♾ Continuous Delivery vs. Continuous Deployment

➡️ Continuous Delivery: It ensures that your code changes are always deployable, providing a reliable and automated process for building, testing, and preparing for release. However, the deployment to production is a manual step, allowing for human intervention and control over when changes go live.

➡️ Continuous Deployment: It takes automation to the next level by automatically deploying every successful change to production. This means that once code passes all tests and checks, it's automatically pushed into production without the need for manual intervention.


⭐ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🐬 6 Tips to 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐘𝐨𝐮𝐫 𝐃𝐨𝐜𝐤𝐞𝐫𝐟𝐢𝐥𝐞

➡️𝐔𝐬𝐞 𝐌𝐮𝐥𝐭𝐢𝐬𝐭𝐚𝐠𝐞 𝐁𝐮𝐢𝐥𝐝𝐬:
- Utilize multiple stages to reduce the size of the final image.
- Keep the final image lean by copying only necessary artifacts from previous stages.

➡️𝐌𝐢𝐧𝐢𝐦𝐢𝐳𝐞 𝐋𝐚𝐲𝐞𝐫 𝐒𝐢𝐳𝐞:
- Combine multiple RUN commands using && to minimize the number of layers.
- Clean up unnecessary files and dependencies within the same RUN command.

➡️𝐋𝐞𝐯𝐞𝐫𝐚𝐠𝐞 .𝐝𝐨𝐜𝐤𝐞𝐫𝐢𝐠𝐧𝐨𝐫𝐞:
- Exclude unnecessary files and directories from the build context using .dockerignore.
- This reduces the size of the build context and speeds up the build process.

➡️𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐳𝐞 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐈𝐦𝐚𝐠𝐞 𝐋𝐚𝐲𝐞𝐫𝐬:
- Place frequently changing dependencies lower in the Dockerfile to leverage Docker's layer caching mechanism.
- Avoid unnecessary package installations that could bloat the image size.

➡️𝐔𝐬𝐞 𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐓𝐚𝐠𝐬 𝐟𝐨𝐫 𝐁𝐚𝐬𝐞 𝐈𝐦𝐚𝐠𝐞𝐬:
- Specify precise version tags for base images to ensure consistency and avoid unexpected updates.
- Pinning versions mitigates the risk of breaking changes introduced by newer versions.

➡️𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐈𝐦𝐚𝐠𝐞 𝐒𝐢𝐳𝐞:
- Use smaller base images like Alpine Linux where possible to reduce the overall size of the image.
- Remove unnecessary dependencies and files from the final image to make it as lightweight as possible.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

♾ 𝐃𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐭𝐨𝐨 𝐬𝐥𝐨𝐰? 𝐂𝐈/𝐂𝐃 𝐢𝐬 𝐲𝐨𝐮𝐫 𝐥𝐚𝐮𝐧𝐜𝐡𝐩𝐚𝐝 𝐭𝐨 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞! 🚀

Are endless manual deployments and sluggish release cycles holding your team back? You're not alone! But fear not, there's a solution that can turn your development process into a well-oiled machine: CI/CD (Continuous Integration/Continuous Delivery).

The benefits are out of this world:
⏩Faster releases: Get features to users sooner, keeping them engaged and competitive.

⏩Improved quality: Catch and fix bugs early, reducing downtime and frustration.

⏩Happier developers: Less manual work means more time for innovation and creativity.


🌐𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

✅Terraform commands used on a daily basis: ✨

1. terraform init:
- Initializes a working directory containing Terraform configuration files.

2. terraform plan:
- Generates an execution plan, outlining actions Terraform will take.

3. terraform apply:
- Applies the changes described in the Terraform configuration.

4. terraform destroy:
- Destroys all resources described in the Terraform configuration.

5. terraform validate:
- Checks the syntax and validity of Terraform configuration files.

6. terraform refresh:
- Updates the state file against real resources in the provider.

7. terraform output:
- Displays the output values from the Terraform state.

8. terraform state list:
- Lists resources within the Terraform state.

9. terraform show:
- Displays a human -readable output of the current state or a specific resource’s state.

10. terraform import:
- Imports existing infrastructure into Terraform state.

11. terraform fmt:
- Rewrites Terraform configuration files to a canonical format.

12. terraform graph:
- Generates a visual representation of the Terraform dependency graph.

13. terraform providers:
- Prints a tree of the providers used in the configuration.

14. terraform workspace list:
- Lists available workspaces.

15. terraform workspace select:
- Switches to another existing workspace.

16. terraform workspace new:
- Creates a new workspace.

17. terraform workspace delete:
- Deletes an existing workspace.

18. terraform output:
- Retrieves output values from a module.

19. terraform state mv:
- Moves an item in the state.

20. terraform state pull:
- Pulls the state from a remote backend.

21. terraform state push:
- Pushes the state to a remote backend.

22. terraform state rm:
- Removes items from the state.

23. terraform taint:
- Manually marks a resource for recreation.

24. terraform untaint:
- Removes the ‘tainted’ state from a resource.

25. terraform login:
- Saves credentials for Terraform Cloud.

26. terraform logout:
- Removes credentials for Terraform Cloud.

27. terraform force -unlock:
- Releases a locked state.

28. terraform import:
- Imports existing infrastructure into your Terraform state.

29. terraform plan -out:
- Saves the generated plan to a file.

30. terraform apply -auto -approve:
- Automatically applies changes without requiring approval.

31. terraform apply -target=resource:
- Applies changes only to a specific resource.

32. terraform destroy -target=resource:
- Destroys a specific resource.

33. terraform apply -var=”key=value”:
- Sets a variable’s value directly in the command line.

34. terraform apply -var -file=filename.tfvars:
- Specifies a file containing variable definitions.

35. terraform apply -var -file=filename.auto.tfvars:
- Automatically loads variables from a file.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🐧 𝗟𝗶𝗻𝘂𝘅 𝗕𝗼𝗼𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗶𝗻 𝘁𝗵𝗲 𝘀𝗶𝗺𝗽𝗹𝗲𝘀𝘁 𝘄𝗮𝘆 🚀

Here are the 8 steps to understand the Linux boot process in the easiest manner.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

📣 Kubernetes Services and Ingress Demystified.

Understanding how to expose Kubernetes services is key for building robust applications.
In this post,We'll walk through the main service types and ingress in Kubernetes.

Services in Kubernetes allow pods to communicate with each other and provide a stable endpoint that doesn't change as pods are created or deleted. There are several types of services:

➡️ClusterIP: Exposes the service on a cluster-internal IP only. This makes the service only reachable from within the cluster.

➡️NodePort: Exposes the service on each Node's IP at a static port. You can contact the NodePort service from outside the cluster by requesting <NodeIP>:<NodePort>.

➡️LoadBalancer: Creates an external load balancer and assigns a fixed, external IP to the service. The load balancer routes to NodePorts of cluster nodes.

➡️ExternalName: Maps the service to the contents of the externalName field (e.g. foo.bar.example.com), by returning a CNAME record.

Ingress is another Kubernetes resource that allows you to route external traffic to services based on HTTP rules. Ingress exposes HTTP and HTTPS routes from outside the cluster to services within the cluster. Traffic routing is controlled by rules defined on the Ingress resource.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

📌 Building Strong and adaptable Microservices with Java and Spring

While building robust and scalable microservices can seem complex, understanding essential concepts empowers you for success. This post explores crucial elements for designing reliable distributed systems using Java and Spring frameworks.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

Let's face it: the only thing more relentless than the pace of innovation in DevOps is our collective ability to find excuses not to keep up with it! 🏃💨

Embrace the chaos, love the learning, and remember: if DevOps feels like it's pushing you out of your comfort zone, it's probably because your comfort zone could use a bit of cloud-based scalability and automation. 😜


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 often suffer from environment inconsistencies, portability issues, and complex deployments.

➡️Virtual machines (VMs) offer some isolation, but they're resource-hungry and slow.
Enter 𝗗𝗼𝗰𝗸𝗲𝗿, the containerization platform that has revolutionized software development.

➡️𝗪𝗵𝗮𝘁 𝗶𝘀 𝗗𝗼𝗰𝗸𝗲𝗿? 🐬
Docker 𝗽𝗮𝗰𝗸𝗮𝗴𝗲𝘀 𝘆𝗼𝘂𝗿 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗶𝘁𝘀 𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀 𝗶𝗻𝘁𝗼 𝗮 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝗶𝘇𝗲𝗱 𝘂𝗻𝗶𝘁 called a 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿.
This container is 𝗶𝘀𝗼𝗹𝗮𝘁𝗲𝗱 from the underlying system, ensuring your application runs 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁𝗹𝘆 across different environments.

➡️𝗧𝗵𝗶𝗻𝗸 𝗼𝗳 𝗶𝘁 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀:
Imagine a shipping container.
You pack all your application's clothes (code and dependencies) inside.
This container can then be shipped anywhere (deployed anywhere) and unpacked (run) with the same contents and behavior.

➡️𝗪𝗵𝘆 𝗗𝗼𝗰𝗸𝗲𝗿 𝗼𝘃𝗲𝗿 𝗩𝗠𝘀?
Compared to VMs, Docker containers:
Are lightweight: They share the host OS, requiring fewer resources and booting faster.
Are portable: Run them anywhere with the same consistency, regardless of the underlying system.
Are immutable: Changes are isolated within the container, simplifying deployments and rollbacks.

➡️𝗗𝗼𝗰𝗸𝗲𝗿'𝘀 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀:
• Streamlined development and deployment: Spin up isolated test environments quickly, collaborate seamlessly, and automate deployments.
• Improved resource efficiency: Containers share resources, maximizing server utilization.
• Microservices architecture: Package and deploy individual services independently.
• Cloud-native compatibility: Works seamlessly across different cloud providers.
• Enhanced security: Isolated containers minimize attack surfaces.

➡️𝗪𝗵𝗲𝗻 𝘁𝗼 𝘂𝘀𝗲 𝗗𝗼𝗰𝗸𝗲𝗿:
• Microservices architecture
• Continuous integration and continuous delivery (CI/CD) pipelines
• Legacy application modernization
• Multi-cloud deployments

➡️𝗗𝗼𝗰𝗸𝗲𝗿'𝘀 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝗼𝗻:
• Podman: Open-source container engine similar to Docker.
• LXC (Linux Containers): Lightweight containerization alternative.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

📌 Who said Kubernetes is simple. 😂

➡️ Before you dream of Kubernetes auto pilot, you should have this covered:

🔣 CI/CD pipelines? Done
🔣 Per app IAM roles? Done
🔣 Pod security policies? Done
🔣 Load balancing rules? Done
🔣 Secrets management? Done
🔣 Cluster health checks? Done
🔣 CRDs for extensibility? Done
🔣 Disaster recovery plans? Done
🔣 High availability setups? Done
🔣 Role-based access control? Done
🔣 Multi-tenancy architectures? Done
🔣 Proactive capacity planning? Done
🔣 Persistent storage solutions? Done
🔣 Cost management strategies? Done
🔣 Service mesh implementation? Done
🔣 Network wide service discovery? Done
🔣 Apps Dependency management? Done
🔣 Container vulnerability scanning? Done
🔣 Per app network security policies? Done
🔣 Resource monitoring and logging? Done
🔣 Zero downtime Update strategies? Done
🔣 Machine pool isolation for services? Done
🔣 Compliance and governance checks? Done
🔣 Pod communication network policies? Done
🔣 Deployment versioning and rollbacks? Done
🔣 Fleet-wide config updates in real-time? Done
🔣 Path-based HTTP routing within cluster? Done
🔣 Efficient resources labeling and tagging? Done
🔣 Economical deployment on spot instances? Done
🔣 Auto-scaling based on performance metrics? Done

Otherwise, you risk falling into a pattern of reactive responses, never fully seizing the initiative.

It's like starring in your own tech horror show. 😅


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🚀 Unlock the Power of Kubernetes Scaling Strategies! 🚀

Looking to optimize your Kubernetes deployment for peak performance? Explore these cutting-edge scaling strategies:

1⃣. Horizontal Pod Autoscaling (HPA): Effortlessly adjust pod counts based on CPU usage and more.
2⃣. Vertical Pod Autoscaling (VPA): Fine-tune CPU and memory resources for optimal efficiency.
3⃣. Cluster Autoscaling: Dynamically scale your cluster to meet workload demands in real-time.
4⃣. Manual Scaling: Take control with manual replica adjustments using simple commands.
5⃣. Predictive Scaling: Harness AI to predict future demands and scale proactively with tools like PredictKube.
6⃣. Custom Metrics Based Scaling: Tailor scaling based on custom metrics beyond CPU and memory.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🔥 Here is a list of some Resume Ready DevOps projects.

1⃣ 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗖𝗜𝗖𝗗 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/gbDBEASe

🔢 𝗗𝗲𝗽𝗹𝗼𝘆 𝗝𝗮𝘃𝗮 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗝𝗲𝗻𝗸𝗶𝗻𝘀
🔗 https://lnkd.in/gSJaF4VN

🔢 𝗗𝗲𝘃𝗢𝗽𝘀 𝗖𝗜𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗦𝗲𝘁𝘂𝗽 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 { 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 | 𝗡𝗲𝘅𝘂𝘀 | 𝗦𝗼𝗻𝗮𝗿𝗾𝘂𝗯𝗲 | 𝗧𝗼𝗺𝗰𝗮𝘁 | 𝗠𝗮𝘃𝗲𝗻 }
🔗 https://lnkd.in/gvDYKMxV

🔢 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗖𝗜𝗖𝗗 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/g-eaM_EA

🔢 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗳𝗼𝗿 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗖𝗦 𝗨𝘀𝗶𝗻𝗴 𝗝𝗲𝗻𝗸𝗶𝗻𝘀, 𝗚𝗶𝘁𝗛𝘂𝗯, 𝗮𝗻𝗱 𝗔𝗺𝗮𝘇𝗼𝗻 𝗘𝗖𝗥
🔗 https://lnkd.in/gN7WXAnX

🔢 𝗣𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴 𝟮-𝘁𝗶𝗲𝗿𝘀 𝗮𝗻𝗱 𝟯-𝘁𝗶𝗲𝗿𝘀 𝗔𝗪𝗦 𝗩𝗣𝗖 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘂𝘀𝗶𝗻𝗴 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺
🔗 https://lnkd.in/g2Y_Nk6N

🔢 𝗕𝗲𝘀𝘁 𝗝𝗲𝗻𝗸𝗶𝗻𝘀 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗙𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀
🔗 https://lnkd.in/gF93WwrB

🔢 𝗘𝗻𝗱 𝘁𝗼 𝗘𝗻𝗱 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝘂𝘀𝗶𝗻𝗴 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗔𝗻𝗱𝗿𝗼𝗶𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻
🔗 https://lnkd.in/gB-Vvi7r

🔢 𝗖𝗿𝗲𝗮𝘁𝗲, 𝗽𝘂𝗯𝗹𝗶𝘀𝗵, 𝗮𝗻𝗱 𝘀𝘁𝗼𝗿𝗲 𝗡𝗴𝗶𝗻𝘅 𝗗𝗼𝗰𝗸𝗲𝗿 𝗶𝗺𝗮𝗴𝗲 𝗶𝗻 𝗔𝗪𝗦 𝗦𝟯 𝘂𝘀𝗶𝗻𝗴 𝗗𝗼𝗰𝗸𝗲𝗿 𝗮𝗻𝗱 𝗕𝗮𝘀𝗵
🔗 https://lnkd.in/g4iUncv9


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🔔 Here is a list of some Resume Ready DevOps projects (Part-II)

➡️ Real-Time CI CD Pipeline From Scratch with Jenkins:-
🔗 https://lnkd.in/day6k4GE

➡️ Creating AWS EKS Cluster using Terraform:-
🔗 https://lnkd.in/gjtjHuw4

➡️ Cost Optimization through AWS Lambda Function:-
🔗 https://lnkd.in/drDazJ9E

➡️ AWS Ninja — Convert EBS Volume from gp2 to gp3:-
🔗 https://lnkd.in/d6mUFdEK

➡️ Real-World CI/CD DevSecOps Pipeline for Deployment of Python Web-app:-
🔗 https://lnkd.in/d-TJisDn

➡️ AWS S3 Event Triggering Shell Script Used by Netflix, Airbnb, Adobe, Expedia, and Others :-
🔗 https://lnkd.in/dXhzdwP8

➡️ Deploy Multi Stage CICD Pipeline with Amazon EKS :-
🔗 https://lnkd.in/dEn7Vexj

➡️ Deploying Spring Boot application on K8S :-
🔗 https://lnkd.in/d8E_N_eg

➡️ Netflix Clone application via K8's:-
🔗 https://lnkd.in/d2zBUdMG
🔗 https://lnkd.in/dPVTDK9r

➡️ Deploy a Flask Application to a EKS Cluster using Jenkins and ArgoCD :-
🔗 https://lnkd.in/dn8WtnWj


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🔔 Here is a list of some Resume Ready DevOps projects.(Part-III)


➡️ Deploying Super Mario on Amazon EKS
🔗 (https://lnkd.in/d2JVCw6M)

➡️ 🚀 Designing a 10-Microservices Application Deployment on EKS! 🤖
🔗 (https://lnkd.in/dFuq9mMA)

➡️ Uber Clone DevSecOps Project
🔗 (https://lnkd.in/dTXm9_h9)

➡️ 3-Tier Robot Shop App On EKS
🔗 (https://lnkd.in/dtFK8Xj7)

➡️ Full Stack CICD Virtual Browser Project
🔗 (https://lnkd.in/d2ZErR2b)


💬 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

📌 𝐄𝐱𝐩𝐥𝐨𝐫𝐞 𝐃𝐞𝐯𝐎𝐩𝐬 𝐓𝐨𝐨𝐥𝐬 𝐒𝐭𝐚𝐜𝐤

Setting up an effective DevOps pipeline involves a combination of practices, tools, and cultural considerations.


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

𝐋𝐢𝐬𝐭 𝐨𝐟 𝐟𝐫𝐞𝐞 𝐜𝐨𝐮𝐫𝐬𝐞𝐬 𝐭𝐨 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐘𝐨𝐮𝐫 𝐒𝐤𝐢𝐥𝐥𝐬: 𝐃𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐖𝐨𝐫𝐥𝐝 𝐨𝐟 𝐃𝐞𝐯𝐎𝐩𝐬 & 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐦𝐮𝐬𝐭 𝐭𝐫𝐲 𝐅𝐫𝐞𝐞 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔢. 𝐏𝐲𝐭𝐡𝐨𝐧:
A scripting language used for automation in DevOps.
🔗 https://lnkd.in/gTEsX2VC

🔢. 𝐆𝐢𝐭:
Distributes version control system handles everything from small to very large projects with speed and efficiency.
🔗 https://lnkd.in/gFTyTWCC

🔢. 𝐂𝐥𝐨𝐮𝐝:
Its fair to say the rapid increament of startUps is revolutionised by the cloud technology.
🔗 https://lnkd.in/gf6_8RNG

🔢. 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬:
An approach of making a loosely coupled application.
🔗 https://lnkd.in/gYqdHCdF

🔢. 𝐒𝐞𝐫𝐯𝐞𝐫𝐥𝐞𝐬𝐬:
Allows developers to build and run applications without worrying about servers.
🔗 https://lnkd.in/g8knM8uE

🔢. 𝐋𝐢𝐧𝐮𝐱:
Probably the most famous primitive yet secure OS to use
🔗 https://lnkd.in/ghmZybpz

🔢. 𝐃𝐞𝐯𝐎𝐩𝐬:
An exploding domain to learn (It is an ecosystem that takes care of continuous integration, delivery, deployment and monitoring)
🔗 https://lnkd.in/g6ryYv8N

🔢. 𝐃𝐨𝐜𝐤𝐞𝐫:
Packages application along with dependencies and libraries required to run the application.
🔗 https://lnkd.in/ggaqmu8p

🔢. 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬, 𝐎𝐩𝐞𝐧𝐒𝐡𝐢𝐟𝐭:
Manages the deployment of an application and have autoscaling and autohealing capabilities.
🔗 https://lnkd.in/gsKYTciW

🔢🔢. 𝐌𝐲𝐒𝐐𝐋:
Relational Database Management System
🔗 https://lnkd.in/gbmjQcsD


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

🔣 Introduction to Kubernetes (k8s) ~ The Orchestrator ⚓️

🚒 What is Kubernetes?
Kubernetes, commonly referred to as K8s, is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications.

🚒 Key Concepts:
🚧 Nodes:
- Physical or virtual machines that form the cluster.
- Each node runs container runtime (like Docker), kubelet (agent for managing node), and a kube-proxy.

🚧 Pods:
- The smallest deployable units in kubernetes.
- Containers within a pod share the same network namespace, enabling them to communicate easily.

🚧 Services:
- Defines a set of pods and how they should be accessed.
- Provides a stable IP address and DNS name to access the pods.

🚧 ReplicaSets:
- Ensures a specified number of replicas (pods) are running at all times.
- Helps with scaling and ensuring high availability.

🚧 Deployments:
- Manages ReplicaSets, allowing declarative updates to applications.
- Supports rolling updates and rollbacks.

⛴ Basic Operations:
⛵️ Creating a Deployment:
- Defines the desired state for the application.
- Uses YAML files for configuration.
⛵️ Scaling:
- Adjusts the number of replicas for a Deployment or ReplicaSet.
⛵️ Service Discovery:
- Allows communication between different services within the cluster.
- Uses DNS names to locate services.
⛵️ Updating Deployments:
- Modifies the configuration to roll out updates.
- Supports rolling updates with zero downtime.
⛵️ Rollbacks:
- Reverts to a previous version in case of issues with a new deployment.

🚢 Kubernetes Architecture:
🛎 Master Node:
- Controls and manages the overall cluster.
- Components: kube-apiserver, kube-controller-manager, kube-scheduler, etcd (distributed key-value store).

🛎 Worker Node:
- Executes tasks assigned by the Master Node.
- Components: kubelet, container runtime (e.g., Docker), kube-proxy.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

⚡️ If u start learning DevOps and Cloud Engineering today... ⚡️

🔣Here are the 8 things u would take more seriously.🔣

1⃣. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴:
- Command-level operations are fine.
- To excel in system architecture, deep knowledge of network protocols, IP routing, firewall management, and secure communication channels is essential.

🔢. 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗖𝗟𝗜:
- GUIs are intuitive, but incomplete.
- Get started with CLI from Day 1.
- Terraform, Ansible, Kubernetes, AWS - you name it, every single provider has a CLI.

🔢. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴:
- DevOps is not just about connecting tools.
- Automating tasks, writing hooks, API integration, and more needs solid programming expertise.
- Python, Go, Rust are promising choices.

🔢. 𝗔𝗣𝗜𝘀:
- No day goes by without an API.
- Authentication methods like OAuth, JWT, and contract testing are crucial for smooth service integration.
- Knowing how to effectively consume and design RESTful services cannot be a choice.

🔢. 𝗗𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴:
- Robust troubleshooting skills across apps and infrastructure are non-negotiable.
- Tools such as strace, netstat, tcpdump, and app-specific debuggers enable swift, effective problem-solving.
- Tools aren't enough; couple it with an open mindset.

🔢. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗛𝘆𝗴𝗶𝗲𝗻𝗲:
- Being security responsible from the start is imperative.
- Strict adherence to least privilege, RBAC, centralized secrets management, and a single source of truth is mandatory.

🔢. 𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴:
- Mastering how to catch, handle, and log exceptions can be a lifesaver in unexpected failure scenarios.

🔢. 𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀:
- Business is about dealing with humans; technology is built by and for humans.
- Effectively working in a team, understanding requirements, and clearly presenting technical solutions are underrated.
- But that makes all the difference more than anything else.

It's not about 'what if I start learning today.'

It's about understanding the gaps in the past and keeping updating.

🔣 Basically, never stop learning.


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

#devopshiring


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs

📣 Opening - DevOps Engineer
⏩ GIIT Solutions

➡️ Location : Anywhere in all India
➡️ Skills : Jenkins, AWS
➡️ Notice : 90 Days
➡️ Qualification : Any
➡️ Salary : As per company
➡️ Experience : 0-2 Years

🔗 Apply from here - https://lnkd.in/dUUvxWNN


😎 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!! // Join for DevOps DOCs: @devopsdocs