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➡️ Understanding Container Runtimes in Kubernetes 👈

A container runtime in Kubernetes is the software component responsible for managing the lifecycle of individual containers within a pod. It's the engine that executes the commands and manages the processes within the container environment.

➡️ What it does:

➡️Creates and starts containers: Based on instructions from the kubelet (the Kubernetes agent on each node), the container runtime pulls the container image, sets up the necessary resources, and fires up the container process.

➡️Manages container resources: It allocates CPU, memory, and other resources as specified in the pod definition, ensuring each container gets its fair share.

➡️Monitors and manages container health: It keeps an eye on the container's health and restarts it if it crashes or becomes unresponsive.

➡️Stops and removes containers: When a container is no longer needed, the runtime gracefully stops it and cleans up its resources.

➡️ Why it's important:

➡️Isolation: Container runtimes create isolated environments for each container, ensuring applications don't interfere with each other or the host system.

➡️Security: They enforce security policies and resource limitations, providing a more secure environment for containerized applications.

➡️Portability: Container runtimes adhere to industry standards, allowing containers to be easily moved between different platforms and cloud providers.

➡️Common container runtimes in Kubernetes.

- containerd
- CRI-O
- Docker Engine
- Mirantis Container Runtime


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

🔖 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!!!

♾ DevOps Tools - Setup, Installations, Guides ⚙️

🔗Link: https://github.com/NotHarshhaa/DevOps_Setup-Installations

We add daily Tools Setup, Installations, Guides with each and every commands with clear explanation

💎 Now added : Kubernetes, Jenkins, Ansible, Terraform, AWS, Azure, Linux
More added daily so fork the repository for updates

🐱 Follow me on GitHub for more DevOps/Cloud related sources


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

➡️ Repository Update 📣


➡️Added Jenkins installation and setup and integrating for various types of tools to support your continuous integration and continuous deployment (CI/CD) pipelines

➡️ Here are tools content:

🔢. Version Control & Build Tools
🔢. Testing Frameworks Tools
🔢. Containerization Tools
🔢. Infrastructure as Code (IaC) Tools
🔢. Code Quality and Analysis Tools
🔢. Deployment Tools
🔢. Notification and Collaboration Tools

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

💡 Kubernetes vs Docker: What's The Difference?

➡️Docker and Kubernetes are the most common names that one might hear in the field of container technology.

➡️Docker is a runtime and containerization platform that was first introduced in 2013 and brought about a microservices-based computing model.

➡️Kubernetes is a platform that manages and runs containers from multiple container runtimes and supports various container runtimes, including Docker.


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

📢 Node Affinity

🔣 In Kubernetes, node affinity is a feature that allows you to control which nodes your pods are scheduled on based on labels on the node. This can be useful for various reasons such as optimizing performance, ensuring certain workloads are placed on specific nodes, or ensuring high availability by spreading pods across different nodes.

There are two types of node affinity:
🔎 Required Node Affinity: This type specifies that a pod should only be scheduled on nodes that meet the specified node selector requirements.

🔎 Preferred Node Affinity: This type specifies that a pod prefers to be scheduled on nodes that meet the specified node selector requirements, but it can still be scheduled on nodes that do not meet those requirements.


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

🔴 A nice cheat sheet of different cloud services.

➡️ What’s included?
- AWS, Azure, Google Cloud, Oracle Cloud, Alibaba Cloud
- Cloud servers
- Databases
- Message queues and streaming platforms
- Load balancing, DNS routing software
- Security
- Monitoring


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

https://blog.prodevopsguy.xyz/the-ultimate-devops-bootcamp-2024-pack-by-prodevopsguy

⚠️ Note: Anyone Interested, can open the Blog 🌐, share it to your friends and colleagues.


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

🔣 Docker is a powerful tool that allows you to package your application and its dependencies into a standardized unit called a container.

👉 𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗯𝗿𝗲𝗮𝗸𝗱𝗼𝘄𝗻 𝗼𝗳 𝗵𝗼𝘄 𝗗𝗼𝗰𝗸𝗲𝗿 𝘄𝗼𝗿𝗸𝘀:

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀 are self-contained units that package your application code, runtime, system tools, settings, and libraries. They're like tiny virtual machines, but they share the underlying operating system kernel with other containers, making them much more lightweight and efficient.

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝗶𝗺𝗮𝗴𝗲𝘀 are blueprints that contain instructions for creating containers. They're kind of like recipes that tell Docker how to build a container with all the necessary ingredients. You can find and share images on public registries like Docker Hub, or create your custom images.

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝗱𝗮𝗲𝗺𝗼𝗻 (𝗱𝗼𝗰𝗸𝗲𝗿𝗱) is the engine that builds, runs, and manages Docker containers. It's the behind-the-scenes workhorse that makes everything tick.

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝗰𝗹𝗶𝗲𝗻𝘁 (𝗱𝗼𝗰𝗸𝗲𝗿 𝗖𝗟𝗜) is the tool you use to interact with the Docker daemon. It allows you to build, run, stop, and manage your containers using commands or a graphical user interface (GUI).

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝗿𝗲𝗴𝗶𝘀𝘁𝗿𝗶𝗲𝘀 are repositories that store and share Docker images. Think of them as libraries for Docker images. Docker Hub is the most popular public registry, but there are also private registries that organizations can use to store their custom images.

➡️𝗗𝗼𝗰𝗸𝗲𝗿 𝘀𝘁𝗼𝗿𝗮𝗴𝗲 𝗱𝗿𝗶𝘃𝗲𝗿𝘀 manage how data is stored and persisted within containers. The default storage driver is overlay2, but there are other options available, such as aufs, zfs, and btrfs.

➡️𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗼𝗿𝘀 like Kubernetes and Swarm are tools that help you manage and scale large deployments of Docker containers. They take care of provisioning, scheduling, and healing your containers, making it easier to run complex applications in production.


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

📌 https://harshhaa.hashnode.dev/real-time-devops-project-deploy-to-kubernetes-using-jenkins-end-to-end-devops-project-cicd

🔗 More DevOps Projects : HERE

🔥🔥🔥🔥🔥🔥🔥🔥

Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬

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

👍 Multi-Stage Build Images used in CICD ♾

➡️ Every microservice should be its own separate container. If you only use a single-stage Docker build, you’re probably missing out on some powerful features of the build process. On the other hand, a multi-stage Docker build has many advantages over a single-stage build for deploying microservices.

➡️ Some Advantages are :
- Optimizes the overall size of the Docker image
- Removes the burden of creating multiple Dockerfiles for different stages
- Easy to debug a particular build stage
- Able to use the previous stage as a new stage in the new environment
- Ability to use the cached image to make the overall process quicker
- Reduces the risk of vulnerabilities found as the image size becomes smaller with multi-stage builds


😎 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

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


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

⚙️ Interested in mastering security practices? Let's embark on your DevSecOps ♾ journey

𝐁𝐢𝐠 𝐨𝐧 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭? ▶️ Jenkins identifies issues early.
𝐍𝐚𝐯𝐢𝐠𝐚𝐭𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬? ▶️ DevSecOps ensures stability.
𝐇𝐢𝐭 𝐚 𝐬𝐲𝐬𝐭𝐞𝐦 𝐟𝐚𝐢𝐥𝐮𝐫𝐞? ▶️ Jenkins guides us back on course.
𝐇𝐢𝐝𝐝𝐞𝐧 𝐭𝐫𝐞𝐚𝐬𝐮𝐫𝐞𝐬 𝐚𝐡𝐞𝐚𝐝 - 𝐜𝐨𝐬𝐭 𝐬𝐚𝐯𝐢𝐧𝐠𝐬! ▶️ Every efficient step counts.
𝐀𝐧𝐨𝐦𝐚𝐥𝐢𝐞𝐬? ▶️ Our AI-powered monitor remains vigilant.

Approaching the finish line, security risks arise, yet DevSecOps mitigates them, instilling confidence. Ultimately, complete awareness of potential threats.


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

📌 Discuss scenarios in which you would prefer Docker Swarm over Kubernetes, or vice versa, for container orchestration 📌

Docker Swarm and Kubernetes are popular container orchestration tools that efficiently manage, scale and deploy containers. Each has its strengths and weaknesses, and understanding these can help you choose the right tool for your specific needs. Differences and scenarios where one might be preferred over the other

✅ Docker Swarm
➡️ Simplicity and Integration: Docker Swarm is known for its simplicity and ease of setup, especially for users already familiar with Docker. It's tightly integrated with Docker, meaning you can use Docker CLI commands to create a swarm, deploy applications, and manage nodes. This integration makes Swarm a more straightforward choice for smaller-scale applications or teams beginning with container orchestration.

➡️ How it works: Docker Swarm uses the standard Docker API, making it compatible with any Docker tool. Swarm managers can delegate tasks to worker nodes, automatically decide the optimal node for container deployment based on resource availability, and manage load balancing and scaling.

✅ Kubernetes
➡️ Complexity and Flexibility: Kubernetes is more complex than Docker Swarm but offers significantly more flexibility, features, and fine-grained control over containers. It supports a wide range of workloads, has extensive integration with cloud services, and has a vast ecosystem.

➡️ How it works: Kubernetes architecture includes a master node (control plane) and worker nodes. The control plane's components (API server, scheduler, etcd, controller manager, etc.) manage the state of the cluster, scheduling, and deployments based on user-defined desired states. Kubernetes uses etcd, a distributed key-value store, to keep the cluster state consistent.

🧐 Prefer Docker Swarm when:
1️⃣ You're looking for simplicity and faster deployment. Docker Swarm is easier to configure and manage, making it suitable for smaller teams or projects with simpler deployment needs.
2️⃣ You have a smaller-scale application or microservices that don't require the extensive features of Kubernetes.
3️⃣ Your team is already comfortable with Docker, and you want to leverage container orchestration without a steep learning curve.

🧐 Prefer Kubernetes when:
1️⃣ You need to manage large-scale, complex applications with high availability and many services. Kubernetes' advanced features and flexibility make it suitable for enterprise-level deployments.
2️⃣ You require advanced deployment strategies (like blue-green deployments, canary releases) and auto-scaling based on traffic or other metrics.
3️⃣ You're leveraging cloud-native technologies and services, as Kubernetes has extensive support from cloud providers and a vast ecosystem of tools and extensions.


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

🔥 Ansible Commands which DevOps Engineers use on daily bases: 🔣

1. ansible-playbook: Executes Ansible playbooks.
ex: ansible-playbook -i <inventory_file> <playbook.yml>

2. ansible: Runs ad-hoc commands or tasks.
ex: ansible all -m copy -a "src=/path/to/local/file dest=/path/to/remote/file"
ansible all -m yum -a "name=httpd state=latest"

3. ansible-galaxy: Manages Ansible roles.
ex: ansible-galaxy install <role_name>

4. ansible-vault: Manages encrypted data within Ansible.
ex: ansible-vault encrypt <file>

5. ansible-galaxy init role_name: Initializes a new Ansible role scaffold.
ex: ansible-galaxy init <role_name>

6. ansible-inventory: Shows Ansible's inventory.
ex: ansible-inventory --list -i /path/to/inventory/hosts

7. ansible-config: Manages Ansible configuration.
ex: ansible-config list, ansible-config view

8. ansible-pull: Pulls playbooks from a version control system and executes them locally.
ex: ansible-pull -U <repository_url> <playbook.yml>

9. ansible-playbook --syntax-check: Checks playbook syntax without executing.
ex: ansible-playbook --syntax-check <playbook.yml>

10. ansible-playbook --list-hosts: Lists hosts defined in a playbook.
ex: ansible-playbook --list-hosts playbook.yml

11. ansible-playbook --tags: Runs specific tagged tasks within a playbook.
ex: ansible-playbook --tags=tag1,tag2 playbook.yml

12. ansible-playbook --limit: Limits playbook execution to specific hosts or groups.
ex: ansible-playbook --limit=<host_pattern> <playbook.yml>

13. ansible-vault edit: Edits an encrypted file.
ex: ansible-vault edit secrets.yml

14. ansible-doc: Displays documentation for Ansible modules.
ex: ansible-doc <module_name>

15. ansible-config view: Displays the current Ansible configuration.
ex: ansible-config view

16. ansible-config dump: Dumps the current Ansible configuration variables.
ex: ansible-config dump

17. ansible-config list: Lists configuration settings.
ex: ansible-config list

18. ansible-console: Starts an interactive console for executing Ansible tasks.
ex: ansible-console

19. ansible-lint: Lints Ansible playbooks for best practices and potential errors.
ex: ansible-lint <playbook.yml>

20. ansible-vault encrypt_string: Encrypts a string for use in a playbook.
ex: ansible-vault encrypt_string <string>

21. ansible-vault rekey: Rekeys an encrypted file with a new password.
ex: ansible-vault rekey <file>


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📌 Exercise Caution When Utilizing the drop_cache 📌

Instead of just looking at the available memory in the free -m output, some users might panic and quickly run the drop_cache command. I strongly advise against doing so.

💻 The command "echo 3 > /proc/sys/vm/drop_cache" is used to clear the disk cache in Linux.

⏩ The different options for the drop_cache command:

🔹 Option 1:
➡️ Command: echo 1 > /proc/sys/vm/drop_cache
➡️ Effect: This option clears the page cache only. It removes unused pages, making more memory available right away.

🔹 Option 2:
➡️ Command: echo 2 > /proc/sys/vm/drop_cache
➡️ Effect: This option clears the directory and file metadata cache. It frees up space used for file information, resulting in faster access to directories and file details.

🔹 Option 3:
➡️ Command: echo 3 > /proc/sys/vm/drop_cache
➡️ Effect: This option combines the effects of options 1 and 2. It clears the page cache and the directory/file metadata cache, providing a more thorough clearing of cached data.

🚨 It's important to note that running these commands requires administrative privileges (root access). It's also worth mentioning that clearing the disk cache using the drop_cache command is usually done in specific cases, such as optimizing system performance, troubleshooting issues, or testing. Clearing the cache without a valid reason may temporarily slow down your system until the cache is filled with relevant data again.

🎬 Always exercise caution and understand the implications before using these commands.


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