📌 Cloud Load Balancer Cheat Sheet

➡️ Efficient load balancing is vital for optimizing the performance and availability of your applications in the cloud.

However, managing load balancers can be overwhelming, given the various types and configuration options available.

In today's multi-cloud landscape, mastering load balancing is essential to ensure seamless user experiences and maximize resource utilization, especially when orchestrating applications across multiple cloud providers. Having the right knowledge is key to overcoming these challenges and achieving consistent, reliable application delivery.

😎 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.

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

🔔 DevOps, SRE, and Platform Engineering - making sense of the terminology! 🤔

Many enthusiasts whom I interviewed, didn't understand
the difference between DevOps, SRE, and Platform Engineering.

While these disciplines share similarities, there are nuances in their focus:

💻 DevOps emphasizes collaboration between dev and ops teams to optimize and accelerate software delivery.

📈 SRE focuses more on system reliability, availability, monitoring, and capacity planning.

🚀 Platform Engineering deals with building and managing the underlying infrastructure and platforms.

🔄 All three leverage automation, infra-as-code, and CI/CD.

📊 DevOps and SRE teams may own services end-to-end. Platform teams focus on shared platforms.

🎯 DevOps improves agility. SRE improves reliability. Platform Engineering improves developer productivity.

There's overlap in principles but differences in scope. Many organizations blend these roles for the best results.


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

🔣Platform engineering Vs DevOps..

Is this difference or is this same.

Let's look at the focus area of each and you determine if it's different or same.


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

☁️ 𝗔𝗪𝗦 𝗵𝗮𝘀 𝗼𝘃𝗲𝗿 𝟮𝟬𝟬 𝗳𝘂𝗹𝗹𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝗱 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀.✨
𝗠𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗔𝗪𝗦 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝘆𝗼𝘂 𝘀𝗵𝗼𝘂𝗹𝗱 𝗹𝗲𝗮𝗿𝗻 𝘁𝗼 𝗯𝗲 𝗮 𝗗𝗲𝘃𝗢𝗽𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿.

✔️Amazon EC2
✔️AWS IAM
✔️AWS CloudFormation
✔️AWS CloudWatch
✔️AWS CodePipeline
✔️AWS CodeBuild
✔️AWS CodeDeploy
✔️Amazon ECS
✔️AWS Lambda
✔️AWS Elastic Beanstalk
✔️Amazon DynamoDB


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

F13 Technologies is hiring for an AWS Cloud Intern.

Share your resume at tarleen.kaur@f13.tech if interested.


😎 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

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

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

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

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

🔣 The DevOps Engineer role is not for freshers.

🔣 Here are some of the tasks that you will be required to do as a DevOps engineer:

1⃣. 𝗬𝗼𝘂 𝘄𝗼𝗻’𝘁 𝗯𝗲 𝗮𝘀𝗸𝗲𝗱 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗲 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 on the day of joining. Most of the companies already have everything in place.

🔢. 𝗬𝗼𝘂 𝘄𝗶𝗹𝗹 𝗮𝘀𝗸𝗲𝗱 𝘁𝗼 𝗽𝗲𝗿𝗳𝗼𝗿𝗺 𝗣𝗢𝗖𝘀(𝗣𝗿𝗼𝗼𝗳 𝗼𝗳 𝗖𝗼𝗻𝗰𝗲𝗽𝘁) on a variety of tools, starting from CI/CD to secret management. For instance the difference in build time between Jenkins and GitLab.

🔢. 𝗕𝘂𝗶𝗹𝗱 𝗰𝘂𝘀𝘁𝗼𝗺 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 for better business growth and process efficiency.

🔢. Work closely with the Cloud and Development team to 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝗹𝗮𝘁𝗲𝗻𝗰𝘆, 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗦𝗟𝗔.

🔢. Spend crazy time in finding “𝗪𝗵𝗮𝘁 𝗲𝗹𝘀𝗲 𝗰𝗮𝗻 𝘄𝗲 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲”.

🔢. 𝗪𝗿𝗶𝘁𝗲 𝗰𝘂𝘀𝘁𝗼𝗺 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 like controllers for Kubernetes.

🔢. 𝗛𝗲𝗹𝗽 𝘀𝗵𝗶𝗳𝘁 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗹𝗲𝗳𝘁 by Writing security policies and rules for tools like OPA and Falco.

🔢. Play the most active role 𝗱𝘂𝗿𝗶𝗻𝗴 𝗿𝗼𝗹𝗹𝗼𝘂𝘁𝘀, 𝗯𝗹𝗶𝗻𝗱𝘀 𝗮𝗻𝗱 𝘂𝗽𝗱𝗮𝘁𝗶𝗼𝗻 of components.

🔢. Work with APIs, optimize and troubleshoot them.

🔟. 𝗖𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝗮 𝘁𝗼𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗼𝗿𝗴'𝘀 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻.


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

➡️ [ 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 ] ⬅️

1️⃣. 𝐓𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
- In this model, applications are installed and run directly on a physical server.
- The operating system, necessary libraries and the application itself all reside on a single, dedicated machine.
- This leads to tight coupling between the application and the underlying hardware.

2️⃣. 𝐕𝐢𝐫𝐭𝐮𝐚𝐥𝐢𝐳𝐞𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
- Virtualization introduces a hypervisor layer on top of the physical hardware. - This layer allows you to create multiple Virtual Machines (VMs) on a single server.
- Each VM emulates a complete physical computer system, with its own virtual CPU, memory and storage.
- Applications run within these VMs, isolated from each other.

3️⃣. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐢𝐳𝐞𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
- Containers take virtualization a step further.
- They package an application and its dependencies (libraries, binaries, configuration files) into a portable, lightweight image.
- Unlike VMs, containers share the host machine's operating system kernel, making them far more efficient.

4️⃣. 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬-𝐛𝐚𝐬𝐞𝐝 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭
- Kubernetes is an open-source platform that automates the deployment, scaling and management of containerized applications.
- It groups containers into logical units (pods) and provides mechanisms for :

➡️ Orchestration
Automates container placement, scaling, and networking.

➡️ Self-healing
Monitors and restarts containers, or reschedules pods on different nodes in case of failures.

➡️ Rolling Updates
Enables zero-downtime application updates.


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

🔣 Developing applications in Kubernetes is complex and hard.

Managing resources , updating configurations and integrating with CI/CD takes up a lot of time and effort.

✅ This is where the helm comes in. Helm simplifies the process of developing applications , automating the distribution of the application. Consider it similar to a package manager , the apt or yum of kubernetes.

🟡 Some of its use cases
- Versioning of application releases and rollbacks if necessary.
- Customize configurations and charts for different environments.
- Centralized package management.
- Simplify deploying and using applications in a standardized manner.


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

If you're a DevOps engineer, you'll agree with this. Read below 👇

"automating manual tasks brings a unique pleasure"

Why?

✅ Efficiency
- Automating tasks saves time and effort, allowing DevOps engineers to focus on more critical and challenging aspects of their work.

✅ Consistency
- Automation ensures that tasks are performed consistently, reducing the chances of human error and enhancing reliability.

✅ Innovation
- Automating manual processes often requires creative problem-solving and innovation, which can be intellectually stimulating and rewarding.

✅ Scalability
- Automation enables DevOps teams to scale their operations efficiently, handling larger workloads without significant increases in manpower.

✅ Empowerment
- Automating mundane tasks empowers DevOps engineers to take on more meaningful and impactful work, contributing to their professional growth and job satisfaction.


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

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

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7. Understand KubeConfig File
8. Understand Kubernetes Objects And Resources
9. Learn About Pod & Associated Resources
10. Learn About Pod Dependent Objects
11. Deploy End to End Application on Kubernetes
12. Learn About Securing Kubernetes Cluster
13. Learn About Kubernetes Operator Pattern
14. Learn Important Kubernetes Configurations
15. Learn Kubernetes Best Practices
16. Real-World Kubernetes Case Studies
17. Kubernetes Failures/Learnings
18. Kubernetes Deployment Tools (GitOps Based)


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➡️Auto Scaling Policy: A Simple Complex task⬅️

Automatically scaling capacity is critical for meeting fluctuating demand. AWS has a robust auto-scaling capability to add or remove resources dynamically.

There are three main components for getting started:
📈 Launch Configurations define the server configuration for new instances.

👥 Auto Scaling Groups contain a fleet of identical instances defined by a launch config. Groups scale in or out based on criteria.

⏫Scaling Policies determine when and how to scale the group - manually or based on metrics.

There are a few key scaling policy types:
📝 Target Tracking - Maintain a target metric value like X% CPU utilization.

📉 Simple/Step Scaling - Add or remove instances based on thresholds like server CPU exceeding Y%.

✅Scheduled Scaling - Scale on a schedule for predictable spikes, e.g. increase servers on seasonal sales days.


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