Jerry T.’s Post

#Kubernetes is becoming the go-to solution for managing containerized applications. The new post from #Speedscale explores what Kubernetes infrastructure and traffic visibility mean, why they matter and the best practices surrounding them. #DevOps #API https://lnkd.in/etKRgrmV

🌟 Exciting News in Tech! 🌟 Are you curious about Kubernetes and its revolutionary architecture? Let's dive in! 🚀 What is Kubernetes? Kubernetes, also known as K8s, is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It eliminates the manual processes involved in deploying and scaling applications, making it easier to manage containerized workloads efficiently. 🏗️ Architecture Overview: Kubernetes architecture consists of two main components: the Master Node and the Worker Node. The Master Node acts as the control plane, managing the cluster's state and making decisions about scheduling and scaling. The Worker Nodes, on the other hand, host the applications in the form of containers and execute the tasks assigned by the Master Node. The Master Node includes components like the API Server, Scheduler, Controller Manager, and etcd (a distributed key-value store). These components work together to maintain the desired state of the cluster. Meanwhile, each Worker Node contains the Kubelet, responsible for managing containers; a Container Runtime (like Docker); and Kube Proxy for network routing. Please find article below https://lnkd.in/gFmgJDMN 🌐 Why Kubernetes? Kubernetes offers numerous benefits, including: Scalability: Easily scale applications up or down based on demand. High Availability: Ensures applications are highly available and resilient to failures. Portability: Run applications consistently across different environments, whether on-premises, in the cloud, or hybrid. Automation: Automate various tasks related to deployment, scaling, and management, reducing manual effort and potential errors. With its robust architecture and powerful features, Kubernetes has become the de facto standard for container orchestration in today's cloud-native ecosystem. #Kubernetes #CloudNative #TechInnovation #ContainerOrchestration #LinkedInLearning Feel free to engage with your thoughts, questions, and experiences in the comments below! Let's learn and grow together. 🌟

Cloud-Native Infrastructure Trends & Automating Kubernetes with IaC The rise of cloud-native applications is driving a revolution in infrastructure management. Discover how Infrastructure as Code (IaC) and Kubernetes are shaping the future of app deployment and scaling. Read more in my latest blog: Trends In Cloud-Native Infrastructure and How You Can Provision Kubernetes Resources Using IaC Tools (https://bit.ly/3wwrS8a) #cloudnative #kubernetes #infrastructure #IaC #devops

I've been exploring ClusterAPI, a project from the Kubernetes Special Interest Group (SIG), and it's an impressive tool for managing Kubernetes clusters at scale. But what makes it even more powerful is combining it with GitOps for fully automated and declarative cluster management. Managing clusters manually—whether provisioning, upgrading, or handling daily operations—can be overwhelming. That's where ClusterAPI steps in by offering a streamlined approach for: • Provisioning new clusters as easily as deploying applications • Automating upgrades without manual intervention • Centrally managing clusters from a single platform Now, pair that with GitOps, where your infrastructure and cluster configurations are stored in a version-controlled Git repository. Together, ClusterAPI + GitOps provides several key advantages: • Declarative management: All cluster changes are made through Git, ensuring an audit trail and consistency across environments • Self-healing: Any drift from the desired state is automatically detected and corrected • Full automation: With tools like ArgoCD or Flux, any changes in Git trigger automated updates across clusters, enabling continuous delivery for infrastructure By using ClusterAPI with GitOps, you can easily manage multiple clusters, whether on-prem or across clouds, with less manual work and more automation. Curious to learn more? Check out the documentation to get started: ClusterAPI Documentation: https://lnkd.in/gJAvhwT7 #Kubernetes #ClusterAPI #GitOps #CloudNative #DevOps #InfrastructureAsCode #Automation #K8s #CloudComputing #ContinuousDelivery #OpsEfficiency

The way ClusterAPI simplifies the management of Kubernetes clusters by providing declarative APIs for creating, configuring, and managing clusters across various infrastructure providers is critical for running mission critical services and handling n number of clusters using as a code mechanism.

What is Kubernetes ? ✌ Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Originally developed by Google, Kubernetes is now maintained by the Cloud Native Computing Foundation (CNCF) and has become one of the most popular tools for managing containerized workloads in production environments. K8s Architecture Explained in Simple words:   ✌ Pods are the smallest deployable units of computing that you can create and manage in Kubernetes. A Pod (as in a pod of whales or pea pod) is a group of one or more containers, with shared storage and network resources. ✌ The kubelet is the primary "node agent" that runs on each node. It makes sure that the containers are running and healthy. 🤞 The Kubernetes network proxy runs on each node. This reflects services as defined in the Kubernetes API on each node and can do simple TCP, UDP, and SCTP stream forwarding or round robin TCP, UDP, and SCTP forwarding across a set of backends. ✌ etcd is a consistent and highly-available key value store used as Kubernetes' backing store for all cluster data. ✌ The Kubernetes API server validates and configures data for the api objects which include pods, services, replication controllers, and others. ✌ The Kubernetes scheduler is a control plane process which assigns Pods to Nodes. The scheduler determines which Nodes are valid placements for each Pod in the scheduling queue according to constraints and available resources. ✌ The Kubernetes controller manager is a daemon that embeds the core control loops shipped with Kubernetes. àThe cloud-controller-manager is a Kubernetes control plane component that embeds cloud-specific control logic. The cloud controller manager lets you link your cluster into your cloud provider's API(AWS, Azure, GCP etc) Thank you Abhishek Veeramalla for introducing me to the concepts of Kubernetes. #kubernetes #devops #cloudcomputing #containerization

Kubernetes Architecture: Simplified Kubernetes is a powerful platform for managing containerized applications at scale. Let’s break down its architecture into simple, easy-to-understand components: 1. Control Plane: The brain of the Kubernetes cluster, managing and maintaining the desired state of your applications. API Server: The front door to your Kubernetes cluster. All communication goes through the API Server, making it the central management hub. etcd: The cluster’s database, storing all the configuration data, state, and secrets. Think of it as Kubernetes' memory. Scheduler: Decides which node will run a new Pod. It’s like the air traffic controller, ensuring that workloads are evenly distributed. Controller Manager: Watches over the cluster to ensure the desired state matches the actual state. It acts like an automated supervisor that keeps everything in check. Cloud Controller Manager: Manages cloud-specific tasks, such as handling load balancers or storage in cloud environments. 2. Worker Nodes: These are the machines (virtual or physical) where your applications (in the form of Pods) actually run. Kubelet: The node agent that ensures containers are running in a Pod as expected. It’s the worker bee that takes orders from the API Server and gets the job done. Kube Proxy: Manages networking for the Pods, ensuring they can communicate with each other and the outside world. It’s the traffic cop of Kubernetes, directing network traffic efficiently. Container Runtime Interface (CRI): The underlying software that actually runs your containers. This could be Docker, containerd, or another container runtime. It’s the engine that runs the applications within Pods. 3. Communication Tools: Kubectl: The command-line tool that you use to interact with your Kubernetes cluster. Whether you’re deploying applications or checking the health of your cluster, Kubectl is your go-to tool. Cloud Provider API: Allows Kubernetes to interact with cloud resources like load balancers, storage, and more. It’s how Kubernetes speaks to the cloud. In summary, Kubernetes is all about managing your containerized applications efficiently and reliably, whether you're running on a single machine or a massive cluster in the cloud. #aws #devops #kubernetes

Kubecost is a cost-monitoring and optimization tool for Kubernetes that helps track and reduce costs associated with running containerized applications. Integrating with Kubernetes clusters, Kubecost provides real-time insights into resource usage, cost breakdowns by namespace, deployment, service, and more. Here is my medium article to give you a detailed overview of Kubecost. #kubecost #kubernetes #devops

Creating a Kubernetes cluster from scratch in 1 hour using automation #DEVOPS #KUBERNETES #TERRAFORM #ANSIBLE https://lnkd.in/eeqG-x_7

Over 50% of companies experience issues with Kubernetes autoscaling! 🚨 As Kubernetes admins know, autoscaling is crucial for optimizing resource utilization and ensuring application availability. But without proper monitoring and alerting, autoscalers like Karpenter can fail without you even noticing. That's why we at Perfectscale recently overhauled our Karpenter monitoring using Prometheus. By integrating Karpenter metrics into our Prometheus stack, we gained visibility into node claims, utilization, errors - everything needed to know if autoscaling is working properly. We even set up custom alerts to notify us if new nodes can't register, utilization nears nodepool limits, or errors occur talking to the cloud provider. Now if anything interrupts the Karpenter autoscaling, we find out immediately before it causes application disruption. The result? We avoid the pitfalls over half of companies experience with Kubernetes autoscaling. Our apps continue serving users without interruption. And we sleep better at night knowing our cluster autoscaling is under watchful eyes. So take a cue from Perfectscale - tame your Karpenter with Prometheus! Comprehensive monitoring and alerting is the secret sauce for autoscaling confidence. Written by Oleksandr Veleten, DevOps Engineer at Perfectscale. https://hubs.ly/Q02nkT480 #karpenter Grafana Labs Prometheus Group #kubernetes #k8s #autoscaling #devOps #platformengineering