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Showing posts with the label gke

Google Cloud Platform Practice Series

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Introduction Google Cloud Platform (GCP) is a suite of cloud computing services provided by Google. It allows you to build, deploy, and scale applications, websites, and services on the same infrastructure that Google uses internally for its end-user products like Google Search, Gmail, and YouTube. Key Features of GCP Compute Services: Includes virtual machines (VMs) with Google Compute Engine, serverless computing with Google Cloud Functions, and container orchestration with Google Kubernetes Engine (GKE). Storage and Databases: Offers various storage options like Google Cloud Storage for object storage, Google Cloud SQL for managed relational databases, and Google Bigtable for NoSQL databases. Networking: Provides a global network infrastructure with services like Virtual Private Cloud (VPC), Cloud Load Balancing, and Cloud CDN for content delivery. Big Data and Machine Learning: Includes tools like BigQuery for data warehousing, Dataflow for stream and batch data processing, and AI

Helm for beginer - Deploy nginx to Google Kubernetes Engine

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Introduction Helm is a package manager for Kubernetes , which simplifies the process of deploying and managing applications on Kubernetes clusters. Helm uses a packaging format called charts , which are collections of files that describe a related set of Kubernetes resources. Key Components of Helm Charts : Helm packages are called charts. A chart is a collection of files that describe a related set of Kubernetes resources. A single chart might be used to deploy something simple, like a memcached pod, or something complex, like a full web app stack with HTTP servers , databases, caches, and so on. Values : Charts can be customized with values, which are configuration settings that specify how the chart should be installed on the cluster. These values can be set in a ` values.yaml ` file or passed on the command line. Releases : When you install a chart, a new release is created. This means that one chart can be installed multiple times into the same cluster, and each can be indep

Deploy React Application to Google Kubernetes Engine

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Introduction In this article, I will guide you through deploying a React Application to Google Kubernetes Engine (GKE) . Previously, I wrote an article about deploying a NodeJS Application to GKE , which you can refer to for some basic information before continuing. Steps to Follow The process is quite similar to deploying a NodeJS Application and includes the following steps: Create a React Application Build a Docker image Push the Docker image Deploy the Docker image to GKE You will notice that when working with Kubernetes , the main difference is in the step where you build the Docker image . Depending on the application you need to deploy, there are different ways to build the Docker image . However, the common point is that once you build the Docker image , you have completed almost half of the process. This is because the subsequent steps involving Kubernetes are entirely the same. Detailed Process 1. Create a React Application In this step, you can either use an existing R

Using Terraform to deploy a docker image on Google Kubernetes Engine

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Introduction to Terraform Terraform is an Infrastructure as Code (IaC) tool developed by HashiCorp . It allows you to build, change, and version your infrastructure safely and efficiently. Here are some key features of Terraform : Human-Readable Configuration Files : Terraform lets you define both cloud and on-prem resources in human-readable configuration files that you can version, reuse, and share. Multi-Cloud Support : Terraform can manage infrastructure on multiple cloud platforms. Providers enable Terraform to work with virtually any platform or service with an accessible API. Lifecycle Management : The core Terraform workflow consists of three stages: Write : Define resources across multiple cloud providers and services. Plan : Terraform creates an execution plan describing what it will create, update, or destroy. Apply : On approval, Terraform performs the proposed operations in the correct order, respecting any resource dependencies. State Management : Terraform keeps track

Deploying a NodeJS Server on Google Kubernetes Engine

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Introduction to GKE Google Kubernetes Engine (GKE) is a managed Kubernetes service provided by Google Cloud Platform , facilitating simple and efficient deployment of Docker images. We only need to provide some configuration for the number of nodes, machine types, and replicas to use. Some Concepts Cluster A Cluster is a collection of Nodes where Kubernetes can deploy applications. A cluster includes at least one Master Node and multiple Worker Nodes . The Master Node is used to manage the Worker Nodes . Node A Node is a server in the Kubernetes Cluster. Nodes can be physical servers or virtual machines. Each Node runs  Kubernetes , which is responsible for communication between the Master Node and Worker Node , as well as managing Pods and containers running on it. Pod A Pod is the smallest deployable unit in Kubernetes . Each Pod contains one or more containers, typically Docker containers. Containers in the same Pod share a network namespace, meaning they have the same