🎙 DevOps Day to Day Activities. 👾

The daily activities of a DevOps engineer can vary depending on the specific organization, project, and team structure.

However, here are some common tasks and responsibilities that DevOps engineers typically engage in on a day-to-day basis:

➕1. Collaboration and Communication: Collaborate with cross-functional teams and attend project status meetings to discuss issues and planning.

➕2. Infrastructure as Code (IaC): Write, review, and maintain infrastructure code using Terraform, Ansible, or CloudFormation. Automate infrastructure provisioning and configuration.

➕3. Continuous Integration/Continuous Deployment (CI/CD): Enhance CI/CD pipelines for automated build, test, and deployment. Troubleshoot pipeline issues.

➕4. Version Control: Work with version control systems (e.g. Git) to manage and version codebase and infrastructure configurations.

➕5. Monitoring and Logging: Set up and maintain monitoring tools to ensure the health and performance of systems. Analyze logs and metrics to identify and address issues proactively.

➕6. Containerization and Orchestration: Work with containerization technologies like Docker. Manage container orchestration tools like Kubernetes for deploying and scaling applications.

➕7. Automation Scripting: Write scripts (e.g., Bash, Python, PowerShell) to automate repetitive tasks and streamline processes.

➕8. Security: Implement security best practices for infrastructure and applications. Work on identifying and mitigating security vulnerabilities.

➕9. Collaborative Tools: Use collaborative tools for communication, documentation, and project management (e.g., Slack, Jira, Confluence).

➕10. Incident Response: Respond to and resolve incidents, and work on post-incident analysis and improvement.

➕11. Infrastructure Monitoring: Monitor server and application performance. Set up alerts and notifications for critical events.

➕12. Capacity Planning: Assess and plan for the scalability of systems and infrastructure.

➕13. Knowledge Sharing: Share knowledge with team members and contribute to documentation. Stay updated on industry trends and emerging technologies.

➕14. Continuous Learning: Stay informed about new tools, technologies, and best practices in the DevOps space. Attend relevant conferences, webinars, or training sessions.

➕15. Deployment and Release Management: Plan and execute software releases, ensuring smooth deployment and rollback processes.


🔵 Follow for more: @prodevopsguy

☄️ EXCLUSIVE WITH SOURCE CODE (SCRIPTS INCLUDED) ☄️

🔥 Zomato Clone: Secure Deployment with DevSecOps CI/CD

💎 Blog LINK : https://harshhaa.hashnode.dev/zomato-clone-secure-deployment-with-devsecops-cicd

💎 Source Code LINK : https://github.com/NotHarshhaa/Zomato-Clone

🌐FORK THE REPO


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

📣 New to DevOps? 📣

Here are the most widely used tools in the industry along with their official documentation:

➡️ Source Code Management:

1. Git: https://git-scm.com/docs
2. GitHub: https://docs.github.com/en
3. Bitbucket: https://lnkd.in/dA2PcM_w

➡️ Ticketing Tools:

1. Service Now: https://lnkd.in/d69yubJF
2. Jira: https://lnkd.in/dD_WcXFQ
3. Trello: https://trello.com/guide

➡️ Public Clouds:

1. AWS: https://lnkd.in/dMa9XpMa
2. Azure: https://lnkd.in/dBsJtZHy
3. GCP: https://lnkd.in/d3hmN-Jr

➡️ Containerization and Orchestration Tools:

1. Docker: https://docs.docker.com/
2. Kubernetes: https://lnkd.in/dZXfQEqW
3. Mesos: https://lnkd.in/dqzvzJhY

➡️ Deployment Tools:

1. Terraform: https://lnkd.in/dM46h2_D
2. Octopus: https://octopus.com/docs
3. Heroku: https://lnkd.in/dCDuwvcj

➡️ Testing Tools:

1. Selenium: https://lnkd.in/dTnFN8bT
2. Cucumber: https://lnkd.in/dpmD4A9C
3. Postman: https://lnkd.in/d3xERi6c

➡️ Build Tools:

1. Maven: https://lnkd.in/dfgBnrZj
2. Gradle: https://lnkd.in/dv6rQczZ
3. Ant: https://lnkd.in/dQgMsgef

➡️ Pipeline Tools:

1. Jenkins: https://lnkd.in/dPmA6-ff
2. TravisCI: https://lnkd.in/dxxFaK_X
3. Argo CD: https://lnkd.in/dK5eXbYi

➡️ Monitoring Tools:

1. Grafana: https://lnkd.in/dX5anVq9
2. Prometheus: https://lnkd.in/ddxjc9bV


🚀 Follow for more DevOps content, tips and tricks, and Hands-On Project Implementation.


🔵 Follow for more: @prodevopsguy

🚀 Excited to share the power of Prometheus in the world of 𝐃𝐞𝐯𝐎𝐩𝐬! 🌐

👉 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐏𝐫𝐨𝐦𝐞𝐭𝐡𝐞𝐮𝐬?
Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It's your go-to companion for gaining deep insights into your infrastructure and applications.

Here are some key points highlighting the advantages and applications of Prometheus:

🔢. 𝐑𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 📊:
➡️ Prometheus provides robust real-time monitoring, allowing DevOps teams to gain insights into system performance and quickly identify issues.

🔢. 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 🚀:
➡️ Its scalable architecture makes Prometheus suitable for both small-scale setups and large, complex environments, ensuring adaptability as your infrastructure grows.

🔢. 𝐌𝐮𝐥𝐭𝐢-𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥 𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥 🔄:
➡️ Embrace the flexibility of Prometheus' multi-dimensional data model, which simplifies querying and reporting, providing a comprehensive view of your system.

🔢. 𝐀𝐥𝐞𝐫𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐍𝐨𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 🚨:
➡️ Enjoy proactive alerting capabilities that empower teams to detect anomalies and potential issues before they impact users, enabling a more reliable and resilient infrastructure.

🔢. 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 🌐:
➡️ Prometheus seamlessly integrates with service discovery mechanisms, making it an excellent choice for dynamic environments where instances and services may change dynamically.

🔢. 𝐑𝐢𝐜𝐡 𝐐𝐮𝐞𝐫𝐲 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 💬:
➡️ Leverage Prometheus Query Language (PromQL) to perform complex queries and obtain meaningful insights, enabling a deep dive into the performance metrics of your applications.

🔢. 𝐎𝐩𝐞𝐧 𝐒𝐨𝐮𝐫𝐜𝐞 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲 🤝:
➡️ Engage with a vibrant and supportive open-source community that continually contributes to Prometheus' development, ensuring a cutting-edge and evolving monitoring solution.

🔢. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 📈:
➡️ Combine the power of Prometheus with Grafana for visually appealing and interactive dashboards, providing a user-friendly interface for monitoring and analysis.

🔢. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 🐳:
➡️ Prometheus natively supports containerized environments, making it an ideal choice for organizations embracing container orchestration platforms like Kubernetes.

🔢🔢. 𝐂𝐥𝐨𝐮𝐝-𝐍𝐚𝐭𝐢𝐯𝐞 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 ☁️:
➡️ Seamlessly adapt Prometheus to your cloud-native ecosystem, gaining visibility into distributed architectures and microservices.


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

Just had an Great interview experience for the role of a DevOps Engineer with 1-2 years of experience! ✨

I recently had the opportunity to interview for a DevOps Engineer position, and I wanted to share some of the questions that were asked during the process. Whether you're preparing for a similar role or just interested in the DevOps field, I hope you find these questions helpful!

✅ Regarding Self Introduction and DevOps:
1) Could you Please Introduce yourself Briefly about your background and your project ?
2) What Does DevOps Means and how DevOps is Different from Other Department in IT Industry ?
3) What Happen when DevOps comes in IT Industry ?
4) Could you please Explain me About your last project have you worked on and what was you roles and responsibility ?

✅ About Linux OS:
1) What are Different OS have you Familiar with and worked on ?
2) What is Kernel ?
3) which Linux version you used in your project ?
4) why we Used Linux OS Rather than Windows and any other ?

✅ About Git GitHub and Gitlab:
1) What is Git, GitHub and Gitlab what is the difference between them ?
2) what is Merge and Rebase ?
3) How do you revert a commit in Git ?
4) Explain the difference between Git pull and Git fetch ?
5) Explain the Branching Strategies have you used in your project

✅ About CICD with Jenkins:
1) what is CICD and explain me the Jenkins file and Its Stages ?
2) In which phase Testing will do In CI phase or in CD phase ?
3) how did you used Jenkins in your project ?
4) Describe the process of setting up a Jenkins job to automate a build process ?

✅ About Docker and K8S:
1) What Does mean by containerization and Orchestration ?
2) What is a Docker image, and how is it different from a Docker container?
3) How do you manage data persistence in Docker containers?
4) Have you Used docker Compose ?
5) could you Explain me a Docker File for Node ?
6) How do you secure a MySQL Data which is Running in my container ?
7) what is Ingress and Deployment in K8S ?
8) what is Services in K8S ?
9) How can K8S control and manage a containers ?

✅ Some Scenarios Questions:
1) Your company is planning to implement a disaster recovery (DR) strategy for its critical services hosted on AWS. Describe the steps you would take to design and implement a robust DR plan, including backup strategies, failover mechanisms, and testing procedures.


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

📌 Describe strategies for scaling Terraform configurations in large enterprise 📌

Terraform has emerged as a foundation for provisioning infrastructure as code (IaC), but scaling it across large enterprises presents unique challenges. Here's an approach to scale your Terraform strategies:

🏗 Infrastructure Organization
✔️ Sort Your Projects: Group your Terraform setups meaningfully, like by function or whether they're for testing, staging, or live environments. This will help everyone stay on track and minimize mix-ups.
✔️ Workspaces Are Your Friend: Terraform's workspaces allow you to handle different settings without juggling too many files. It's like having separate desks for each project and keeping things tidy.

🧩 Module Design
✔️ Build Once, Use Everywhere: Create Terraform modules for tasks you do often and store them in one place. It's like keeping your tools in a toolbox, ready whenever needed.
✔️ Keep Versions Clear: When you update a module, label it appropriately. Implement semantic versioning for modules to safely manage changes and ensure your infrastructure aligns precisely with the tested versions.

💾 State Management at Scale
✔️ Safe Storage for State Files: Utilize remote backends like AWS S3, coupled with state locking via DynamoDB, to ensure a shared, versioned, and concurrent write-protected state, essential for collaborative environments.
✔️ Break It Down: Split your Terraform state into smaller pieces to keep things clear and quick.

⚙️ CI/CD Integration
✔️ Automate the Routine: Use tools like Jenkins or GitHub Actions to set up automatic pipelines for your Terraform work.
✔️ Rules Matter: Incorporate HashiCorp Sentinel or OPA to enforce compliance and governance policies automatically, securing and standardizing infrastructure provisioning.


😎 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

🎮 Azure DevOps Guide: 🧠

Create a CI/CD Pipeline for Python application in Azure DevOps with integrate with Azure Repos with pipeline script of deployment and test stages and finally push to Azure Artifacts


🌐 Link: https://github.com/NotHarshhaa/DevOps_Setup-Installations/blob/master/azure-devops/setup-cicd.md

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

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


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

🔥 AWS Cloud ☁️ 🆓 Videos 📷


🟡 Part 1: https://drive.google.com/drive/folders/17Q3Tf3PEfmq_cGM97brqO3oCR0EPLFC8?usp=sharing

🟡 Part 2: https://drive.google.com/drive/folders/1bl8WhtUkWUXQh4XSm8_Nhf6Ykqu5rY-3?usp=sharing


❤️ Follow for more: @prodevopsguy

🟩 AWS & DevOps Free Videos :– 🟩


🗯 Part -1 : https://drive.google.com/drive/folders/1P2MORPWWUDk6MBzLktlahDRHJgh9YNta?usp=sharing

🗯 Part -2: https://drive.google.com/drive/folders/1-9pCWtNrSwWW3Bgd0BjqfH_x0sfJcXvE?usp=sharing

🗯 Part -3 : https://drive.google.com/drive/folders/1OD3B97MfmlQbnBVB_PMbt5bb5mtjyQk9?usp=sharing

❤️ Follow for more: @prodevopsguy

➡️Docker 🐬 and Kubernetes Free Videos 🟩 :

✅Link: https://drive.google.com/drive/folders/162YOHhybk_pYemCfKmKSGbdSjJDeuAYR?usp=sharing


❤️ Follow for more: @prodevopsguy

🟩 Docker Free Videos 🐬

🔗Link : https://drive.google.com/drive/folders/1lXSplxsWu-7f4Bbb3V9o-Em4XUahWVeD?usp=sharing


❤️ Follow for more: @prodevopsguy

🟩 Ansible 🆓 Videos 🔴

🔗Link : https://drive.google.com/drive/folders/1p35HHSamOyL1Rta8hK5--4k1mPWYAXaV?usp=sharing


❤️ Follow for more: @prodevopsguy

🟩 🌐 Git/GitHub Free Videos:- 🟩

🔥 ➡️ https://drive.google.com/drive/folders/1vhSsxz9oAtSh136JVo3gryaDPJAYWteF?usp=sharing

❤️ Follow for more: @prodevopsguy

📢 Sidecar container in kubernetes:

Sidecar container is a design pattern where an additional container is deployed alongside the main container within the same Pod. The sidecar container runs in the same execution environment and shares the same resources (network namespace, IPC namespace, etc.) with the main container. Sidecar containers are often used to extend or enhance the functionality of the main application container without modifying its codebase directly.
Here are some common use cases for sidecar containers:

📢 Logging: A sidecar container can be used to collect, format, and forward logs generated by the main application container to a centralized logging system.

📢 Monitoring: Sidecar containers can be used to collect metrics, health checks, or other telemetry data from the main application container and expose it to monitoring systems like Prometheus.

📢 Security: A sidecar container can handle tasks such as managing SSL certificates, providing authentication, or enforcing security policies independently of the main application.

📢 Data Processing: Sidecar containers can be used for tasks like data transformation, caching, or pre-processing data before it's consumed by the main application.


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

🎙 Kubernetes is an open-source 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 system for automating software deployment, scaling, and management.

➡️ Features:
✅ Load balancing
✅ Self-healing
✅ High availability / Ensure no downtime / Maintain fault tolerance
✅ Performance enhancement
✅ Auto-scaling

Several key components of Kubernetes are important to understand:

𝗣𝗼𝗱 ➡️ Represents one or more containers running in a cluster.
𝗦𝗲𝗿𝘃𝗶𝗰𝗲 ➡️ An abstract way to access pod/application.
𝗡𝗮𝗺𝗲𝘀𝗽𝗮𝗰𝗲 ➡️ Used to remove name collision within a cluster. It supports multiple virtual clusters on the same physical cluster.
𝗡𝗼𝗱𝗲 ➡️ Kubernetes worker machine.
𝗖𝗹𝘂𝘀𝘁𝗲𝗿 ➡️ Consisting of a group of nodes running containerized applications on Kubernetes.
𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝗦𝗲𝘁 ➡️ Several replicas of running pods. It helps in achieving high availability and scalability.
𝗟𝗮𝗯𝗲𝗹 ➡️ Giving a name to Kubernetes objects so that they can be identified across the system.
𝗞𝘂𝗯𝗲𝗹𝗲𝘁 ➡️ Agent that runs on each node and checks if the containers are running in the pods.
𝗞𝘂𝗯𝗲𝗰𝘁𝗹 ➡️ Command-line utility to interact with the Kubernetes API server.
𝗞𝘂𝗯𝗲-𝗽𝗿𝗼𝘅𝘆 ➡️ Network proxy which contains all the network rules on each node in the cluster.


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

🔥 I have created this handy diagram that breaks down the key concepts of Kafka in a simple and easy-to-understand way.

🔴 𝗣𝗿𝗼𝗱𝘂𝗰𝗲𝗿:

A Kafka producer is an entity that publishes data to topics within the Kafka cluster. In essence, producers are the sources of data streams, which might originate from various applications, systems, or sensors. They push records into Kafka topics, and each record consists of a key, a value, and a timestamp.

🔴 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿:

A Kafka consumer pulls data from Kafka topics to which it subscribes. Consumers process the data and often are part of a consumer group. In a group, multiple consumers can read from a topic in parallel, with each consumer responsible for reading from certain partitions, ensuring efficient data processing.

🔴 𝗧𝗼𝗽𝗶𝗰:

A topic is a category or feed name to which records are published. Topics in Kafka are multi-subscriber; they can be consumed by multiple consumers and consumer groups. Topics are divided into partitions to allow for data scalability and parallel processing.

🔴 𝗣𝗮𝗿𝘁𝗶𝘁𝗶𝗼𝗻:

A topic can be divided into partitions, which are essentially subsets of a topic's data. Each partition is an ordered, immutable sequence of records that is continually appended to. Partitions allow topics to be parallelized by splitting the data across multiple brokers.

🔴 𝗕𝗿𝗼𝗸𝗲𝗿:

A broker is a single Kafka server that forms part of the Kafka cluster. Brokers are responsible for maintaining the published data. Each broker may have zero or more partitions per topic and can handle data for multiple topics.

🔴 𝗖𝗹𝘂𝘀𝘁𝗲𝗿:

A Kafka cluster comprises one or more brokers. The cluster is the physical grouping of one or more brokers that work together to provide scalability, fault tolerance, and load balancing. The Kafka cluster manages the persistence and replication of message data.

🔴 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

A replica is a copy of a partition. Kafka replicates partitions across multiple brokers to ensure data is not lost if a broker fails. Replicas are classified as either leader replicas or follower replicas.

🔴 𝗟𝗲𝗮𝗱𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

For each partition, one broker is designated as the leader. The leader replica handles all read and write requests for the partition. Other replicas simply copy the data from the leader.

🔴 𝗙𝗼𝗹𝗹𝗼𝘄𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

Follower replicas are copies of the leader replica for a partition. They replicate the leader's log and do not serve client requests. Instead, their purpose is to provide redundancy and to take over as the leader if the current leader fails.

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

😀😀 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!!!