🌐 AWS Disaster Recovery strategies 🌐

1️⃣. Backup:
This is the most basic level of disaster recovery readiness. It involves regular backups of data and systems, often stored offsite or in the cloud. In this context, "Back" likely refers to backing up data and systems to restore them in case of data loss or system failure.

2️⃣. Pilot Light:
This refers to a disaster recovery setup where essential systems are kept in a minimal operational state
In the event of a disaster, additional resources can be quickly provisioned to bring the system to full operational capacity. It's a step up from basic backup, offering a faster recovery time.

3️⃣.Warm Standby:
A warm standby site is a disaster recovery setup where duplicate hardware and infrastructure are maintained, but they are not actively processing data or serving users.
The infrastructure is configured and ready to take over in case the primary site fails. This setup typically involves periodic synchronization of data and configurations to reduce recovery time.

➡️Hot Site:
A hot site is a fully operational secondary data center or environment that mirrors the primary production environment. It is continuously updated and synchronized with the primary site in real-time or near real-time.
In the event of a disaster, operations can seamlessly switch to the hot site with minimal disruption, offering the shortest recovery time objective (RTO) and recovery point objective (RPO).


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

👉Continuous deployment as sumes that every product change or update is deployed automatically to production without any manual supervision from a DevOps engineer.

💡 Continuous Delivery:
- Automates the release process.
- Ensures readiness for deployment at any time.
- Allows manual deployment when needed.

💡 Continuous Deployment:
- Automates deployment of every successful code change.
- Directly deploys to production without human intervention.
- Requires high confidence in automated testing.


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

🔖 𝐇𝐨𝐰 𝐭𝐨 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐃𝐞𝐯𝐎𝐩𝐬 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐔𝐬𝐢𝐧𝐠 𝐉𝐞𝐧𝐤𝐢𝐧𝐬!

Jenkins is a popular automation server that can be used to automate the CI/CD pipeline. In this post we will learn how to use Jenkins to automate the following steps:

✅ Checkout code from version control: Jenkins can be configured to automatically checkout code from a version control system, such as GitHub.
✅ Compile code: Jenkins can use a variety of build tools, such as Maven or Gradle, to compile the code.
✅ Run unit tests: Jenkins can run unit tests to ensure that the code is working properly.
✅ Build a Docker image: Jenkins can build a Docker image from the compiled code.
✅ Push Docker image to registry: Jenkins can push the Docker image to a Docker registry, such as Docker Hub.
✅ Deploy to Kubernetes: Jenkins can notify Kubernetes of the new Docker image and deploy it to a Kubernetes cluster.


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

🐳 𝗗𝗼𝗰𝗸𝗲𝗿 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀! 🐳

Docker has revolutionized the world of containerization, enabling scalable and efficient application deployment.

To make the most of this powerful tool, here are 10 essential Docker best practices:

✔️ 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗮 𝗟𝗶𝗴𝗵𝘁𝘄𝗲𝗶𝗴𝗵𝘁 𝗕𝗮𝘀𝗲 𝗜𝗺𝗮𝗴𝗲: Use minimalist base images to reduce container size and vulnerabilities.

✔️ 𝗦𝗶𝗻𝗴𝗹𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗽𝗲𝗿 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿: Keep it simple - one process per container for better isolation and maintainability.

✔️ 𝗨𝘀𝗲 𝗗𝗼𝗰𝗸𝗲𝗿 𝗖𝗼𝗺𝗽𝗼𝘀𝗲: Define multi-container applications in a YAML file for easy management.

✔️ 𝗩𝗼𝗹𝘂𝗺𝗲 𝗠𝗼𝘂𝗻𝘁𝗶𝗻𝗴: Store data outside the container to preserve it, even if the container is removed.

✔️ 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Consider Kubernetes or Docker Swarm for managing containers at scale.

✔️ 𝗩𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗧𝗮𝗴𝗴𝗶𝗻𝗴: Always tag images with version numbers to ensure reproducibility.

✔️ 𝗛𝗲𝗮𝗹𝘁𝗵 𝗖𝗵𝗲𝗰𝗸𝘀: Implement health checks to monitor container status and reliability.

✔️ 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗶𝗺𝗶𝘁𝘀: Set resource constraints to prevent one container from hogging resources.

✔️ 𝗗𝗼𝗰𝗸𝗲𝗿𝗳𝗶𝗹𝗲 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: Optimize Dockerfiles by minimizing layers and using caching effectively.

✔️ 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Regularly update images, scan for vulnerabilities, and follow security best practices.


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

☄️ 𝗕𝗲𝘀𝘁 𝐘𝐨𝐮𝐭𝐮𝐛𝐞 𝐜𝐡𝐚𝐧𝐧𝐞𝐥𝐬 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗲𝘃𝗢𝗽𝘀 ✨


✔️ LogicOps Lab by Ravish Rawat ( Real time Interview's )
🔗 https://lnkd.in/g3rtbjHb

✔️ Real time projects @mr.cloudbook
🔗 https://lnkd.in/gWWqHnJx

✔️ Train With Shubham by Shubham Londhe
🔗 https://lnkd.in/g9SwADkB

✔️ Tech Tutorials with Piyush by Piyush sachdeva (Azure and GCP cloud)
🔗 https://lnkd.in/g4iWpScc

✔️ TechWorld With Nana by Nana Janashia
🔗 https://lnkd.in/g7iFKKb9

✔️ KodeKloud by Mumshad Mannambeth
🔗 https://lnkd.in/g2jdc__p

✔️ Stéphane Maarek
🔗 https://lnkd.in/gzSbeKFt

✔️ Technical Guftgu by Bhupinder Rajput l भूपिंदर राजपूत l بھوپندر راجپوت In Hindi
🔗 https://lnkd.in/g8FYMCAS

✔️ Cloud Advocate by Krishna Chaitanya Gadhiraju (GK)
🔗 https://lnkd.in/giNb536Y

✔️ Abhishek Veeramalla
🔗 https://lnkd.in/gMfRacqy

✔️ Cloud Champ by Nasiullha Chaudhari
🔗 https://lnkd.in/gYUQ4r5x

✔️ Praveen Singampalli
🔗 https://lnkd.in/gVAeX8dZ


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

🔣 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗖𝗼𝗺𝗺𝗼𝗻 𝗘𝗿𝗿𝗼𝗿𝘀 🔣

1️⃣.𝙄𝙢𝙖𝙜𝙚𝘽𝙖𝙘𝙠𝙋𝙪𝙡𝙡𝙊𝙛𝙛 :-
We face this issue when the image is not present in registry or the given image tag is wrong.
Make sure you provide correct registry url, image name and image tag.

We might face authentication failures, when image is being stored in a private registry, make sure to create secret with private registry credentials and add created secret in Kubernetes Deployment File to pull docker image.

2️⃣.𝘾𝙧𝙖𝙨𝙝𝙇𝙤𝙤𝙥𝘽𝙖𝙘𝙠𝙊𝙛𝙛 :-
We face this issue when the process deployed inside container not running then the POD will be moved to CrashLoopBackOff.
POD might be running out of CPU or memory, POD should get enough resources allocated that’s cpu and memory for an application to be up and running, to fix that check in Resources Requests and Resources Limits.

3️⃣.𝙊𝙊𝙈 𝙆𝙞𝙡𝙡𝙚𝙙 - 𝙊𝙪𝙩 𝙊𝙛 𝙈𝙚𝙢𝙤𝙧𝙮 :-
We face this issue when PODs tries to utilise more memory than the limits we have set.
We can resolve it by setting appropriate resource request and resource limit.

4️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙋𝙚𝙣𝙙𝙞𝙣𝙜 :-
When nodes might not be ready and required resources like CPU and Memory may not be available in nodes for the PODs to be up and running.

5️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙒𝙖𝙞𝙩𝙞𝙣𝙜 :-
POD will be scheduled to a node but POD won’t be running in scheduled node.
We can fix this by providing correct image name, image tag and authentication to registry.

6️⃣.𝙋𝙊𝘿 𝙬𝙞𝙡𝙡 𝙗𝙚 𝙪𝙥 𝙖𝙣𝙙 𝙧𝙪𝙣𝙣𝙞𝙣𝙜 𝙖𝙣𝙙 𝙖𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙞𝙨 𝙣𝙤𝙩 𝙖𝙘𝙘𝙚𝙨𝙨𝙞𝙗𝙡𝙚.
We can fix this by creating appropriate service.
If service is already created and application is still not accessible, make sure application and service are deployed in same namespace.

7️⃣.𝙋𝙊𝘿 𝙎𝙩𝙖𝙩𝙪𝙨 – 𝙀𝙫𝙞𝙘𝙩𝙚𝙙 :-
We can resolve this by setting appropriate resource requests and resource limits for the PODs and having enough resources in worker nodes.


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

📌 Title: DevOps Engineer

➡️ Location: Remote

➡️ Job Description:

1-10 years of exp in DevOps (AWS/ Azure/ GCP).
Hands-on exp in deploying Kubernetes cluster using ELK/ GKE environment.
Creating CI/CD pipeline using Jenkins.
Using Monitoring tools like Prometheus/ Grafana/ Stack driver.
Docker
Infra Automation scripting

🖥 Interested upload resume with 100% details - https://lnkd.in/eFn7aja


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

🔴 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!!!

𝐓𝐨𝐩 𝐔𝐬𝐞𝐝 𝐃𝐨𝐜𝐤𝐞𝐫 𝐂𝐨𝐦𝐦𝐚𝐧𝐝𝐬 🐋

🐳 𝐃𝐨𝐜𝐤𝐞𝐫 𝐁𝐚𝐬𝐢𝐜𝐬:
• 🏁 docker run: Run a container from an image.
• 📦 docker build: Build an image from a Dockerfile.
• 🔍 docker images: List all images on the system.
• 🗑 docker rmi: Remove one or more images.
• 🏗 docker-compose up: Start services defined in a Compose file.
• 🛑 docker stop: Stop a running container.
• ♻️ docker rm: Remove one or more containers.
• 💡 docker ps: List running containers.


🐋 𝐃𝐨𝐜𝐤𝐞𝐫 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠:
• 🌐 docker network create: Create a network.
• 🔗 docker network connect: Connect a container to a network.
• 🛠 docker network inspect: Inspect a network.
• 🔄 docker network disconnect: Disconnect a container from a network.


📁 𝐃𝐨𝐜𝐤𝐞𝐫 𝐕𝐨𝐥𝐮𝐦𝐞𝐬:
• 📂 docker volume create: Create a volume.
• 🔌 docker volume ls: List volumes.
• 🔄 docker volume inspect: Inspect a volume.
• 🗑 docker volume rm: Remove one or more volumes.



⚙️ 𝐃𝐨𝐜𝐤𝐞𝐫 𝐂𝐨𝐦𝐩𝐨𝐬𝐞:
• 📋 docker-compose up: Start services defined in a Compose file.
• 🗄 docker-compose down: Stop and remove services defined in a Compose file.
• 🔧 docker-compose build: Build or rebuild services.
• 📊 docker-compose logs: View output logs from services.
• 🔄 docker-compose restart: Restart services.
• 📈 docker-compose scale: Scale services to a specified number.


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

DevOps 👾 Life Cycle Overview 🔥


1️⃣. Code: Developers create the software code, using tools like Git to collaborate and manage changes.

2️⃣. Build: Converts code for computer understanding, with tools like Jenkins for efficiency.

3️⃣. Test: Ensures software quality with tools like JUnit for bug-free performance.

4️⃣. Release: Deploys tested software via CI/CD for user access.

5️⃣. Monitor: Maintains software performance post-release with tools like Prometheus.

6️⃣. Operate: Manages real-time software functioning with automation.

7️⃣. Plan: DevOps planning with tools like Jira for agile adaptability.

8️⃣. Deploy: Scales software for more users with Infrastructure as Code.

9️⃣. Scale: Expands software capabilities for growing needs.

1️⃣0️⃣. Feedback Loop: Continuous improvement through user and ops feedback.


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

❤️‍🔥 Ever imagined what a CI/CD ♾ pipeline might look like? Here's a glimpse:

1️⃣. 𝐏𝐥𝐚𝐧/𝐃𝐞𝐬𝐢𝐠𝐧, where great ideas turn into robust plans.
2️⃣. 𝐃𝐞𝐯𝐞𝐥𝐨𝐩, with every line of code embedded with security.
3️⃣. 𝐁𝐮𝐢𝐥𝐝 𝐚𝐧𝐝 𝐂𝐨𝐝𝐞 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬, maintaining the bar high.
4️⃣. 𝐓𝐞𝐬𝐭, rigorous and automated.
5️⃣. 𝐃𝐞𝐩𝐥𝐨𝐲, delivering continuous freshness.
6️⃣. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐧𝐝 𝐀𝐥𝐞𝐫𝐭, with vigilance as the motto.

But the most critical element?
Making security a habit, not just a step.

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Apply now for a chance to join our dynamic team! ⚡️
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🔣 Levels of Kubernetes. 🔣

➡️ Level 1
➖ Knows basic concepts.
➖ Limited troubleshooting skill.

➡️Level 2
➖ Can manage deployments, scaling apps & namespaces well.
➖ Troubleshoots issues with pods and deployments.

➡️ Level 3
➖ Deep understanding of Kubernetes & automate deployments.
➖ Debug advanced issues. (Including cluster level ones.)

➡️ Level 4
➖ Designs & implements secure and scalable clusters.
➖ Optimizes cluster performance and resource utilization.
➖ Good understanding of Kubernetes security best practices.

➡️ Level 5
😎 Ability to say - "We don't need Kubernetes for this problem."


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

🐬 Docker Container Commands for a DevOps Engineer

The below illustration shows some common container commands and their syntax 👇

1. 🏗 Creates a container from an image

docker run -it --name nginx nginx

2. 🚀 Begins a Docker container

docker start nginx

3. 🔄 Restarts a Docker container.

docker restart nginx

4. ⏸ Temporarily halts a container.

docker pause nginx

5. ▶️ Resumes a paused container.

docker unpause nginx

6. 🛑 Ends a running Docker container.

docker stop nginx

7. ❌ Forcefully stops a running container

docker kill nginx

8. 📊 Lists Docker containers.

docker ps

9. 🖥 Accesses a container's shell.

docker exec -it nginx /bin/bash

10. 📝 Connects to a running container.

docker attach nginx

11. 📜 Views container logs.

docker logs nginx

12. 🔄 Change a container's name.

docker rename old-name new-name

13. 🔍 Retrieves container info.

docker inspect nginx

14. 📂 Copies files to/from a container.

docker cp nginx:/container-path/file.txt /local-path

15. 🗑 Deletes a container.

docker rm nginx

These container commands are essential for managing containerized applications, whether for development, testing, or production deployment, as they enable efficient control and manipulation of container instances.


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

🟥 75+ DevOps & Cloud Documents 📇 Uploaded

Here to Here


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➡️ What is DevOps and what DevOps engineer do? ❓


➡️ DevOps is a set of practices, cultural philosophies, and tools that aim to improve collaboration, communication, and integration between software development (Dev) and IT operations (Ops) teams.

✅ The goal of DevOps is to enable Organization to deliver high-quality software products and services more rapidly, reliably, and efficiently.

➡️ DevOps engineers play a critical role in enabling organizations to embrace DevOps culture and practices, driving agility, innovation, and efficiency in software development and delivery.

🌟 DevOps engineer gaining expertise in tools and technologies related to DevOps practices, such as version control systems, continuous integration/continuous deployment (CI/CD) pipelines, containerization, and cloud computing platforms, is essential for a successful career in DevOps engineering.


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

📌 What are Kubernetes Addons?

Kubernetes addons are optional components and features that extend the functionality of your Kubernetes cluster beyond its core capabilities. These addons provide additional functionalities such as monitoring, logging, networking, and security, allowing users to tailor their Kubernetes deployments to their specific needs and preferences.

Key Features of Kubernetes Addons:

➡️Monitoring and Logging: Addons such as Prometheus and Fluentd enable monitoring and logging of cluster metrics, application logs, and system events. They provide insights into cluster health, performance, and troubleshooting capabilities, empowering users to optimize their deployments and ensure reliability.

➡️Networking: Kubernetes addons like CoreDNS and Calico enhance networking capabilities within the cluster, facilitating communication between pods and services, implementing network policies, and providing advanced networking features such as service discovery and load balancing.

➡️Security: Addons such as Kubernetes RBAC and PodSecurityPolicy enforce security best practices within the cluster, controlling access to resources, defining security policies, and mitigating security risks. They help ensure compliance, prevent unauthorized access, and protect against security vulnerabilities.

➡️Visualization and User Interface: Kubernetes addons such as the Kubernetes Dashboard and Grafana provide visualization tools and user interfaces for managing and monitoring cluster resources, workloads, and configurations. They offer a convenient way to interact with the cluster and gain insights into its state and performance.


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From 'It works on my machine!' to 'It works on my container!' but hey at least it works!


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🚀 Jenkins, Maven, Gradle, and CI/CD Pipelines 🚀

Are you ready to elevate your development process to new heights? 🚀 Embrace the power of Jenkins, Maven, Gradle, and CI/CD pipelines for a seamless DevOps experience! 🛠️🌟

🛠 Jenkins: Your ultimate automation hub! Streamline your workflows, automate repetitive tasks, and enhance collaboration across your development teams. Jenkins is the heartbeat of DevOps, orchestrating the entire software delivery process. 🔄💼

📦 Maven and Gradle: The dynamic duo of build automation! 🚀 Maven simplifies project management and dependency resolution, while Gradle empowers you with a flexible, customizable build system. Whether you're a Maven enthusiast or a Gradle aficionado, these tools are your go-to for efficient project builds. 🏗️🔨

🔄 CI/CD Pipelines: Accelerate your delivery pipeline and achieve continuous integration and continuous deployment with CI/CD pipelines. 🚚💨 Enhance collaboration, reduce errors, and deliver high-quality software at the speed of DevOps. Your code goes from development to production seamlessly, ensuring a smooth and efficient release process. 🌐⚙️

🌟 DevOps Magic: Unleash the magic of DevOps to foster collaboration, automate processes, and deliver value to your users faster than ever! 🚀✨ Embrace a culture of continuous improvement and innovation. With Jenkins, Maven, Gradle, and CI/CD pipelines, your DevOps journey is set to reach new heights! 📈🚀

🛡 Tool Integration: Seamlessly integrate these powerful tools into your DevOps toolchain. Whether you're building Java applications, managing dependencies, or automating deployment, this arsenal of tools ensures a cohesive and efficient development process. 🔗🔄

🌐 Join the DevOps Revolution!: Elevate your development game with Jenkins, Maven, Gradle, and CI/CD pipelines. 🚀 Embrace efficiency, collaboration, and innovation. Your DevOps journey starts now! 💼🖥🚀


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