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Kubernetes Cluster Election
💡 Choosing the Right K8s Environment for Your Needs
K8s offers various technologies tailored to different tasks, each with its own characteristics and advantages.
Some popular options:
1️⃣ Minikube (https://lnkd.in/ePQKyEZ7)
> Compatible with Linux, Windows, and macOS
> Uses virtualization to deploy a cluster on a Linux virtual machine
> Suitable for Linux without virtualization support
2️⃣ Kubeadm (https://lnkd.in/epyumfKZ)
> The official CNCF tool for provisioning Kubernetes clusters
> Offers flexibility for various cluster configurations (single node, multi-node, HA, self-hosted, etc.)
> Ideal for launching minimal viable Kubernetes clusters
3️⃣ Kops (Kubernetes Operations) (https://lnkd.in/e7ApRVJP)
> Provides tools for installing, operating, and removing Kubernetes clusters on cloud platforms like AWS, Google Cloud Platform, OpenStack, and DigitalOcean
4️⃣ Microk8s (https://microk8s.io)
> Similar to Minikube, it creates single-node clusters
> Features its own set of add-ons as configuration plugins
> Exclusive to Linux environments
5️⃣ K3s (https://k3s.io)
> Works on any Linux distribution without external dependencies
> Replaces Docker with containerd as the container runtime and uses sqlite3 as the default database
> Lightweight, consuming only 512MB of RAM and 200MB of disk space.
6️⃣ Kind (Kubernetes-in-Docker) (https://kind.sigs.k8s.io)
> Runs Kubernetes clusters in Docker containers
> Supports multi-node and High-Availability clusters
> Compatible with Windows, Mac, and Linux as it runs on top of Docker
7️⃣ K3d (https://k3d.io)
> A project aiming to dockerize K3s
The choice of the Kubernetes environment depends on your project's specific needs.
✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs
K8s offers various technologies tailored to different tasks, each with its own characteristics and advantages.
Some popular options:
> Compatible with Linux, Windows, and macOS
> Uses virtualization to deploy a cluster on a Linux virtual machine
> Suitable for Linux without virtualization support
> The official CNCF tool for provisioning Kubernetes clusters
> Offers flexibility for various cluster configurations (single node, multi-node, HA, self-hosted, etc.)
> Ideal for launching minimal viable Kubernetes clusters
> Provides tools for installing, operating, and removing Kubernetes clusters on cloud platforms like AWS, Google Cloud Platform, OpenStack, and DigitalOcean
> Similar to Minikube, it creates single-node clusters
> Features its own set of add-ons as configuration plugins
> Exclusive to Linux environments
> Works on any Linux distribution without external dependencies
> Replaces Docker with containerd as the container runtime and uses sqlite3 as the default database
> Lightweight, consuming only 512MB of RAM and 200MB of disk space.
> Runs Kubernetes clusters in Docker containers
> Supports multi-node and High-Availability clusters
> Compatible with Windows, Mac, and Linux as it runs on top of Docker
> A project aiming to dockerize K3s
The choice of the Kubernetes environment depends on your project's specific needs.
Once you understand K8s basics, the next step is to create a cluster, which can be done both locally and in the cloud.
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Traffic control in the digital world can feel like solving a complex puzzle.
A reverse proxy sits in front of your servers, handling client requests. Think of it as a middleman.
𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬:
When to Use It:
- You need to protect your backend infrastructure from direct exposure.
- You’re managing HTTP/HTTPS traffic effectively.
A load balancer ensures requests are spread across multiple servers to prevent overload. It's like directing traffic during rush hour.
Key Features:
When to Use It:
- You have multiple servers and need to maintain consistent performance.
- Uptime and reliability are your top priorities.
API Gateway acts as the single entry point for APIs, handling all the heavy lifting. It’s the concierge for your microservices.
Key Features:
When to Use It:
- You’re managing multiple APIs and need centralized control.
- You want to offload cross-cutting concerns like security or monitoring.
- Use Reverse Proxy if you need enhanced security and basic traffic forwarding.
- Use Load Balancer to distribute traffic and ensure availability.
- Use API Gateway for a powerful, API-first architecture, especially with microservices.
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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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As the year draws to a close, we want to express our heartfelt gratitude to each one of you for being an integral part of this amazing journey. Your enthusiasm, knowledge sharing, and passion for DevOps have made this community truly special.
May this festive season bring you joy, peace, and success in all your endeavors. Let’s continue building, learning, and growing together in the year to come.
Wishing you and your loved ones a Merry Christmas and a prosperous New Year!🎉
Stay inspired and keep automating!
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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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DEV Community
Automating Infrastructure with AWS CloudFormation: A Beginner's Guide
Automating infrastructure is a cornerstone of modern DevOps practices, and AWS CloudFormation is a...
"Automating Infrastructure with AWS CloudFormation: A Beginner's Guide"
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- 𝑷𝒖𝒔𝒉: Send your local commits to the remote repo.
- 𝑷𝒖𝒍𝒍: Grab the latest changes from remote. It's actually fetch + merge in one go.
- 𝑭𝒆𝒕𝒄𝒉: Download changes, but don't apply them yet.
- 𝑴𝒆𝒓𝒈𝒆: Combine those fetched changes with your work.
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The working of static pods can be explained with the help of steps below:
Static pods are not created through the Kubernetes API server, so they do not have the full capabilities of API-managed pods. However, the kubelet creates a 𝐦𝐢𝐫𝐫𝐨𝐫 𝐩𝐨𝐝 in the API server for visibility, allowing tools like 𝐤𝐮𝐛𝐞𝐜𝐭𝐥 to display their status.
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Ever had something work perfectly on your machine but fail elsewhere?
With Docker, you’re using the same environment locally, in CI/CD, and production. No more "it works on my machine" issues!
Each project gets its own container, avoiding dependency clashes and system-level config issues.
Need a build from months ago? Docker’s versioned environments let you recreate it instantly.
Docker ensures clean builds every time, avoiding leftover artifacts. Reusable images mean faster pipelines!
Whether it’s Linux, Windows, or ARM, Docker handles it all.
Run as many containers as you need—parallel builds without a hitch.
Containers are isolated, minimizing risks to the host. Crucial for handling sensitive data!
Develop, test, and deploy anywhere—Docker ensures consistency across all platforms.
Need different tools for different projects? Docker packages custom toolchains with ease.
New team members? Just give them the Docker image—they’ll be coding in no time!
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↳ In GitOps world everyone is aware about the ArgoCD.
It's has tremendous features due to which its first choice of almost every DevOps engineer.
1. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 of applications to specified target environment in multiple clusters
Support for multiple config management/templating tools-->
• Kustomize
• Helm
• Ksonnet
• Jsonnet
• Plain-YAML
2. 𝗦𝗦𝗢 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 :
• OIDC
• OAuth2
• LDAP
• SAML 2.0
• GitHub
• GitLab
• Microsoft
3. 𝗠𝘂𝗹𝘁𝗶-𝘁𝗲𝗻𝗮𝗻𝗰𝘆 𝗮𝗻𝗱 𝗥𝗕𝗔𝗖 policies for authorization
4. 𝗥𝗼𝗹𝗹𝗯𝗮𝗰𝗸/𝗥𝗼𝗹𝗹-𝗮𝗻𝘆𝘄𝗵𝗲𝗿𝗲 to any application configuration committed in Git repository.
• Health status analysis of application resources
5. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 𝗱𝗿𝗶𝗳𝘁 detection and visualization
6. Out-of-the-box Prometheus metrics
7. Audit trails for application events and API calls
8. PreSync, Sync, PostSync hooks:
• Support complex application rollouts
-> blue/green
-> canary upgrades
9. Web-hook integration
-> GitHub
-> BitBucket
-> GitLab
10. CLI and access tokens for automation and Cl integration
11. Web UI which provides real-time view of application activity
12. Automated or manual syncing of applications to its desired state
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DevOps & Cloud (AWS, AZURE, GCP) Tech Free Learning
Photo
1. What is Google Cloud Platform (GCP)?
2. What are the key services offered by GCP?
3. What is Google Compute Engine?
4. What is Google Cloud Storage?
5. Explain the difference between Google Cloud Storage and Persistent Disks.
6. What is Google App Engine?
7. What are Google Cloud Regions and Zones?
8. What is Google Kubernetes Engine (GKE)?
9. What is Google Cloud IAM (Identity and Access Management)?
10. How does Google Cloud VPC work?
11. What is Google BigQuery?
12. What is Google Cloud Pub/Sub?
13. What is Google Cloud Functions?
14. Explain the concept of Preemptible VMs in GCP.
15. What is Google Cloud Datastore?
16. What is Google Cloud SQL?
17. How does Google Cloud Load Balancing work?
18. What is Google Cloud Spanner?
19. What is the Google Cloud Marketplace?
20. What is Google Cloud Memorystore?
21. What is Google Cloud Bigtable?
22. What is Google Cloud Endpoints?
23. What is Google Cloud Dataflow?
24. How does Google Cloud Monitoring work?
25. What is Google Cloud AutoML?
26. What is Google Cloud Run?
27. Explain the difference between Google App Engine and Google Cloud Functions.
28. What is Google Cloud Interconnect?
29. What is Google Cloud Armor?
30. What is Google Cloud Vision API?
31. How do you secure data in GCP?
32. What is the difference between Google Cloud SQL and Google Cloud Spanner?
33. What is Google Cloud Deployment Manager?
34. How does Google Cloud DNS work?
35. What is Google Cloud CDN?
36. Explain the concept of Google Cloud Firestore.
37. What is Google Cloud Composer?
38. What is the difference between Google Cloud Datastore and Google Cloud Firestore?
39. What is Google Cloud Data Fusion?
40. What is Google Cloud Resource Manager?
41. What is Google Cloud Operations Suite (formerly Stackdriver)?
42. What is Google Cloud VPN?
43. What is Google Cloud NAT?
44. Explain the concept of VPC peering in GCP.
45. What is Google Cloud Filestore?
46. How does Google Cloud Key Management Service (KMS) work?
47. What is Google Cloud Identity?
48. What is Google Cloud Healthcare API?
49. How do you manage access control in GCP?
50. What is Google Cloud Traffic Director?
51. What is Google Cloud Anthos?
52. What is Google Cloud Tasks?
53. Explain the concept of Google Cloud Secret Manager.
54. What is Google Cloud Transfer Service?
55. What is Google Cloud Apigee?
56. What is Google Cloud Data Labeling Service?
57. How does Google Cloud Profiler work?
58. What is the difference between Google Cloud SQL and Google BigQuery?
59. What is Google Cloud Logging?
60. What is Google Cloud Asset Inventory?
61. What is the Google Cloud Shared VPC?
62. How do you implement CI/CD in GCP?
63. What is Google Cloud Service Directory?
64. What is the role of Google Cloud in machine learning?
65. What is Google Cloud Tensor Processing Unit (TPU)?
66. Explain the concept of multi-region deployments in GCP.
67. How do you optimize costs in GCP?
68. What is Google Cloud Private Catalog?
69. How do you manage hybrid cloud deployments with GCP?
70. What are the best practices for securing a GCP environment?
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A Kubernetes End-to-End (E2E) project for deploying a 2048 game app on Amazon Elastic Kubernetes Service (EKS) involves setting up, deploying, and managing the popular 2048 game application on a Kubernetes cluster running on AWS EKS. This project aims to demonstrate how to containerize a web application, deploy it on EKS, manage the cluster, and expose the application to users.
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1. terraform init: Initializes a Terraform working directory.
2. terraform validate: Validates the Terraform configuration files.
3. terraform fmt: Formats the Terraform configuration files.
4. terraform apply: Applies the configuration to create or update infrastructure.
5. terraform destroy: Destroys the infrastructure managed by Terraform.
6. terraform refresh: Refreshes the Terraform state to match the actual infrastructure.
7. terraform show: Shows the Terraform state and configuration.
8. terraform state list: Lists the resources in the Terraform state.
9. terraform state show: Shows the details of a specific resource in the Terraform state.
10. terraform state rm: Removes a resource from the Terraform state.
11. terraform state mv: Moves a resource from one state to another.
12. terraform get: Downloads and installs Terraform modules.
13. terraform module: Manages Terraform modules.
14. terraform module init: Initializes a Terraform module.
15. terraform providers: Lists the available Terraform providers.
16. terraform provider: Manages Terraform providers.
17. terraform provider init: Initializes a Terraform provider.
18. terraform workspace: Manages Terraform workspaces.
19. terraform workspace new: Creates a new Terraform workspace.
20. terraform workspace select: Selects a Terraform workspace.
21. terraform debug: Enables debug logging for Terraform.
22. terraform logs: Shows the Terraform logs.
23. terraform console: Opens a Terraform console for interactive debugging.
24. terraform import: Imports existing infrastructure into Terraform.
25. terraform export: Exports the Terraform state to a file.
26. terraform version: Shows the Terraform version.
27. terraform help: Shows the Terraform help.
28. terraform upgrade: Upgrades Terraform to the latest version.
29. terraform console: Opens a Terraform console for interactive debugging.
30. terraform graph: Generates a graph of the Terraform configuration.
31. terraform output: Shows the output of a Terraform configuration.
32. terraform cli: Manages the Terraform CLI.
33. terraform cli config: Configures the Terraform CLI.
34. terraform config: Manages the Terraform configuration.
35. terraform config init: Initializes a Terraform configuration.
36. terraform state backend: Manages the Terraform state backend.
37. terraform state backend init: Initializes a Terraform state backend.
38. terraform workspace: Manages Terraform workspaces.
39. terraform workspace new: Creates a new Terraform workspace.
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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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- Deployment manifest files
- Jenkins deployments & configurations
- Kubernetes Ingress files
- Realtime projects manifest files
- Helm charts for any application
- End to End Manifest files for any applications
- Includes AWS ELK Stack (Elasticsearch, Logstash, Kibana)
- Network service configurations templates
- Application monitoring templates for any applications
- Complete application launch manifest files for Realtime projects
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The diagram above illustrates the typical workflow.
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Pods, ReplicaSets, Deployments: Basic building blocks of Kubernetes clusters.
PersistentVolumes, StatefulSets: Managing stateful applications and data within Kubernetes.
Nodes, Controllers, Scheduler: Core infrastructure management and control mechanisms.
RBAC, Network Policies: Ensuring secure access and communication within clusters.
HorizontalPodAutoscaler, Ingress Controllers: Automatic scaling and efficient traffic distribution.
Velero (formerly Heptio Ark): Tools for data protection and disaster recovery strategies.
Services, DNS, CNI: Network configuration and communication between Kubernetes components.
Helm, Operators: Managing application packages and custom resources.
Prometheus, Grafana: Tools for monitoring cluster health and performance.
Jenkins, GitLab CI/CD: Integrating CI/CD pipelines for automated application deployment.
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