Docker & Kubernetes QuickStart: Build, Test & Deploy Mastery

Explore how to use the from command to select a base image from Docker Hub, including Alpine and official images.

Explore using the env command to define environment variables and environment files, enabling reusable paths and exact versioning inside docker builds for reliable containerized configurations.

Install essential packages for a dockerized nginx server, including npm, python, openssl, and supervisor, to support a simple react frontend deployment; outline repeatable setup steps.

Learn to use the Docker copy (COPY) command to add local files to a Docker image, including configuration files, supervisor setups, and an entry point for container startup.

Learn to set safe docker permissions using chown and chmod, mark files executable, apply recursive rights, and switch to a non-root user for secure container deployment.

Set up front-end environment by installing node with nvm, creating a React app in the dashboard folder, building a production build, and copying dashboard files into Docker with proper permissions.

Explore docker build sequencing to maximize cache hits, starting from the linux base image, installing packages, and placing changing app files last for faster builds.

Explore best practices for config files by using variables with curly brackets to replace conflict production folders, manage namespaces like staging, and achieve scalable deployments.

Expose container ports to the outside environment by mapping internal ports to external ones, enabling external clients to reach APIs (for example, 8443 to 443 or 5000 to outside access).

Define an entrypoint to run your application in a Docker container with supervisor, demonstrating command execution and process management. Emphasize reusable Dockerfiles and consistent environments for reliable containers.

Install Docker on your computer by choosing the right Mac option (apple silicon or intel), downloading the Docker desktop app, and confirming Docker is ready to build and run images.

Build and run a docker container by following a cheat sheet, create an image with docker build, run it interactively, expose ports, and debug with docker exec.

Explore using supervisor to run background tasks and manage engine processes, then deploy via staging and master branches, monitor builds with cloud build, and inspect logs for engine requests.

Learn to manage Docker images and containers through the Docker interface, removing containers and unused images with a clean-up action, with no shell commands required.

Choose OpenLinux as the cloud OS for Docker and Kubernetes workloads to maximize security and performance with a lean, container-optimized server and fewer vulnerabilities.

Set up a Google Cloud account and explore the console. Enable the container registry and push your image to Google Cloud to streamline build, test, and deploy workflows.

Authenticate Google Cloud from the terminal, build a Docker image, and push it to Google Cloud Container Registry while tagging versions 0 0 1 to 0 0 3.

Explore how workloads and clusters operate in Kubernetes, learn to deploy a Docker image on a cluster, and expose the workload to the outside world using load balancers.

Enable the Kubernetes engine API in your Google Cloud project, wait about 30 seconds, and access Kubernetes on Google Cloud, noting interface differences by region but keeping the core concepts.

Compare standard and autopilot modes, regional versus zonal deployments, and latency considerations for optimal cluster placement. Autopilot automatically sizes and provisions resources, enabling scalable, managed Kubernetes clusters.

Explore workloads in Kubernetes by deploying each application as a separate workload, see how a frontend container becomes three bots on a cluster, and monitor cpu, memory, and disk usage.

Deploy a hello world container on Kubernetes by editing the workload yaml, configuring the image and resource requests and limits, and performing rolling updates.

Authenticate to Google Cloud, fetch cluster credentials, access the workload via kubectl, view logs, fix port eight to eighty-eight, redeploy, perform a rolling update, and expose the new IP.

Expose your Kubernetes apps by creating a service and a load balancer, map external and target ports, and reserve a static external IP for a stable front-end.

Add a readiness probe in the Kubernetes YAML to monitor health with periodic http checks; set a 30-second delay, 1-second interval, and a failure threshold for readiness.

Monitor cluster cpu and memory usage, compare resource requests to actual usage, and adjust limits to optimize performance and reduce costs, preparing for auto scaling.

Learn how to configure auto scaling in kubernetes engine, setting min and max pods, and using cpu and memory metrics (with optional external metrics) to scale workloads efficiently.

Learn to secure and deploy environment files, secrets, and config maps in kubernetes by creating, loading, and mounting env credentials into workloads, enabling shared, secure configuration across multiple deployments.

Learn how GitHub workflows enable continuous integration and deployment from staging to production, with automated Docker image builds, pushes, and one-click promotions on merge.

Create and push the project to a GitHub repository, configure the main branch and origin, and verify Docker image builds, while addressing ignored or missing files and folder initialization.

Define auto deploy steps using a cloud build yaml to guide Google Cloud through building and caching Docker images, deploying to Kubernetes, and managing production configurations with substitutions.

Push a new git-committed image to Kubernetes using cloud builds, update the deployment with the new image, and monitor rollout status while troubleshooting permissions and container naming mismatches.

Explore how Kubernetes namespaces enable separate staging and production environments, manage deployments, secrets, and config maps, and implement staging pipelines with Cloud Build triggers.

Scale cloud builds with Google Cloud worker pools by increasing CPU and memory for large Docker images, and apply the config in Cloud Build YAML for staging and production.

Master deploying a Laravel app on Docker and Kubernetes, with backend workload setup, Docker and Nginx configurations, composer installation, and a robust build and deployment workflow for production and staging.

Compare nginx and Apache to optimize web server performance, showing how nginx sustains fast response times under high load and why it is chosen for efficient deployment.

Leverage established templates with reusable configuration and environment files to accelerate deploying Laravel and related services, reducing setup from scratch to minutes.

Securely manage sensitive data on your cluster by creating encrypted credentials in Kubernetes secrets, mounting them into deployments, and updating environment configs without exposing keys in GitHub.

Deploy Redis on Kubernetes by adjusting memory and CPU resource requests. Build Docker images, set up Cloud Build triggers, expose port 6379, and test with Telnet.