools and Technologies: 1. Containerization platforms:   - #Docker   - #Kubernetes   - Red Hat OpenShift   - #Amazon Elastic Container Service (ECS) 2. Migration tools:   - Docker Migration Tool   - Kubernetes Migration Tool   - AppDynamics   - New Relic 3. Refactoring tools:   - API gateways (e.g., NGINX, Amazon API Gateway)   - Service mesh (e.g., Istio, Linkerd) 4. Testing and validation tools:   - Selenium   - JMeter   - Postman   - OWASP ZAP Best Practices: 1. Start with simple applications 2. Use iterative and incremental approach 3. Focus on application modernization 4. Leverage automation and scripting 5. Monitor and optimize performance Challenges and Considerations: 1. Application complexity 2. Dependency management 3. Security and compliance 4. Networking and storage 5. Scalability and performance 6. Team skills and expertise 7. Change management Real-World Examples: 1. #Netflix's migration to cloud-native architecture 2. #Amazon's migration to containerized environments 3. #Google's migration to Kubernetes 4. #Microsoft's migration to Azure Kubernetes Service (AKS) Additional Resources: 1. #Docker Migration Guide 2. #Kubernetes Migration Guide 3. Containerization tutorials (e.g., Docker, Kubernetes) 4. Webinars and conferences (e.g., DockerCon, KubeCon) 5. Online courses and training (e.g., Coursera, edX) By following these steps and best practices, organizations can successfully migrate legacy applications to containerized environments, improving scalability, security, and efficiency. Would you like to know more about containerization?

🚀 New Blog Post Alert! 🚀 I’m thrilled to share my latest blog post on Hashnode, where I dive deep into the world of DaemonSets in Kubernetes! 🎉✨ 🔍 What’s Inside: Understanding the concept and purpose of DaemonSets 🤔 Exploring real-world use cases like monitoring, logging, and security 🔒📊 A detailed workflow of how DaemonSets operate in a Kubernetes environment 🔄 Step-by-step YAML configuration to create a Fluentd DaemonSet for log collection 📜 Commands to manage DaemonSets and verify pod deployment in your cluster 🛠️✅ Mastering DaemonSets is essential for ensuring that critical services run seamlessly across your Kubernetes nodes. 🌐💪 💡 Check it out: [https://lnkd.in/gg2Nqdfe] 🔗 Feel free to share your thoughts or ask questions in the comments! Let’s keep learning together! 🌱🙌 #Kubernetes #DevOps #CloudComputing #DaemonSet #Logging #Hashnode #Microservices #Containers #CloudNative #Infrastructure #CI/CD #ITInfrastructure #TechCommunity #OpenSource #Monitoring #SysAdmin #SoftwareDevelopment #Agile #TechBlog #LearningInPublic

🔀 Kubernetes application traffic routing - have you ever wondered how it actually works? ⬇️ Take a look at this high level overview: ⬇️ To begin, let's list all objects involved in application traffic routing: ➡️ External Load Balancer ➡️ Ingress Controller ➡️ Ingress ➡️ Service ➡️ Pod Second, let’s discuss responsibilities of 💻 Kubernetes Application Developer and 👷 Kubernetes Administrator with respect to these objects. 👷 Kubernetes Administrators are maintainers of the cluster including the cluster-wide resources such as Ingress Controller. 💻 Kubernetes Application Developer are users of of cluster-wide resources and consume provisioned Ingress Controller by creating Ingress rules. As 💻 Kubernetes Application Developer, you are responsible for defining: 1️⃣ Pods templates including containers listening for requests on specific ports. 2️⃣ Services exposing those pods. 3️⃣ Ingress rules routing the traffic to services. As 👷 Kubernetes Administrator, you are responsible for provisioning Ingress Controller. ___ Would you like to learn more about other Kubernetes components? ⬇️ Please comment below! ⬇️ ___ My name is Jakub Krzywda, PhD. I post about: #kubernetes, #cloudnative technologies and #devops practices. Learn #K8sWithK5a Click my name + follow + 🔔 so you don’t miss my next posts! Looking for training in Kubernetes or other Cloud Native technologies? 🔝 Enrol today in the course that best suits your needs (link on the top of my profile)

Kubernetes itself is a very powerful platform, but it can sometimes need additional tools to satisfy the demands of modern applications and operations. In this guide, we will take a look at 20+ tools in different categories that can enhance your Kubernetes experience, allowing you to manage Kubernetes better. https://lnkd.in/gRWm38Uj

As of late, working with Kubernetes has become an integral part of my work. But what is Kubernetes, and why use it in the first place? Kubernetes is an open-source orchestration platform for containerised applications, typically deployed within a cluster format. Kubernetes supports microservices architectures by managing the deployment, scaling, and operation of application containers across clusters of hosts. Although static pods on a single node deployment are possible, they're primarily used for small-scale test environments. The primary forms of deploying a Kubernetes cluster involve using the kubeadm tool, which sets up a minimum viable cluster, or the manual way, which requires more administrative leg-work i.e sourcing different binaries, configuring authentication certificates for different services, and more. From a high-level view, a cluster comprises a master node and worker nodes, which can be physical or virtual, on-prem or hosted in the cloud. The master node contains control plane components: the kube-scheduler, kube-api server, etcd cluster database, and controller managers like the node-controller or replication controller. Worker nodes within the cluster host applications as containers within ephemeral pods. Worker node components include: the kube-proxy service, which enables communication between nodes, and the kubelet agent, which receives instructions from the kube-api server and a container runtime engine, which is often docker. My favourite aspect of working with Kubernetes is the declarative form of deployment, which simplifies documenting how pods, deployments, services, and replicasets are configured. Find out more about how Kubernetes functions here: https://lnkd.in/ez7RDAWY kubectl reference docs: https://lnkd.in/e-c492q8 Happy learning! #kubernetes #aks #cicd #devops #microservices