EDB’s Post

What Kubernetes is not 1) Does not limit the types of applications supported. Kubernetes aims to support an extremely diverse variety of workloads, including stateless, stateful, and data-processing workloads. If an application can run in a container, it should run great on Kubernetes. 2) Does not deploy source code and does not build your application. Continuous Integration, Delivery, and Deployment (CI/CD) workflows are determined by organization cultures and preferences as well as technical requirements. 3) Does not provide application-level services, such as middleware (for example, message buses), data-processing frameworks (for example, Spark), databases (for example, MySQL), caches, nor cluster storage systems (for example, Ceph) as built-in services. Such components can run on Kubernetes, and/or can be accessed by applications running on Kubernetes through portable mechanisms, such as the Open Service Broker. 4) Does not dictate logging, monitoring, or alerting solutions. It provides some integrations as proof of concept, and mechanisms to collect and export metrics. 5) Does not provide nor mandate a configuration language/system (for example, Jsonnet). It provides a declarative API that may be targeted by arbitrary forms of declarative specifications. 6) Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems. #kubernetes #docker #aws #devops #azure #eks #container #devopsengineer #terraform

Multi-Cloud Mastery - New release date! October 2nd! Pre-order -> https://lnkd.in/gsy5WS8t Chapter 4: Architecting Resilient Stateful Applications in Kubernetes --> Data persistence is critical <-- Chapter 4 dives into designing Kubernetes clusters for stateful applications, ensuring data availability and integrity across multiple clouds. Gain the confidence to run Kubernetes effectively in a multi-cloud environment! #Kubernetes #MultiCloud #CloudManagement #DevOps #PlatformEngineering

𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐘𝐨𝐮𝐫 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐰𝐢𝐭𝐡 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫𝐬! 💻 Tired of the hassle of manual management in Kubernetes? Meet Kubernetes Operators – your new go-to for streamlining deployments and scaling effortlessly. 𝐖𝐡𝐚𝐭 𝐀𝐫𝐞 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫𝐬? Think of them as your deployment assistants. They simplify tasks by treating your app as one entity, instead of juggling various components. It's like having a personal assistant for your Kubernetes operations! 𝐖𝐡𝐲 𝐔𝐬𝐞 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫𝐬? Operators shine when managing complex, stateful apps. From databases to message queues, they automate tasks like backups and scaling, freeing you up for more important work. 𝐔𝐧𝐥𝐨𝐜𝐤 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 Operators encapsulate operational knowledge into code, ensuring consistency and reliability. Say goodbye to errors and hello to seamless operations! With a wide range of community-driven and enterprise-grade solutions, there's an Operator for every use case. Simplify your life with tailored solutions for your apps. In the age of cloud-native computing, agility is crucial. Kubernetes Operators empower you to scale effortlessly and stay ahead of the curve. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: Deploying a MongoDB Database Looking to deploy MongoDB on Kubernetes? Say no more! With the MongoDB Operator, you can automate the entire lifecycle of your MongoDB database. 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: 1. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜 𝐒𝐜𝐚𝐥𝐢𝐧𝐠: The Operator dynamically adjusts the size of your MongoDB cluster based on demand, ensuring optimal performance. 2. 𝐁𝐚𝐜𝐤𝐮𝐩 𝐚𝐧𝐝 𝐑𝐞𝐬𝐭𝐨𝐫𝐞: Say goodbye to manual backups. The Operator handles scheduled backups and restores, keeping your data safe and secure. 3. 𝐑𝐨𝐥𝐥𝐢𝐧𝐠 𝐔𝐩𝐠𝐫𝐚𝐝𝐞𝐬: Keep your MongoDB deployment up-to-date with seamless rolling upgrades, minimizing downtime and ensuring continuous availability. 4. 𝐂𝐮𝐬𝐭𝐨𝐦 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧𝐬 (𝐂𝐑𝐃𝐬): The Operator extends Kubernetes' capabilities with custom resource definitions, allowing you to manage MongoDB resources like any other Kubernetes object. With the MongoDB Operator, deploying and managing MongoDB on Kubernetes has never been easier. Say hello to simplified operations and goodbye to manual management! Ready to revolutionize your deployment workflow? Dive into Kubernetes Operators and watch your operations reach new heights! Kubernetes #Operators MongoDB #DevOps #Automation #CloudNative #Deployment #Containerization #Scaling #DatabaseManagement

Hey Everyone, Take a look at my first Medium blog discussing Kubernetes custom resources. I recently incorporated the custom resources concept in my master's thesis and discovered its significant utility in extending the Kubernetes API. I would greatly appreciate your valuable feedback on this blog. Thank you! #kubernetes #orchestration #devops

Day 35 of #40daysofkubernetes Today I explored how to backup and restore etcd in a Kubernetes cluster. Check out my latest blog to learn how to perform this. A special thanks to Piyush sachdeva and The CloudOps Community #Kubernetes #etcd #DevOps #KubernetesCluster #DevOpsJourney #TechBlog #BackupandRestore #CloudComputing #KubernetesBackup #CloudNative

GitOps for Kafka at Scale From the content: Managing complex infrastructures in distributed systems like Kafka requires more than manual intervention; it requires a scalable and automated approach....[read more] Follow #techbeatly @techbeatly gmsocial, tbsocial

𝗗𝗮𝘆 𝟮: ✋ 🚀 𝗗𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗩𝗼𝗹𝘂𝗺𝗲𝘀 📊💾 𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗩𝗼𝗹𝘂𝗺𝗲𝘀? Kubernetes volumes provide a way to store and persist data in containers. They solve the problem of data persistence in the ephemeral world of containers. Why are Volumes Important? 𝗗𝗮𝘁𝗮 𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝗲: Containers are stateless by nature. Volumes allow data to persist beyond the lifecycle of a pod. 𝗗𝗮𝘁𝗮 𝗦𝗵𝗮𝗿𝗶𝗻𝗴: Volumes enable data sharing between containers within a pod. Stateful Applications: Essential for running databases and other stateful applications in Kubernetes. 𝗞𝗲𝘆 𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗩𝗼𝗹𝘂𝗺𝗲𝘀: 𝗲𝗺𝗽𝘁𝘆𝗗𝗶𝗿: • Temporary storage within a pod • Deleted when the pod is removed • Use case: Sharing data between containers in a pod 𝗵𝗼𝘀𝘁𝗣𝗮𝘁𝗵: Mounts a file or directory from the host node's filesystem Use case: Accessing Docker internals 𝗻𝗳𝘀: Mounts an NFS share into the pod Use case: Persistent storage shared across pods 𝗽𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁𝗩𝗼𝗹𝘂𝗺𝗲 (𝗣𝗩) 𝗮𝗻𝗱 𝗽𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁𝗩𝗼𝗹𝘂𝗺𝗲𝗖𝗹𝗮𝗶𝗺 (𝗣𝗩𝗖): Abstraction for storage resources Separates storage provisioning from pod deployment Use case: Managing storage as a distinct resource 𝗰𝗼𝗻𝗳𝗶𝗴𝗠𝗮𝗽 𝗮𝗻𝗱 𝘀𝗲𝗰𝗿𝗲𝘁: For storing configuration data and sensitive information Use case: Injecting configuration into applications 𝗰𝗹𝗼𝘂𝗱-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝘃𝗼𝗹𝘂𝗺𝗲𝘀 (𝗲.𝗴., 𝗮𝘄𝘀𝗘𝗹𝗮𝘀𝘁𝗶𝗰𝗕𝗹𝗼𝗰𝗸𝗦𝘁𝗼𝗿𝗲, 𝗮𝘇𝘂𝗿𝗲𝗗𝗶𝘀𝗸, 𝗴𝗰𝗲𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁𝗗𝗶𝘀𝗸): Integrate with cloud provider storage services Use case: Leveraging cloud-native storage solutions Understanding these volume types is crucial for effectively managing data in Kubernetes deployments. Each type serves different use cases, from temporary storage to persistent, distributed filesystems. #Kubernetes #CloudNative #DevOps #DataPersistence #ContainerOrchestration #ContinuousLearning

📺 Tune in: Accelerate software delivery with database DevOps for AWS 🚀 Learn how to bring #databaseDevOps to your application pipeline from experts Pete Pickerill (Liquibase Co-Founder and Principal Product Strategist) and Marina Novikova (Sr. Partner Solution Architect at Amazon Web Services (AWS)). They’ll give actionable, nuanced advice to solve challenges like: 🐌 Pipeline slowdowns caused by #database change management 🙌 Launching and refining #DevOps initiatives 🤖 Maximizing #automation investments and filling the gaps 🎛️ Dealing with different types of databases (#SQL, #NoSQL, #datawarehouse, etc.) 🗓️ Thursday, Dec. 7 @ 11am (CT). Includes live demo and Q&A. Sign up: https://hubs.li/Q02929H80

🚀 Kubernetes Architecture: A Quick 1-Minute Guide! Kubernetes is a powerful container orchestration system with three key components: Data Plane, Control Plane, and Worker Nodes. 🌟 Data Plane (etcd) 💻 etcd is the database that stores all Kubernetes data (configurations, manifests, resources). It’s a distributed key-value store where data integrity is ensured by a quorum (a majority of nodes agreeing on state changes). 🌟 Control Plane (The Brain) Manages the entire Kubernetes cluster. Key components include: kube-apiserver: Handles all communication via API. Ensures clients interact with the cluster safely. Kube-controller-manager: Manages resources, state, and replicas. Utilizes leader election to ensure only one active controller. Kube-scheduler: Decides which worker nodes will run the pods based on resources and policies. Cloud-controller-manager: Integrates with cloud providers (only used in cloud environments). 🌟 Nodes. 💻 Worker Nodes (The Executors) Kubelet ensures containers run correctly by communicating between the control plane and container runtime (like Docker). Kube-proxy: Manages networking rules, allowing pods to communicate within and outside the cluster. 🛂 Container Runtime: Runs the actual containers (Docker, Containerd, etc.). Kubernetes orchestrates, but the runtime executes. This architecture makes Kubernetes highly scalable and resilient, ensuring apps stay up and running smoothly. #Kubernetes #ContainerOrchestration #DevOps #CloudComputing

#AWS #DevOps #Kubernetes #K8s #API Kubernetes Architecture A Kubernetes cluster consists of Control plane and Data Plane. Control Plane: The control plane is responsible for container orchestration and maintaining the desired state of the cluster. Let’s understand Control Plane components in depth: API Server: API Server is a Component, which basically exposes your Control Plane & Data Plane. ◉ When you want something to happen in your cluster, like deploying an application or checking on its health, etc. the command is sent to the API Server. ◉ It is the only component that communicates with etcd to store and retrieve critical cluster information. ◉ It is responsible for validating and processing incoming requests and communicating with other Kubernetes components ◉ It ensures that requests are evenly distributed across multiple instances, preventing overload on a single server. ETCD: It stores all configurations, states, and metadata of Kubernetes objects (pods, secrets, daemonsets, deployments, configmaps, statefulsets, etc). ◉ ETCD is like a high-tech dictionary, storing data as key-value pairs. Acts as central repository for Kubernetes.  ◉ It ensures that when you retrieve data, you get a consistent and accurate view of the cluster. ◉ ETCD scales and can handle growing numbers of key-value pairs efficiently. Scheduler: Scheduler serves as a decision-maker for Pod Placement. It is responsible for scheduling Kubernetes pods on worker nodes. ◉ It optimizes resource utilization by considering factors like node capacity, workload balancing, and user-defined policies such as affinity rules. ◉ The Scheduler ensures that Pods are placed in a way that respects these topological constraints. ◉ It strives to distribute Pods evenly across nodes, avoiding situations where some nodes are overloaded while others are underutilized. Controller Manager: The Controller Manager keeps a keen eye on the current state of your cluster. Think of the Replication Controller as a director ensuring that there is the right number of actors (Pods) on the stage (cluster). If there are too few or too many, the Replication Controller makes adjustments. ◉ It also acts as a Garbage Collector which removes old and unused resources, keeping everything neat and efficient. Data Plane: Worker Node is responsible for running containers. It’s a physical or virtual machine that hosts and executes containers. Let’s understand worker node components in depth: ◉ Kubelet: Kubelet is an agent available on every node that acts as a bridge between the master (Control Plane) and the containers running on the node. ◉ Kube-Proxy: Kube-proxy is a network proxy that runs on each node in a Kubernetes cluster. ◉ Container Runtime: The worker node includes a container runtime such as Docker Shim or container. This runtime is the engine that manages the creation, execution, and termination of containers on the node.