🛠 Implementation of the Entire Advanced CI/CD Pipeline with Major DevOps Tools 🛠

➡️ Project Link : HERE

💥 Included Step by Step procedure
💥 Easy Understanding guide
💥 Used DevOps advanced Tools
💥 Each & Every Commands used in project are Included
💥 Tools used in Project :
✅ Jenkins
✅ Docker
✅ Kubernetes
✅ Ansible
✅ Terraform
✅ Prometeous
✅ Maven
✅ AWS
✅ SonarQube
✅ SonarCloud
✅ JFrog

Hit the Star! 🌟 & Follow me on GitHub for more like this

If you are planning to use this repo for learning, please hit the star.


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

☄️ Here is the process for how Projects/companies build a successful project outcomes.....


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

🆘 How do we manage configurations in a system?

The diagram shows a comparison between traditional configuration management and IaC (Infrastructure as Code).


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

☁️ Git Branching Strategies: Navigate the Options for a Robust CI/CD Pipeline

Choosing the right Git branching strategy is crucial for streamlining your CI/CD pipeline and maintaining a healthy codebase.

Here's a breakdown of popular strategies, their differences, and how to select the best fit for you:

𝟭. 𝗚𝗶𝘁𝗙𝗹𝗼𝘄:
➡️Focus: Structured workflow with separate branches for features, releases, hotfixes, and development.
➡️Pros: Well-defined roles for each branch, reduces merge conflicts, suitable for large teams.
➡️Cons: Overhead of managing many branches, complex for smaller teams, potential merge fatigue.

𝟮. 𝗚𝗶𝘁𝗵𝘂𝗯 𝗙𝗹𝗼𝘄:
➡️Focus: Simpler approach, primarily relies on feature branches and pull requests.
➡️Pros: Lightweight, easy to use, encourages collaboration and code review.
➡️Cons: Can lead to merge conflicts if not managed carefully, not ideal for complex releases.

𝟯. 𝗧𝗿𝘂𝗻𝗸-𝗯𝗮𝘀𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 (𝗚𝗶𝘁𝗟𝗮𝗯 𝗙𝗹𝗼𝘄):
➡️Focus: Continuous integration directly onto the main branch, using feature flags for experimentation.
➡️Pros: Faster deployments, reduces merge friction, encourages frequent testing.
➡️Cons: Requires stricter discipline to avoid breaking changes, less suitable for projects with high risk of regressions.

𝟰. 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗕𝗿𝗮𝗻𝗰𝗵 𝗙𝗹𝗼𝘄:
➡️Focus: Similar to Github Flow, but with dedicated release branches for deployments.
➡️Pros: Balances simplicity with some release control, good for teams comfortable with feature branches.
➡️Cons: Adds complexity compared to Github Flow, not as structured as GitFlow.

𝟱. 𝗚𝗶𝘁𝗞𝗿𝗮𝗸𝗲𝗻 𝗙𝗹𝗼𝘄:
➡️Focus: Integrates GitFlow concepts with elements of Github Flow, allowing for flexible customization.
➡️Pros: Adaptable to various team sizes and workflows, promotes continuous integration and testing.
➡️Cons: Requires more configuration and understanding compared to simpler strategies.


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

📌 https://harshhaa.hashnode.dev/how-to-deploy-daemonsets-service-in-kubernetes-k8s

🔗 More DevOps Blogs : HERE

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Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬

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

🔴 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐰𝐢𝐭𝐡 𝐆𝐫𝐚𝐟𝐚𝐧𝐚, 𝐋𝐨𝐤𝐢, 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 𝐀𝐠𝐞𝐧𝐭

Visualizing logs, metrics, and traces has never been easier!

This diagram illustrates the seamless integration between Grafana, Loki, and the Grafana Agent, enabling you to collect, visualize, and analyze all your observability data in one place.

➡️ 𝐇𝐞𝐫𝐞'𝐬 𝐡𝐨𝐰 𝐢𝐭 𝐰𝐨𝐫𝐤𝐬:

✅ 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 𝐀𝐠𝐞𝐧𝐭: Collects logs from various sources, including your firewall, filesystem, applications, and Kubernetes clusters. It also scrapes Prometheus metrics and discovers Prometheus targets and rules.

✅ 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 𝐋𝐨𝐤𝐢: Centralizes log storage and management, allowing you to query and analyze your logs efficiently.

✅ 𝐆𝐫𝐚𝐟𝐚𝐧𝐚: Provides a powerful and user-friendly interface for visualizing all your logs, metrics, and traces. You can create dashboards and alerts to monitor your system health and performance in real-time.

𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐮𝐬𝐢𝐧𝐠 𝐆𝐫𝐚𝐟𝐚𝐧𝐚, 𝐋𝐨𝐤𝐢, 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 𝐀𝐠𝐞𝐧𝐭 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫:

✅ 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐨𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲: Gain a deeper understanding of your system's health and performance by visualizing all your data in one place.

✅ 𝐅𝐚𝐬𝐭𝐞𝐫 𝐭𝐫𝐨𝐮𝐛𝐥𝐞𝐬𝐡𝐨𝐨𝐭𝐢𝐧𝐠: Quickly identify and diagnose issues with the help of centralized logs and real-time monitoring.

✅ 𝐒𝐢𝐦𝐩𝐥𝐢𝐟𝐢𝐞𝐝 𝐝𝐚𝐭𝐚 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Streamline your data collection and analysis workflows with a unified platform.


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

♾ CI/CD Triggers: Cron Job vs. Poll SCM vs. Webhook

These triggers are responsible for initiating the execution of automated build processes based on specific events or schedules.

⏩ Cron Job: A cron job is a scheduled task or command that is executed at specified intervals according to the cron schedule.

⏩ Poll SCM: It is a mechanism used by CI/CD systems to periodically check the source code repository (SCM) for changes.

⏩ Webhook: It is used for automatically triggering actions when certain events occur.


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

⚡️ 𝐀 𝐐𝐮𝐢𝐜𝐤 𝐂𝐥𝐨𝐮𝐝 𝐂𝐨𝐦𝐩𝐚𝐫𝐢𝐬𝐨𝐧 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭❗️

In today's tech-driven world, selecting the perfect cloud service can be a game-changer for your business.

To make your decision a bit easier, I've put together a quick comparison cheat sheet of some popular cloud providers: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).


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

🔣Exploring Kubernetes 🚀 Let's talk about scaling applications!

📌 When it comes to running applications on Kubernetes, we don’t run an individual pod. Because Kubernetes is all about 𝐬𝐜𝐚𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧𝐢𝐧𝐠 the availability of pods.

📌 So if you run a single pod, it will be a 𝐬𝐢𝐧𝐠𝐥𝐞 𝐩𝐨𝐢𝐧𝐭 𝐨𝐟 𝐟𝐚𝐢𝐥𝐮𝐫𝐞. Because the Pods themselves cannot be directly scaled.

📌 we need controllers like Replicaset to ensure the desired number of pods are running at all times. Kubernetes has different types of objects associated with pods for different use cases.

The following are important pod-associated objects.
📍𝐑𝐞𝐩𝐥𝐢𝐜𝐚𝐬𝐞𝐭 : To maintain a stable set of Pods replicas running at any given time.
📍𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 : To run stateless applications like web servers, APIs, etc
📍𝐒𝐭𝐚𝐭𝐞𝐟𝐮𝐥𝐒𝐞𝐭𝐬 : To run stateful applications like distributed databases.
📍𝐃𝐚𝐞𝐦𝐨𝐧𝐬𝐞𝐭𝐬 : To run agents on all the Kubernetes nodes.
📍𝐉𝐨𝐛𝐬 : For batch processing.
📍𝐂𝐫𝐨𝐧𝐉𝐨𝐛𝐬 : Scheduled Jobs.


✈️ 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

☁️ AWS now provides an API to programmatically track free-tier usage.

🔣It provides:
a. actual usage
b. forecasted usage
c. no data if usage is greater than the limit.
d. free-tier limit

Though it can be done via alerts, it is helpful to programmatically limit resource consumption based on the usage data provided and an understanding of what the amount will be after the free tier limit is reached.

Once, I forgot to shut down an EC2 machine and one DocumentDB instance and the final bill was $$$. 😀

🔗 https://lnkd.in/g5Ve8-6e


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

Let's talk about Kubernetes Gateway API.

It is a new way to manage traffic to Kubernetes services. 🤠

🔣How is it different from Ingress?
Ingress focuses on routing HTTP traffic.
While Gateway API supports a wider range of protocols, including HTTP, TCP, and gRPC.

🔣It also supports:

➡️HTTP Routing & TCP Routing
➡️HTTP Traffic Splitting (10% to service-1 and 90% to service-2)
➡️Cross-Namespace Routing
➡️Role-Based Access Control
➡️Enhanced Secuirty Controls


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

📌 Top 5 Kafka use cases

Kafka was originally built for massive log processing. It retains messages until expiration and lets consumers pull messages at their own pace.

➡️ Let’s review the popular Kafka use cases.
- Log processing and analysis
- Data streaming in recommendations
- System monitoring and alerting
- CDC (Change data capture)
- System migration


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

📌 𝐂𝐥𝐨𝐮𝐝 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 🚀

Cloud security is the top priority for any business because it ensures the safety and privacy of their digital assets in the cloud.


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

🔔 Free Resources for End-to-End DevOps ♾ Learning:


🐧 𝗟𝗶𝗻𝘂𝘅:
- The Linux Foundation: https://lnkd.in/epkP5dYQ
- Linux Documentation: https://lnkd.in/eWNYW246
- Fedora Project: fedoraproject.org

🐍 𝗦𝗰𝗿𝗶𝗽𝘁𝗶𝗻𝗴:
- Python: learnpython.org
- Go: go.dev/tour
- Automate with Python: automatetheboringstuff.com
- Golang Bootcamp: https://lnkd.in/eSsK7KUG

🤖 𝗔𝗜 𝗳𝗼𝗿 𝗗𝗲𝘃𝗼𝗽𝘀:
- GenAI - https://brij.guru/ai

🌐 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴:
- Cisco Networking Academy: netacad.com
- Networking Fundamentals: https://lnkd.in/eQ62Bfza
- Networking: A Top-Down Approach: kurose.cslash.net
- FreeCodeCamp's Course: https://lnkd.in/ecAsMH2w

🧑‍💻 𝗚𝗶𝘁:
- Git SCM: git-scm.com
- Try Git: github.com/Try
- Git Tutorials: https://lnkd.in/eDbQBQfD
- Git Interactive Tutorial: https://lnkd.in/eqfE2ZC4

🐳 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀:
- Docker Documentation: docs.docker.com
- Docker Hub: hub.docker.com
- Docker Labs: dockerlabs.collabnix.com
- Kubernetes Fundamentals: https://lnkd.in/eurRUTSt

☁️ 𝗖𝗹𝗼𝘂𝗱:
- AWS Free Tier: aws.amazon.com/free
- Microsoft Azure Free Account: https://lnkd.in/ehxD777x
- Google Cloud Platform Free Tier: cloud.google.com/free
- Cloud Academy: cloudacademy.com

⚙️ 𝗖𝗜/𝗖𝗗:
- Jenkins: jenkins.io
- Travis CI: https://lnkd.in/eDTJtRjB
- CircleCI: circleci.com
- GitLab CI/CD: docs.gitlab.com/ee/ci

🧩 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻:
- Kubernetes Documentation: kubernetes.io/docs/home
- Kubernetes the Hard Way: https://lnkd.in/edWs7_FW
- CNCF Curriculum: cncf.io
- Kubernetes Fundamentals: https://lnkd.in/e55BRxGy

🔍 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆:
- Prometheus: prometheus.io
- Grafana: grafana.com
- Elasticsearch: elastic.co
- Jaeger: https://lnkd.in/eiFkzXwD

📜 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 (𝗜𝗮𝗖):
- Terraform: terraform.io
- AWS CloudFormation: https://lnkd.in/e4wGb2eT
- Azure Resource Manager: https://lnkd.in/eWzjg94i
- Deployment Manager: https://lnkd.in/ekAQpT3n

🔏 𝗣𝗼𝗹𝗶𝗰𝘆 𝗮𝘀 𝗖𝗼𝗱𝗲:
- Open Policy Agent: https://lnkd.in/eG4jMZSU
- Kyverno: kyverno.io/docs
- Rego: https://lnkd.in/eD75meCB

🕸 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗠𝗲𝘀𝗵:
- Istio: https://lnkd.in/eaxdAMZC
- Linkerd: linkerd.io
- Consul Service Mesh: https://lnkd.in/eEn3eacn


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🔴 𝐈𝐦𝐩𝐫𝐨𝐯𝐢𝐬𝐢𝐧𝐠 𝐏𝐨𝐝 𝐒𝐭𝐚𝐫𝐭-𝐮𝐩 𝐭𝐢𝐦𝐞 𝐢𝐧 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐭𝐡𝐨𝐮𝐠𝐡 𝐈𝐦𝐚𝐠𝐞 𝐂𝐚𝐜𝐡𝐢𝐧𝐠 ☸️ 🤔

Delay in Pod startup for an application workload can be often attributed to the time taken to pull necessary container images from the registry.

❗️ 𝑰𝒎𝒑𝒂𝒄𝒕
👉 For #Kuberenetes clusters requiring auto-scaling, the delay in pulling a #OCI compliant image can take a longer time, sometimes leading to network timeout (if the image pull doesn't go through the kubelet defined time-period)
👉 Further in situations where application needs to scale out horizontally or process high-speed real-time data, this may have compounding effect on the availability of the application

💥 𝑺𝒐𝒍𝒖𝒕𝒊𝒐𝒏
✅ The probable solution needs to have a cache layer on top of #k8s, so that Kubernetes has a centralized image cache and all nodes “pull” from it
✅ To accelerate image caching, the solutions needs to sit inside #k8s, and all nodes should have the fastest latency towards it.

A handful of #oss projects & tools helps in achieving the objective:
📍 𝐇𝐚𝐫𝐛𝐨𝐫 (https://lnkd.in/dqWZNwnh)
✍️ A pull-through proxy cache performs caching mechanism designed to optimize the distribution and retrieval of container images within a #container registry environment. It acts as an intermediary between clients (such as container runtimes or build systems) and the upstream container registry.

📍 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬-𝐢𝐦𝐚𝐠𝐞-𝐩𝐮𝐥𝐥𝐞𝐫 (https://lnkd.in/dXXghvqt)
✍️ Deploys a huge number of containers (one container per image and per node / uses a daemonset for the caching mechanism), to fulfill the caching feature.

📍 𝐓𝐮𝐠𝐠𝐞𝐫 (https://lnkd.in/dcemgYbC)
✍️ Uses a single configuration file, defined through its Helm file values. It does not allow us to segregate “system” configurations (eg : exclude specific images from the caching system) and “users” configurations

📍 𝐊𝐮𝐛𝐞-𝐢𝐦𝐚𝐠𝐞-𝐤𝐞𝐞𝐩𝐞𝐫 (𝐤𝐮𝐢𝐤) (https://lnkd.in/dFCk9jur)
✍️ #Container image caching system for Kubernetes. It saves the container images used by your pods in its own local registry so that these images remain available if the original becomes unavailable.

📍 𝐊𝐮𝐛𝐞-𝐟𝐥𝐞𝐝𝐠𝐞𝐝 (https://lnkd.in/deSUwCbn)
✍️ Kubernetes add-on or operator for creating and managing a cache of container images directly on the worker nodes of a kubernetes cluster. It allows a user to define a list of images and onto which worker nodes those images should be cached (i.e. pulled). As a result, application pods start almost instantly, since the images need not be pulled from the registry


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🔣 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐃𝐞𝐯𝐎𝐩𝐬, 𝐒𝐑𝐄, 𝐚𝐧𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐑𝐨𝐥𝐞𝐬❓


🔣In today's fast-evolving software landscape, three key pillars have emerged to reshape the way we build, deploy, and maintain software: Site Reliability Engineering (SRE), DevOps, and Platform Engineering. These dedicated teams each bring a unique set of skills, responsibilities, and tools to the table, fostering collaboration and efficiency throughout the software development lifecycle


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⚡️ If you are serious about securing your Kubernetes.. ⚡️

You should know these 15 plugins

𝟭. 𝗦𝘁𝗲𝗿𝗻: Enhances log monitoring with regex support for Pod and Container IDs, similar to 'tail -f'.
🔣GitHub URL: https://lnkd.in/gbFmpTUu

𝟮. 𝗥𝗕𝗔𝗖-𝘁𝗼𝗼𝗹: Simplifies querying and creating RBAC policies, with visualization features.
🔣GitHub URL: https://lnkd.in/ggqV8yGd

𝟯. 𝗸𝘂𝗯𝗲𝗰𝘁𝗹-𝗰𝗶𝗹𝗶𝘂𝗺: Manages Cilium network security, providing eBPF dataplane capabilities.
🔣GitHub URL: https://lnkd.in/gUE6kTwK

𝟰. 𝗞𝘂𝗯𝗲 𝗣𝗼𝗹𝗶𝗰𝘆 𝗔𝗱𝘃𝗶𝘀𝗼𝗿: Advises on PodSecurityPolicies and OPA Policies, enhancing admission control.
🔣GitHub URL: https://lnkd.in/gnWCssCe

𝟱. 𝗞𝘂𝗯𝗲𝗰𝘁𝗹-𝘀𝘀𝗺-𝘀𝗲𝗰𝗿𝗲𝘁: Facilitates the import/export of Kubernetes Secrets to/from AWS SSM Parameter Store.
🔣GitHub URL: https://lnkd.in/gpr3sT7t

𝟲. 𝗞𝘂𝗯𝗲𝗹𝗼𝗴𝗶𝗻: Streamlines logging into Kubernetes clusters via CLI with OpenID Connect providers.
🔣GitHub URL: https://lnkd.in/gEtsDwu6

𝟳. 𝗞𝘂𝗯𝗲𝗰𝘁𝗹-𝘄𝗵𝗶𝘀𝗽𝗲𝗿-𝘀𝗲𝗰𝗿𝗲𝘁: Improves secret creation with secure input prompts, protecting against leaks.
🔣GitHub URL: https://lnkd.in/gCWuDaPE

𝟴. 𝗞𝘂𝗯𝗲𝗰𝘁𝗹-𝗰𝗮𝗽𝘁𝘂𝗿𝗲: Enables packet capture for container troubleshooting and security investigations.
🔣GitHub URL: https://lnkd.in/gbH99RmX

𝟵. 𝗞𝘂𝗯𝗲𝗰𝘁𝗹-𝘁𝗿𝗮𝗰𝗲: Facilitates distributed tracing in Kubernetes, aiding in security and performance analysis.
🔣GitHub URL: https://lnkd.in/gxrKacca

𝟭𝟬. 𝗔𝗰𝗰𝗲𝘀𝘀-𝗺𝗮𝘁𝗿𝗶𝘅 (𝗥𝗮𝗸𝗸𝗲𝘀𝘀): Displays an access matrix for server resources, highlighting CRUD permissions.
🔣GitHub URL: https://lnkd.in/gGKhsv6r

𝟭𝟭. 𝗥𝗼𝗹𝗲𝘀𝘂𝗺: Generates a summary of roles and permissions in the cluster, aiding in access control reviews.
🔣GitHub URL: https://lnkd.in/g8Xa2YQA

𝟭𝟮. 𝗖𝗲𝗿𝘁-𝗠𝗮𝗻𝗮𝗴𝗲𝗿: Automates TLS certificate management, ensuring secure and up-to-date communication.
🔣GitHub URL: https://lnkd.in/gBiqWjwV

𝟭𝟯. 𝗻𝗽-𝘃𝗶𝗲𝘄𝗲𝗿: Visualizes network policies and topologies, helping to identify misconfigurations.
🔣GitHub URL: https://lnkd.in/g6hYgp7t

𝟭𝟰. 𝗸𝘀𝗻𝗶𝗳𝗳: Captures and analyzes network traffic for security assessments and troubleshooting.
🔣GitHub URL: https://lnkd.in/gWQhM9_q

𝟭𝟱. 𝗜𝗻𝘀𝗽𝗲𝗸𝘁𝗼𝗿-𝗚𝗮𝗱𝗴𝗲𝘁: The eBPF tool and systems inspection framework for Kubernetes, containers and Linux hosts.
🔣GitHub URL: https://lnkd.in/gK7i_Tgb


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🔣Kubernetes Mind Map 2024🔣


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