ℹ️ 𝐂𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐢𝐧𝐠 𝐇𝐀 𝐨𝐧 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐮𝐬𝐢𝐧𝐠 𝐞𝐭𝐜𝐝, 𝐢𝐭'𝐬 𝐩𝐫𝐨𝐬 & 𝐜𝐨𝐧𝐬 🤔

One of the method of configuring High Availability on Kubernetes is configuring etcd (distributed db) under two modes:
👉 𝐒𝐭𝐚𝐜𝐤𝐞𝐝 𝐞𝐭𝐜𝐝 𝐭𝐨𝐩𝐨𝐥𝐨𝐠𝐲 - This is the default mode of bring-up of distributed database provided by etcd that is brought upon the control plane nodes.
This topology couples the control planes and etcd members on the same nodes.
📌 Pros
✅ Simpler to set up than a cluster with external etcd nodes
✅ Easier for managing replication.
✅ Reduces potential latency and network-related issues as communication is internal
🛑 Cons
❗️ Runs the risk of failed coupling, redundancy is compromised
❗️Co-locating etcd with other Kubernetes components may lead to resource contention, especially in environments with limited resources
❗️Limited Scalability due to by-design nature

👉 𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐞𝐭𝐜𝐝 𝐭𝐨𝐩𝐨𝐥𝐨𝐠𝐲 - Here etcd resides on a separate nodes and each etcd host communicates with the kube-apiserver of each control plane node
📌 Pros
✅ Decouples the control plane and etcd member, losing a control plane instance or an etcd member has less impact and does not affect the cluster redundancy
✅ With an external etcd cluster, one have more control over its scalability independent of k8s cluster, offering more flexibility
✅ External etcd clusters can potentially offer better performance, especially in scenarios where the etcd workload is heavy or requires significant resources
🛑 Cons
❗️ Managing an external etcd cluster adds complexity to the Kubernetes infrastructure
❗️Network issues or latency as it's external to the cluster
❗️Security Concerns as exposing etcd to external networks introduces potential security risk


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

🔔 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤

What it is: A powerful open-source platform designed to automate deploying, scaling, and operating application containers.

➡️𝐂𝐥𝐮𝐬𝐭𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭:
- Organizes containers into groups for easier management.
- Automates tasks like scaling and load balancing.

➡️𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐑𝐮𝐧𝐭𝐢𝐦𝐞:
- Software responsible for launching and managing containers.
- Ensures containers run efficiently and securely.

➡️𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲:
- Implements measures to protect against unauthorized access and malicious activities.
- Includes features like role-based access control and encryption.

➡️𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 & 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲:
- Tools to monitor system health, performance, and resource usage.
- Helps identify and troubleshoot issues quickly.

➡️𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠:
- Manages network communication between containers and external systems.
- Ensures connectivity and security between different parts of the system.

➡️𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬:
- Handles tasks related to the underlying infrastructure, such as provisioning and scaling.
- Automates repetitive tasks to streamline operations and improve efficiency.

➡️𝐊𝐞𝐲 𝐜𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭𝐬:
- Cluster Management: Handles grouping and managing multiple containers.
- Container Runtime: Software that runs containers and manages their lifecycle.
- Security: Implements measures to protect containers and the overall system.
- Monitoring & Observability: Tools to track and understand system behavior and performance.
- Networking: Manages communication between containers and external networks.
- Infrastructure Operations: Handles tasks like provisioning, scaling, and maintaining the underlying infrastructure.


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

🐬 Dockerfile Checklist 👇

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


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

😀. TUTORIALS

🔴 Learn Jenkins! Complete Jenkins Course -
Zero to Hero

🔗 https://lnkd.in/dGrGmhut

🔴 Jenkins CI CD By Mr. Ashok | DevOps Tools

🔗 https://lnkd.in/d9swuiWJ

🔴 Jenkins Full Course | Jenkins Tutorial For Beginners

🔗 https://lnkd.in/d-_qhBXM

🔴 Jenkins Full Course in 4 Hours | Jenkins Tutorial For Beginners

🔗 https://lnkd.in/d-wjPAKh

🔴 Jenkins Tutorial for Beginners

🔗 https://lnkd.in/dDrrsnTg

🔴 Jenkins Full Course

🔗 https://lnkd.in/dRXbYtXd

🔴 Advanced Jenkins tutorial

🔗 https://lnkd.in/dVcxrYE3

🔢. LABS

🔴 Jenkins Tutorial - How to Deploy a Test Server with Docker + Linux (Full Course)

🔗 https://lnkd.in/dNG2jBFN

🔴 Live DevOps Project for Resume - Jenkins
CICD with Git Hub Integration

🔗 https://lnkd.in/dGcmFHMY

🔴 JENKINS PIPELINE FROM SCRATCH

🔗 https://lnkd.in/dm29aWBa

🔴 Amit Kumar Gupta : Cicd Series 1-9

🔗 https://lnkd.in/dvitBdfd

🔴 CICD pipeline for Java application to deploy on kubernetes cluster using Jenkins

🔗 https://lnkd.in/dNG4BaJu

🔴 Jenkins Cicd deployment

🔗 https://lnkd.in/dhNjHvjH

🔴 Mega Real-time End to End DevOps CI/CD Project Git Jenkins Nexus SonarQube| HandsOn Lab

🔗 https://lnkd.in/deCvSKf7

🔴 Setting up CI-CD Pipeline for an E-Commerce App

🔗 https://lnkd.in/dPH4z4Af

🔗 https://lnkd.in/d-xzCR8F

🔴 Jenkins CI/CD Workflow Implementation with Real-time

🔗 https://lnkd.in/daGQ28BC

🔴 Production Ready CI/CD Pipeline Setup

🔗 https://lnkd.in/d_BeVj65


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

👨‍💻 https://harshhaa.hashnode.dev/2023-devops-is-terrible

Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬


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

🌐 https://prodevopsguy.site/posts/devops/devops-roadmap-2024/


✈️ 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.

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

♾ 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

You're Decent at Linux if You Know What Those Directories Mean?? 🐧

The Linux file system used to resemble an unorganized town where individuals constructed their houses wherever they pleased. However, in 1994, the Filesystem Hierarchy Standard (FHS) was introduced to bring order to the Linux file system.

By implementing a standard like the FHS, software can ensure a consistent layout across various Linux distributions. Nonetheless, not all Linux distributions strictly adhere to this standard. They often incorporate their own unique elements or cater to specific requirements.

ℹ️To become proficient in this standard, you can begin by exploring. Utilize commands such as "cd" for navigation and "ls" for listing directory contents. Imagine the file system as a tree, starting from the root (/). With time, it will become second nature to you, transforming you into a skilled Linux administrator.


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

⚙️ 𝐃𝐞𝐯𝐎𝐩𝐬 𝐓𝐨𝐨𝐥 𝐒𝐭𝐚𝐜𝐤 𝐆𝐮𝐢𝐝𝐞❗️

DevOps is all about working together smoothly from start to finish in software making. The right tools are key, and we've got the perfect guide - the DevOps Tool Stack Wheel!

✅ Planning: Use Jira or Trello.
✅ Coding: Try Git or Bitbucket.
✅ Building: Jenkins or CircleCI can help.
✅ Testing: Go for Selenium or JUnit.
✅ Releasing: Use GitLab CI/CD or Travis CI.
✅ Deploying: Docker or Kubernetes are great.
✅ Operating: Pick Ansible or Puppet.
✅ Monitoring: Check out Prometheus or Grafana.

This set of tools has you covered at every step. From the first plan to the final checks, it's everything you need for great DevOps work.💡

Keep an eye out as we explore each tool and how they work together to boost your DevOps projects. Don't miss your chance to step up your DevOps skills!


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

👾 DevOps metrics are crucial for:

1️⃣. Enhancing work quality 🌿

2️⃣. Monitoring progress 📈

3️⃣. Determining the cost of work 💰

➡️ Key DevOps metrics include:

✅ Development metrics (code coverage, churn, build success rate)
✅ Release metrics (deployment frequency, lead time, rollback rate)
✅ Operational metrics (uptime, MTTR, MTTR)


Embrace the power of DevOps metrics and unlock the full potential of your software development lifecycle! 🚀


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

🔔 𝗔𝗿𝗴𝗼𝗖𝗗 𝘃𝘀. 𝗙𝗹𝘂𝘅𝗖𝗗

➡️ 𝐈𝐦𝐚𝐠𝐢𝐧𝐞 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐚𝐬𝐬𝐞𝐦𝐛𝐥𝐞 𝐚 𝐧𝐞𝐰 𝐩𝐢𝐞𝐜𝐞 𝐨𝐟 𝐟𝐮𝐫𝐧𝐢𝐭𝐮𝐫𝐞 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐡𝐨𝐮𝐬𝐞.

In this scenario, GitOps tools are like the robot assistant that follows the blueprint (your Git repository) to ensure every piece fits perfectly.

➡️ 𝗔𝗿𝗴𝗼𝗖𝗗 and 𝗙𝗹𝘂𝘅𝗖𝗗 stand out as two of the leading GitOps tools, automating deployment to Kubernetes clusters efficiently and reliably.

But how do they differ, and which one should you choose?

➡️ 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐤𝐞𝐲 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞𝐬 ↓

𝟏. 𝐒𝐞𝐜𝐫𝐞𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭
↳ ArgoCD: Relies on external tools like Sealed Secrets
↳ FluxCD: Built-in Mozilla SOPS for encrypted secrets

𝟐. 𝐇𝐞𝐥𝐦 𝐒𝐮𝐩𝐩𝐨𝐫𝐭
↳ ArgoCD: Integrates Helm within its application
↳ FluxCD: Uses Helm operator for management

𝟑. 𝐔𝐬𝐞𝐫 𝐈𝐧𝐭𝐞𝐫𝐟𝐚𝐜𝐞
↳ ArgoCD: Native UI with comprehensive overview
↳ FluxCD: Primarily CLI-based, can integrate with other UIs

𝟒. 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞
↳ ArgoCD: Part of broader Argo Project, with various tools
↳ FluxCD: Focuses on continuous delivery, with GitOps toolkit

𝟓. 𝐑𝐁𝐀𝐂
↳ ArgoCD: Built-in RBAC with GUI management
↳ FluxCD: Relies more on Kubernetes RBAC

𝟔. 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐇𝐨𝐨𝐤𝐬
↳ ArgoCD: Robust support for pre/post synchronization hooks
↳ FluxCD: Relies on Helm for hooks outside of Helm charts

𝟕. 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐢𝐧𝐠
↳ ArgoCD: Supports direct deployment templating
↳ FluxCD: Templating capabilities tied to Helm's ecosystem


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

➡️ 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

👉 Continuous deployment assumes 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

😀 10 DevOps Real time Scenarios. 😀
🚀 Issues as well as their resolutions: 🚀

🔢. Continuous Integration Pipeline Failure and its Resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Application experiences performance degradation and becomes slow during high-traffic periods and its resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Deployments are error-prone and inconsistent across different environments and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. The application goes down in production due to an unforeseen issue and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. A security vulnerability is discovered in a component of the application stack and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. Production environments start to deviate from their desired configurations over time and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. A critical service experiences an outage, impacting users and business operations and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. Communication breakdowns between development and operations teams lead to misunderstandings and delays and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. A major release causes unexpected issues in the production environment.
🔗 https://lnkd.in/gYbFKPrv

🔢🔢. Cloud resource costs are increasing beyond budgeted limits.
🔗 https://lnkd.in/gYbFKPrv


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

⛈ Free DevOps Courses


⚡️ Introduction to DevOps : https://lnkd.in/eewbW8xF

⚡️ IBM Applied DevOps Engineering : https://lnkd.in/erfsfEzm

⚡️ Python Scripting for DevOps Specialization : https://lnkd.in/ejaHRK8q

⚡️ Continuous Delivery & DevOps : https://lnkd.in/eBuU9Gb6

⚡️ Introduction to DevOps (Great Learning) : https://lnkd.in/e4h_vt8B

⚡️ Getting Started with DevOps on AWS : https://lnkd.in/ejchJqDN

⚡️ Introduction to DevOps (Codeacademy) : https://lnkd.in/ek-bXi8r

⚡️ DevOps - For Beginners : https://lnkd.in/ecUVWb36

⚡️ DevOps 101: What is DevOps? : https://lnkd.in/ezPfGTkU

⚡️ Bonus: Live Workshop - https://brij.guru/ai


🛒 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

⚜️ 𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 💬 𝐖𝐡𝐚𝐭𝐬𝐀𝐩𝐩 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞

Have you ever wondered how WhatsApp, the messaging titan, keeps your chats flowing seamlessly?


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

🔣🔣 Kubernetes Scaling Strategies 👇

Each scaling strategy offers a unique approach to efficiently manage resources and ensure optimal performance:

1️⃣. Horizontal Pod Autoscaling (HPA):
Automatically scales the number of pods in a deployment or replica set based on observed CPU utilization or other select metrics.

2️⃣. Vertical Pod Autoscaling (VPA):
Automatically adjusts the CPU and memory resources allocated to pods in a deployment or replica set.

3️⃣. Cluster Autoscaling:
Dynamically adjusts the number of nodes in a Kubernetes cluster based on the demands of the workloads and resource availability.

4️⃣. Manual Scaling:
Involves manually setting the number of replicas in a deployment or replica set, using a command like

kubectl scale --replicas=desired_replica_count object_type/object_name

5️⃣. Predictive Scaling:
Uses advanced algorithms and AI, like in PredictKube, to forecast future demand and proactively scale resources before they are needed.


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