If you want to become a Certified Kubernetes Administrator, or you want to become an EXPERT in Kubernetes, learn Kubernetes from scratch and understand everything, this repo is a good choice.
1. Kubernetes
2. Helm
3. Operator
4. Prometheus
5. EKS
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Many DevOps Engineers struggle to fully understand the structure of an Ansible directory and how everything ties together.
To make it easier, I've broken it down to help you better understand each component and its purpose.
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𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗟𝗶𝘀𝘁 𝗼𝗳 20 𝗺𝗼𝘀𝘁 𝗰𝗼𝗺𝗺𝗼𝗻𝗹𝘆 𝘂𝘀𝗲𝗱 𝐃𝐨𝐜𝐤𝐞𝐫 🐬 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀!!
❤️ 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
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DEV Community
🚀 Mastering DevOps: The Ultimate GitHub Repositories to Accelerate Your Journey♾
Looking to embark on your journey to becoming a proficient DevOps Engineer? Here's a handpicked list...
Are you looking to boost your DevOps skills? I've curated a list of the Most Useful DevOps/Cloud GitHub Repositories that will help you master the art of DevOps, whether you're just getting started or already have experience.
- Realtime DevOps projects for hands-on learning
- Comprehensive guides for CI/CD, Kubernetes, AWS, Azure, and more
- Tool-specific insights and installation guides
- Cheatsheets and setup installers to streamline your workflow
Join our community in mastering these tools and techniques to become a pro DevOps Engineer!
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The repository contains hands-on DevOps projects suitable for individuals at various skill levels, ranging from beginner to advanced.
Projects in this repository showcase the integration of DevOps practices with other cutting-edge technologies such as Machine Learning, Git, GitHub, etc.
The projects included cover a wide array of topics within the DevOps domain, providing practical experience and insights into real-world scenarios.
Whether you're new to DevOps or looking to enhance your skills, this repository offers valuable resources and projects to help you learn and grow in the field.
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➜ Easy to Use: ECS makes it simple to manage containers, especially if you already use AWS. It’s great for quick setups.
➜ Faster Development: With ECS, you can build and launch your apps faster, getting them into production sooner.
➜ Good for Small Teams: If your team doesn’t have a dedicated DevOps person, ECS helps reduce the amount of management you need to do.
➜ Simple Applications: For straightforward apps, ECS provides just the right amount of control without being complicated.
➜ Works Well with AWS: ECS is made for AWS users, so you don’t have to worry about complicated multi-cloud setups.
➜ Cost-Effective: ECS can save you money because there are no extra fees for control planes.
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1707116300601.gif
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Linux's file system is tree-like. The base is "/", with everything else branching off.
/bin
/boot
/dev
/etc
/home
/lib
/media
/mnt
/opt
/proc
/root
/sbin
/srv
/tmp
/usr
/var
cd
ls
mkdir
rmdir
cp
mv
rm
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1714359907264.gif
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𝐀𝐳𝐮𝐫𝐞 𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐑𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞❗️
Planning a microservices architecture on Microsoft Azure? This post dives into the essential network components that will ensure your application is secure, scalable, and highly available.
🔶 Azure's Networking Powerhouse for Microservices:
✔️ Azure Virtual Network (VNet): The foundation for isolating and segmenting your network within Azure. VNets allow secure communication between microservices and, if needed, with the internet.
✔️ Azure Load Balancer or Azure Application Gateway: Distribute traffic evenly across your services or instances.
🔷 Load Balancer: Operates at layer 4 (TCP/UDP), perfect for general traffic distribution.
🔷 Application Gateway: A layer 7 (HTTP/HTTPS) option offering advanced features like SSL termination, WAF (Web Application Firewall), and URL-based routing – ideal for HTTP-based microservices.
✔️ Network Security Groups (NSGs): Enforce security rules at the subnet or network interface level, safeguarding your microservices from unauthorized traffic.
✔️ Azure DNS: Provides name resolution using Microsoft's infrastructure, crucial for service discovery within your microservices architecture.
😎 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Planning a microservices architecture on Microsoft Azure? This post dives into the essential network components that will ensure your application is secure, scalable, and highly available.
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1. Automated Deployment Pipeline:
- Learn to set up CI/CD pipelines using Jenkins, GitLab CI, or GitHub Actions.
- Automate testing, integration, and deployment processes.
2. Containerized Applications with Docker:
- Containerize a web application using Docker.
- Deploy multi-container applications with Docker Compose.
3. Infrastructure as Code (IaC):
- Use Terraform or AWS CloudFormation to manage and provision cloud infrastructure.
- Practice writing modular and reusable code.
4. Kubernetes Cluster Setup:
- Set up a Kubernetes cluster from scratch.
- Deploy and manage applications in a Kubernetes environment.
5. Monitoring and Logging:
- Implement monitoring using Prometheus and Grafana.
- Set up centralized logging with ELK Stack (Elasticsearch, Logstash, Kibana).
6. Configuration Management:
- Use Ansible or Puppet to automate configuration management tasks.
- Write playbooks/manifests to manage server configurations.
7. Version Control and Collaboration:
- Contribute to open-source projects on GitHub.
- Learn best practices for branching, merging, and pull requests.
8. Cloud Services Deployment:
- Deploy and manage applications on AWS, Azure, or Google Cloud.
- Get hands-on experience with services like EC2, S3, RDS, and Lambda.
- Document your projects on GitHub with detailed README files.
- Write blogs or create videos to explain your projects.
- Network with other DevOps enthusiasts and professionals.
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Horizontal scaling involves altering the number of pods available to the cluster to suit sudden changes in workload demands. As the scaling technique involves scaling pods instead of resources, it’s commonly a preferred approach to avoid resource deficits.
Contrary to horizontal scaling, a vertical scaling mechanism involves the dynamic provisioning of attributed resources such as RAM or CPU of cluster nodes to match application requirements. This is essentially achieved by tweaking the pod resource request parameters based on workload consumption metrics.
Cluster scaling involves increasing or reducing the number of nodes in the cluster based on node utilization metrics and the existence of pending pods. The cluster autoscaling object typically interfaces with the chosen cloud provider so that it can request and deallocate nodes seamlessly as needed.
Manual scaling in Kubernetes involves adjusting the number of nodes or resources allocated to a cluster manually. This can be done by adding or removing nodes, adjusting resource requests and limits, and distributing workloads across nodes to optimize performance.
Predictive scaling stands as a transformative approach in the orchestration of cloud-native applications, allowing Kubernetes to not just react to current demands but to anticipate future needs. This forward-looking strategy harnesses the power of data analysis and machine learning to create a more dynamic, efficient, and user-oriented scaling process.
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DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
Photo
\.gitlab-ci\.yml.\.circleci/config\.yml.\.travis\.yml.Remember that the best choice depends on your team's specific needs, existing tools, and preferences. Evaluate factors like ease of setup, integration, scalability, and community support when making your decision!🚀
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The daily activities of a DevOps engineer can vary depending on the specific organization, project, and team structure.
However, here are some common tasks and responsibilities that DevOps engineers typically engage in on a day-to-day basis:
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We add daily Tools Setup, Installations, Guides with each and every commands with clear explanation
More added daily so fork the repository for updates
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1. What is Docker?
2. What are Docker containers?
3. How is Docker different from a virtual machine?
4. What is the purpose of Docker images?
5. What is Docker Hub?
6. How do you create a Docker container?
7. What is a Dockerfile, and how is it used?
8. What is the docker ps command?
9. How do you stop and remove a running Docker container?
10. What is the difference between docker run and docker exec?
11. How do you list all the Docker images on your system?
12. What is the docker-compose command used for?
13. How do you copy files from a Docker container to the host?
14. What is a Docker volume?
15. How do you map ports between your Docker container and host?
16. How do you attach to a running Docker container?
17. What is the Docker Compose file format version?
18. What is a Docker registry?
19. How do you view Docker container logs?
20. What is the docker network command?
21. What is Docker Desktop, and how does it differ from Docker Engine?
22. How do you view Docker container resource usage?
23. What is the purpose of the CMD instruction in a Dockerfile?
24. How do you pull an image from Docker Hub?
25. What is the ENTRYPOINT instruction in a Dockerfile?
26. How do you share data between Docker containers?
27. What is the .dockerignore file used for?
28. How do you create a Docker image from a Dockerfile?
29. What is the docker tag command, and how is it used?
30. How do you run a Docker container in the background (detached mode)?
31. What is the purpose of the EXPOSE instruction in a Dockerfile?
32. How do you remove all stopped containers in Docker?
33. How do you set environment variables for a running Docker container? 34. What is Docker Swarm?
35. How do you check the status of all containers running in Docker?
36. What is the difference between Docker’s COPY and ADD instructions in Dockerfile?
37. What is the docker system prune command?
38. What is the docker-compose up command used for?
39. How do you limit a container’s CPU and memory usage?
40. How do you add a volume to a Docker container?
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How does Docker 🐬 work?
🔢 . Docker Client: This is the interface where users interact with Docker using commands like:
• Docker build: Creates a Docker image based on the configurations defined in a Dockerfile.
• Docker push: Pushes the created image to a remote Docker registry for storage and sharing.
• Docker pull: Pulls an image from the Docker registry to the local environment.
• Docker run: Runs a container from an image on the Docker host.
🔢 . Docker Host:
• Contains the Docker Daemon (or Docker Engine), which manages Docker objects like images, containers, networks, and volumes.
• It communicates with the Docker client to execute commands and manages the lifecycle of containers.
🔢 . Containers and Images:
• Images: Immutable templates (like MySQL, Redis, NGINX) that contain the application code, runtime, libraries, and dependencies.
• Containers: Instances of images that run the application. Each container is an isolated environment where the application functions independently.
🔢 . Docker Registry:
• Stores images and allows them to be shared between different environments.
• The Docker client can push and pull images to/from the registry, enabling distributed deployment of applications.
🔢 . Workflow:
• Build: The Docker client builds an image and stores it locally or in the registry.
• Push: The built image can be pushed to a remote registry for easy access.
• Pull: Images from the registry can be pulled to the local environment as needed.
• Run: The Docker host runs containers from these images, creating isolated environments for each instance.
📱 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
• Docker build: Creates a Docker image based on the configurations defined in a Dockerfile.
• Docker push: Pushes the created image to a remote Docker registry for storage and sharing.
• Docker pull: Pulls an image from the Docker registry to the local environment.
• Docker run: Runs a container from an image on the Docker host.
• Contains the Docker Daemon (or Docker Engine), which manages Docker objects like images, containers, networks, and volumes.
• It communicates with the Docker client to execute commands and manages the lifecycle of containers.
• Images: Immutable templates (like MySQL, Redis, NGINX) that contain the application code, runtime, libraries, and dependencies.
• Containers: Instances of images that run the application. Each container is an isolated environment where the application functions independently.
• Stores images and allows them to be shared between different environments.
• The Docker client can push and pull images to/from the registry, enabling distributed deployment of applications.
• Build: The Docker client builds an image and stores it locally or in the registry.
• Push: The built image can be pushed to a remote registry for easy access.
• Pull: Images from the registry can be pulled to the local environment as needed.
• Run: The Docker host runs containers from these images, creating isolated environments for each instance.
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# Install AWS CLI
pip install awscli
# Configure AWS CLI
aws configure
# List IAM users
aws iam list-users
# Create IAM user
aws iam create-user --user-name <username>
# Attach policy to IAM user
aws iam attach-user-policy --user-name <username> --policy-arn arn:aws:iam::aws:policy/<policy-name>
# List all EC2 instances
aws ec2 describe-instances
# Start an EC2 instance
aws ec2 start-instances --instance-ids <instance-id>
# Stop an EC2 instance
aws ec2 stop-instances --instance-ids <instance-id>
# List all S3 buckets
aws s3 ls
# Upload file to S3 bucket
aws s3 cp <file-path> s3://<bucket-name>/<file-key>
# Download file from S3 bucket
aws s3 cp s3://<bucket-name>/<file-key> <file-path>
# List RDS instances
aws rds describe-db-instances
# Start RDS instance
aws rds start-db-instance --db-instance-identifier <instance-id>
# Stop RDS instance
aws rds stop-db-instance --db-instance-identifier <instance-id>
# List CloudWatch log groups
aws logs describe-log-groups
# Create CloudWatch log group
aws logs create-log-group --log-group-name <log-group-name>
# List Elastic Beanstalk environments
aws elasticbeanstalk describe-environments
# Update environment to new version
aws elasticbeanstalk update-environment --environment-name <env-name> --version-label <version-label>
# List CloudFormation stacks
aws cloudformation describe-stacks
# Create CloudFormation stack
aws cloudformation create-stack --stack-name <stack-name> --template-body file://<template-file>
# Update CloudFormation stack
aws cloudformation update-stack --stack-name <stack-name> --template-body file://<template-file>
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DEV Community
Python for DevOps: A Comprehensive Guide from Beginner to Advanced
Python has gained significant traction in the DevOps ecosystem due to its ease of use, extensive...
Python for DevOps: A Comprehensive Guide from Beginner to Advanced 🐍 💻
Unlock the full potential of Python in DevOps! From automation and CI/CD pipelines to configuration management and Infrastructure as Code, this guide has it all. Perfect for beginners looking to get started and experienced DevOps pros looking to enhance their workflows!
🖥 Check out the article: https://dev.to/prodevopsguytech/python-for-devops-a-comprehensive-guide-from-beginner-to-advanced-2pmm
💡 What You'll Learn:
- Why Python is essential in DevOps
- Python scripting basics and advanced automation
- Integrating Python in CI/CD, monitoring, and IaC
📱 𝐅𝐨𝐥𝐥𝐨𝐰 @prodevopsguy 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 𝐚𝐫𝐨𝐮𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 & 𝐃𝐞𝐯𝐎𝐩𝐬!!! // 𝐉𝐨𝐢𝐧 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐃𝐎𝐂𝐬: @devopsdocs
Unlock the full potential of Python in DevOps! From automation and CI/CD pipelines to configuration management and Infrastructure as Code, this guide has it all. Perfect for beginners looking to get started and experienced DevOps pros looking to enhance their workflows!
- Why Python is essential in DevOps
- Python scripting basics and advanced automation
- Integrating Python in CI/CD, monitoring, and IaC
Start levelling up your DevOps skills with Python today!💪
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- Automates the release process.
- Ensures readiness for deployment at any time.
- Allows manual deployment when needed.
- Automates deployment of every successful code change.
- Directly deploys to production without human intervention.
- Requires high confidence in automated testing.
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