GCP

The architecture of Kubernetes is divided into two main parts: 1. Control Plane Components The Control Plane is the brain of Kubernetes — responsible for managing the overall state of the cluster and orchestrating all activities. 1.1 kube-apiserver Acts as the central communication gateway of the system. All requests from kubectl, the Dashboard, CI/CD pipelines, etc., are sent through this component. Responsible for: Authentication Authorization Reading/writing data from/to etcd Forwarding requests to other components Example: You run kubectl get pods → the request goes to the kube-apiserver. ...

When learning Kubernetes, there are two core concepts you should understand: Kubernetes Object Model and Declarative Management. Let’s break down both of these. 1. Kubernetes Object Model Everything in Kubernetes is an object, and these objects are managed via YAML or JSON definitions. They represent the resources in your system. Cluster A cluster is a group of machines (nodes) consisting of: Control Plane (master) - responsible for managing the system. Worker Nodes - where your applications run. Node A node is a physical or virtual machine within a cluster. Each node includes: ...

In Google Cloud, Billing is the system that helps you manage costs, payments, and budgets when using services on Google Cloud Platform (GCP), such as Compute Engine, BigQuery, Cloud Storage, and more. Below are the four most important components in Google Cloud Billing: 1. Budget Allows you to set a spending limit for a specific time period (e.g., month, quarter) for a project or billing account. Purpose: Avoid spending beyond your planned budget. Example: You’re building a backend for a crawling system running on GCP, using multiple VMs or Cloud Functions. To control cost, you set a $500/month budget to track your expenses. 2. Alert Alerts are automatically triggered when spending exceeds a defined percentage of the budget (e.g., 50%, 90%, 100%). Purpose: Notify you when costs spike unexpectedly — possibly due to a bug or misconfiguration. Example: If the cost of your backend on Cloud Run reaches 90% of the $500 budget, you’ll receive an email notification to take action. ...

In Google Cloud, Compute Offering is a set of services that help you run workloads (like applications, APIs, batch jobs, etc.) on Google’s host infrastructure. Depending on your workload and requirements, you can choose from the options below: 1. Compute Engine (IaaS - Infrastructure as a Service) A virtual machine where you have full permission to configure the environment. High level of control, similar to traditional hosting on the cloud. Use case: Configure OS in detail, install custom software, need full system control. Example: Run a Node.js/Golang server, cron job, or backend AI model training. AWS equivalent: EC2 2. App Engine (PaaS - Platform as a Service) A platform for running applications where you only need to deploy code — Google handles everything else (scaling, patching, infrastructure, etc.). Low level of control — just push your code, no need to manage servers. Use case: Rapid development, no infrastructure management needed. Example: Run a small API server, REST API, or MVP web app. AWS equivalent: Elastic Beanstalk 3. Cloud Run (Serverless Containers) Run containers (e.g., Docker) in a serverless model. Billing is based on request duration. Medium level of control — you manage the container image, while Google handles scaling and infrastructure. Use case: Leverage the benefits of containers + serverless for lightweight backends or microservices. Example: Run an API service, webhook receiver, or AI inference container. AWS equivalent: App Runner / Fargate 4. Google Kubernetes Engine (GKE) (CaaS - Container as a Service) Run containerized applications with Kubernetes. Google manages the control plane. High level of control — you can fully configure your cluster, while Google manages some parts of it. Use case: Need orchestration, CI/CD pipelines, or complex multi-service applications. Example: Run a microservices system, CI job runners, or real-time data pipelines. AWS equivalent: EKS 5. Cloud Functions (FaaS - Function as a Service) Write and deploy small functions that are triggered by events (HTTP, Pub/Sub, Cloud Storage, etc.). Extremely easy to use — just write a function, no need to manage infrastructure. Use case: Handle small event-driven logic, time-based triggers, or system integration tasks. Example: Auto-resize images, handle webhooks from Telegram/Stripe, send emails on user registration. AWS equivalent: Lambda