https://harshhaa.hashnode.dev/transform-kubernetes-manifests-into-helm-chart

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

Version control with 🧑‍💻 GIT has become an essential skill for developers.

In this post, I'll provide a quick overview of some core GIT concepts and commands.

Key concepts:
➡️ Repository - Where your project files and commit history are stored
➡️ Commit - A snapshot of changes, like a version checkpoint
➡️ Branch - A timeline of commits that lets you work on parallel versions
➡️ Merge - To combine changes from separate branches
➡️ Pull request - Propose & review changes before merging branches

Key commands:
➡️ git init - Initialize a new repo
➡️ git status - View changed files not staged for commit
➡️ git add - Stage files for commit
➡️ git commit - Commit staged snapshot
➡️ git branch - List, create, or delete branches
➡️ git checkout - Switch between branches
➡️ git merge - Join two development histories (branches)
➡️ git push/pull - Send/receive commits to remote repo


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

🐬 Dockerfile Checklist 👇

Navigating the ✔️ best practices and ❌ DONT's while handling a Dockerfile


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

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➡️ As a software professional, keeping up with the latest DevOps tools is essential for optimizing development and delivery.

The right tools make teams more productive, applications more resilient, and organizations more innovative.

Here are some of the most impactful DevOps tools I recommend learning in 🌟🌟:

✍️ Kubernetes: This open-source container orchestration system simplifies deploying and managing containerized applications. It allows scaling and balancing container workloads.

✍️ Terraform: Infrastructure as code is a must today. Terraform lets you define cloud and on-prem infrastructure in files and provision it automatically.

✍️ Docker: Containerizing apps with Docker packages software into standardized units along with dependencies to run anywhere consistently. It accelerates development.

✍️ Ansible: This configuration management and automation tool executes tasks across nodes via SSH without needing agents. It's simple yet powerful.

✍️ Prometheus: A top open-source monitoring and alerting solution that scrapes metrics and provides robust query capabilities with PromQL.

✍️ Grafana: The leading analytics and visualization platform for monitoring. It’s easy to create rich dashboards for operational insights.

✍️ ELK Stack: Combines Elasticsearch, Logstash, and Kibana for centralized logging, searching, and visualizing log data for troubleshooting.

I aim to provide actionable insights on leading tools so you can advance your skills efficiently.


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

https://harshhaa.hashnode.dev/deployment-of-super-mario-on-kubernetes-using-terraform

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

Kubernetes: You need to know this 👇

When you do a port farward to a nginx service,

you happily create a tunnel to a single pod 😚

kubectl port-forward svc/nginx 8080:80

❌ Now. Here's a problem:

1. Wonder what happens if the traffic serving pod is terminated?
2. The browser returns "refused to connect" error.

Why?

Because the tunnel is broken.

✔️ To re-establish connection:

"You need to run port-forward command again."
"Port forwarding is useful for testing only."
"For production use cases, always use deployments"

Hope you happily learned something 😎


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

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🔴 Architecture of a Kubernetes Cluster ☸️

A production-ready Kubernetes cluster is vastly complex. There are many non-negotiable such as High Availability, Fault Tolerance, data backups and durability requirements.

Its architecture is divided into the Control Plane and Data Plane.
This is what they do 👇

➡️ DATA PLANE
The part of the cluster where all compute resources reside. This is where ultimately all your container applications run.

1️⃣Nodes
The worker machines that actually run container workloads. These could be EC2 servers (or other cloud provider equivalents), bare-metal servers or even just your personal computer.

2️⃣Pods
The smallest unit of compute that you can deploy in K8s. A Pod contains 1 or more containers running your application(s) and helper processes. A Pod runs inside a Node.

3️⃣Kubelet
An agent that runs on every Node. It takes Pod specifications provided by the user and ensures that the Containers described in them are running and healthy.

4️⃣Kube-proxy
Runs on every Node and manages network rules on the system to ensure network communication works smoothly between Pods and the outside world.

5️⃣Container Runtime
Runs on all nodes and manages the lifecycle of container(s) deployed on them. Eg- Docker, CRI-O, etc.

➡️ CONTROL PLANE
Does the administrative tasks of managing worker nodes, Pods and the cluster in general.
It is basically the “brains” of the cluster that makes all decisions like scheduling, always steering the cluster towards the desired state (eg- spin up new pods in response to some pods going down to maintain the desired number of them).

🔢Kube-apiserver
Exposes the Kubernetes API to the user. When you make an API request to Kubernetes or use a client like Kubectl, you request is handled by kube-apiserver and passed on for further processing.

🔢Etcd
A consistent and highly available Key-value store used by Kubernetes for storing all cluster data. You should have a strong backup strategy for this datastore as it tracks all state of the cluster.

🔢Scheduler
Responsible for placing Pods on to Nodes in the most optimal way possible. When a new Pod is requested, the scheduler looks for a suitable Node to run it in.
Takes many different factors into consideration while scheduling, such as resource requirements, priority, user-specified criteria, etc.

🔢Controller Manager
Runs Controllers. A Controller is a process that always steers the system toward a desired state. Eg- A Node controller monitors and responds when nodes go down.

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

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🟩 Ansible 🆓 Videos 🔴

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🟩 🌐 Git/GitHub Free Videos:- 🟩

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⏩ Hiring DevOps Engineer (Freshers)

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🤦‍♀️ Knowing this beforehand , rolling updates would have been a cake walk to understand & not to surprise why most preferred deployment type by Big Tech Giants 🚀🚀


🔎 Why are different types of deployment strategies used ?

Deployments types are decided based on various factors. including client unique requirements , flexibility , scalability , managing risk and much more !

🪝𝙇𝙚𝙩’𝙨 𝙪𝙣𝙙𝙚𝙧𝙨𝙩𝙖𝙣𝙙 𝙖𝙗𝙤𝙪𝙩 𝙍𝙤𝙡𝙡𝙞𝙣𝙜 𝙐𝙥𝙙𝙖𝙩𝙚𝙨 𝙖𝙨 𝙙𝙚𝙥𝙡𝙤𝙮𝙢𝙚𝙣𝙩 𝙨𝙩𝙧𝙖𝙩𝙚𝙜𝙮

✨ Let’s picturize it as you have multiple servers , but you need to upgrade their versions , at the same time make sure user experience is not hampered by, rolling update comes as saviour , one by one you can upgrade to required/ new version test it and bring it online , similarly you follow it for remaining ones

✨ You can incrementally bring all your servers to required state

📌 It proves to be a game changer as when one of your server is updating/ upgrading rest of the services are in places and users experience no downtime and gradually same follows till whole system is updated


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

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

💜 𝗗𝗲𝘃𝗢𝗽𝘀 𝗧𝗼𝗼𝗹𝘀

𝑱𝒐𝒊𝒏 𝑶𝒖𝒓 𝑻𝒆𝒄𝒉 𝑪𝒐𝒎𝒎𝒖𝒏𝒊𝒕𝒚 -> 𝑮𝒖𝒊𝒅𝒆 𝑶𝒕𝒉𝒆𝒓’𝒔

⏩𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗧𝗲𝘀𝘁𝗶𝗻𝗴:
- Selenium: Great for testing web applications.
- Appium: Focuses on testing mobile applications for iOS and Android.
- Katalon: User-friendly tool for testing web, mobile, and API applications.
- JMeter: Used for performance and load testing of applications.

⏩𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻:
- Kubernetes: Manages containerized applications efficiently.
- Docker Swarm: Simple tool for smaller teams using Docker containers.
- Openshift: Red Hat's solution for container orchestration.
- Apache Mesos: Efficiently orchestrates and manages containers.

⏩𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴:
- Kibana: Visualizes and analyzes logs in real-time.
- Nagios: Open-source system for monitoring IT infrastructure.
- Prometheus: Monitors metrics and alerts for dynamic environments.
- Splunk: Analyzes and monitors machine-generated data.

⏩𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴:
- Jira: Popular for project management and agile development.
- Slack: Real-time messaging platform for team collaboration.
- Confluence: Atlassian's tool for creating, sharing, and collaborating on documents.

⏩𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴:
- Python: Versatile language for automation, scripting, and web development.
- Go: Efficient compiled language for scalable systems.
- Groovy: Dynamic language for scripting in Jenkins pipelines.
- Bash: Shell scripting language for automating tasks in Unix environments.

⏩𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀:
- Docker: Revolutionized application packaging and deployment.
- buildAH: Builds container images without a Docker daemon.
- Podman: Daemonless alternative to Docker for managing containers.
- Kaniko: Builds container images inside containers securely.

⏩𝗜𝗔𝗖 & 𝗜𝗣 (𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 𝗮𝗻𝗱 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗣𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴):
- Ansible: Automates configuration management and task automation.
- Puppet: Manages infrastructure configuration for consistency and compliance.
- Terraform: IAC tool supporting various cloud providers and on-premises environments.

⏩𝗦𝗼𝘂𝗿𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 & 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝘃𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁:
- Gitlab: Integrated platform for source code management and collaboration.
- Git: Distributed version control system for tracking changes and collaboration.
- BitBucket: Atlassian's Git repository management solution.

⏩𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀:
- Google Cloud: Provides scalable infrastructure and various cloud services.
- AWS (Amazon Web Services): Leading cloud service provider with a wide range of services.
- Azure: Microsoft's cloud platform offering comprehensive services.
- Oracle Cloud: Complete suite of cloud services for enterprises adopting DevOps.


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