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1. Pengenalan Docker 8
2. Docker Registry 3
3. Docker Container CLI 8
1. Docker CLI (Command Line Interface)
2. Management Docker Container
3. Management Docker Images
4. Run a command in a running container
5. Expose services to outside using ports
6. Copying files/content between container and filesystem
7. Logging, Inspect, & Resource Usage Statistics Containers
8. Run a Container using Environtment File
4. Docker Networks 7
5. Docker Volumes 5
6. Dockerfile 15
1. Build Docker Image Overview
2. Usage docker build
3. FROM Instruction
4. Environtment Replacement
5. Copying Resources
6. Excluding files/directories
7. Label Instruction
8. Execution Instruction
9. CMD vs ENTRYPOINT?
10. Exposing Ports
11. User, Volumes and Working Directory
12. Health Check Instruction
13. Multiple Stage Builds
14. Best practices for writing Dockerfiles
15. Best practices for scanning images
7. Study Kasus: Build docker image 14
1. Build specific docker image by programming languages
2. Build Docker Image for Java Webapp
3. Build Java Web using maven-docker-plugin
4. Build docker image for spring-boot
5. Springboot - using Environtment
6. Springboot - where data such as files/images we stored?
7. Springboot - Using Database
8. Build docker image for Angular Project
9. Angular - Access Rest API
10. Angular - Proxy to backend
11. Build docker image for PHP
12. Build Docker image for Laravel Framework
13. Laravel - Using Frontend & Rest API
14. Laravel - Using Database
8. Docker Compose 19
1. Overview of Docker Compose
2. Get started with Docker Compose
3. Overview of docker-compose CLI
4. Compose file specification and syntax
5. Environment variables in Compose
6. Volume in Compose
7. Share data between Containers in Compose
8. Using sshfs for share data in Compose
9. Using NFS for share data in Compose
10. Networking Overview in Compose file
11. Network links in Compose file
12. Specify custom networks in Compose file
13. Dependency between services in Compose file
14. Build docker image using Compose file
15. Using profiles with Compose file
16. Multiple Compose files to Add & Override attribute
17. Example use case of multiple compose files
18. Scale services using compose command
19. Use Compose in production
9. Study Kasus: Docker Compose 7
10. Docker Context 8
11. Study Kasus: Docker for CI 8
1. Overview of Study Cases using docker for CI
2. Setup environment for CI using Gitlab & Nexus OSS
3. The `.gitlab-ci.yml` file
4. Pipeline: PHP deployment using Gitlab CI
5. Pipeline: Java Web deployment using Gitlab CI
6. Pipeline: spring-boot deploy with Gitlab CI
7. Pipeline: Angular deploy with Gitlab CI
8. Pipeline: Laravel deploy with Gitlab CI
12. Docker Machine 7
13. Study Kasus: Ansible for Docker 4
14. Docker Swarm
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15. Study Kasus: Docker Swarm
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16. Docker on Cloud using GCP
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Overview of Docker machines
Hai semuanya, Setelah sebelumnya kita membahas Docker for Continues Integration (CI) sekarang kita akan membahas tentang Docker machine.
Note: Docker machine sekarang statusnya sudah deprecated atau sudah tidak aktif lagi. Tetapi tenag kita masih bisa menggunakannya kok, karena docker belum menghapus binarynya.
Ya sebelum kita menggunakan Docker machine, kita bahas dulu
- What is Docker Machine?
- Why should I use it?
- What’s the difference between Docker Engine and Docker Machine?
Ok langsung aja kita bahas materi yang pertama
What is Docker Machine?
Docker Machine is a tool that lets you install Docker Engine on virtual hosts, and manage the hosts with
docker-machine commands. You can use Machine to create Docker hosts on your local Mac or Windows box, on your company network, in your data center, or on cloud providers like AWS or Digital Ocean.
You can use Docker Machine to:
- Install and run Docker on Mac or Windows
- Provision and manage multiple remote Docker hosts
- Provision Swarm clusters
docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host.
Point the Machine CLI at a running, managed host, and you can run
docker commands directly on that host. For example, run
docker-machine env default to point to a host called
default, follow on-screen instructions to complete
env setup, and run
docker run hello-world, and so forth.
Why should I use it?
Machine is the best way to provision multiple remote Docker hosts on various flavors of Linux.
Docker Engine runs natively on Linux systems. If you have a Linux box as your primary system, and want to run
docker commands, all you need to do is download and install Docker Engine. However, if you want an efficient way to provision multiple Docker hosts on a network, in the cloud or even locally, you need Docker Machine.
Whether your primary system is Mac, Windows, or Linux, you can install Docker Machine on it and use
docker-machine commands to provision and manage large numbers of Docker hosts. It automatically creates hosts, installs Docker Engine on them, then configures the docker clients. Each managed host (“machine”) is the combination of a Docker host and a configured client.
What’s the difference between Docker Engine and Docker Machine?
When people say “Docker” they typically mean Docker Engine, the client-server application made up of the Docker daemon, a REST API that specifies interfaces for interacting with the daemon, and a command line interface (CLI) client that talks to the daemon (through the REST API wrapper). Docker Engine accepts docker commands from the CLI, such as
docker run <image>,
docker ps to list running containers,
docker images to list images, and so on.
Docker Machine is a tool for provisioning and managing your Dockerized hosts (hosts with Docker Engine on them). Typically, you install Docker Machine on your local system. Docker Machine has its own command line client docker-machine and the Docker Engine client, docker. You can use Machine to install Docker Engine on one or more virtual systems. These virtual systems can be local (as when you use Machine to install and run Docker Engine in VirtualBox on Mac or Windows) or remote (as when you use Machine to provision Dockerized hosts on cloud providers). The Dockerized hosts themselves can be thought of, and are sometimes referred to as, managed “machines”.