Definition

A load balancer is a type of software or hardware that distributes incoming traffic across multiple servers or resources. This allows the load balancer to distribute the workload evenly, improving the performance and availability of the application.

The Load Balancer Lab

To run your own load balancer using open source software, you will need to:

• Install and configure the load balancer software on a server. Some popular open source options include HAProxy, Nginx, and Envoy.
• Configure the load balancer to distribute incoming traffic to the appropriate servers or resources. This typically involves setting up virtual servers and defining rules for routing traffic.
• Test the load balancer to ensure that it is working correctly and distributing traffic as expected.
• Monitor the load balancer and the underlying servers to ensure that the system is performing well and handling traffic effectively.
• Continually tune and optimize the load balancer configuration to improve performance and ensure that the application is always available and responsive.

Your web applications need a solution to store and retrieve its data. A relational database is often used in web applications. MySQL, MariaDB and PostgreSQL are some popular relational databases. There’s also SQLite. Many applications can use any of these relational databases by the virtue of the database layer abstraction. If you are writing your own web application, pick any one database and install it on your web server.

Install The Database

• Install the package.
• Enable and start the database systemd unit.
• Initialize the database server.
• Create databases.
• Create database users and set their passwords.

Connect The Web Application To The Database Server

I see a lot of people are trying to break into software engineering and DevOps. There are many inspiring stories out there. People from other industries and verticals have switched to IT and are having a successful career. You can do it too.

Let us look at the resources available to you.

Online Vs. Offline Training And Learning Resources

Online

All you need to break into DevOps is:

Once upon a time, Apache was the de-facto web server solution. Later, Nginx became popular. If you are getting started with DevOps and Linux system administration, I would recommend you to start with Nginx.

Start With A Static Website

What is a static website? A website made from HTML and CSS. And maybe some JavaScript, images, videos, fonts, etc. The key takeaway is that there is no server side application involved. Install the Nginx web server on your Linux VM. Configure it to serve a static website. You will need a static website as a per-requisite. Create a static website by assembling some HTML, CSS, JavaScript and images. Optionally, add some fonts and videos. Access the website from your web browser by typing the IP address of the web server in the address bar. Take it to the next level by pointing the DNS A record of your domain to the VM. For our purposes, a fake domain or a local unregistered domain is sufficient. Manipulating /etc/hosts is also fine. Enjoy viewing the website from the browser.

Are you storing secrets such as database credentials, API keys, etc. unencrypted in Git repositories? Stop.

To protect your secrets, do not store them anywhere unencrypted. Especially in Git repositories. Ideally, your organization must have some vault solution where secrets can be stored and securely shared with people on a need-to-know basis. In many small organizations, having such a central secrets management solution is still a luxury. The need to store such secret information in Git repositories is obvious. There are a few ways in which you can encrypt secrets. We discussed using Ansible Vault in one of the previous blog posts.

From an application developer and Kubernetes user’s point of view, you have to have a working knowledge of Kubernetes. The post outlines the most important Kubernetes objects required to deploy a typical web application. Let us assume that the web application uses the two-tier architecture. We also assume that the cluster is created and administered by an infrastructure or DevOps engineer and the necessary access is provided to the developer to deploy their web application onto the Kubernetes cluster. The Kubernetes operations are performed from the web application developer’s perspective.

Introduction

If you have chosen the DevOps engineering path for your career, Linux system administration skills are a must. Companies run their workloads on Linux on-premise as well as in the cloud. Many developers write software on their Linux laptops and workstations. In this post, I will lay out a plan to master Linux system administration skills. The journey begins with you becoming a Linux desktop user. Gradually, you start using your laptop as a Linux server. Become more productive and create your own labs using virtualization. You will be able to simulate a lot of Linux infrastructure scenarios on your laptop.

1. Learn Linux. Install Linux on your laptop. Get familiar with Linux commands. Learn virtualization. Unlock the path to learn more Linux.
2. Programming. Acquiring some programming skills using a general purpose programming language like Python goes a long way. Learning some web development is required in most DevOps engineering contexts. Although you don’t have to be an expert in web development, you should have a clear understanding of workloads consisting of web applications and microservices. Learning some HTML, CSS and JavaSript is required for web development. At this point, you have to learn at least one database system. I recommend PostgreSQL to get started with relational database system. Git is also an essential tool to manage source code.
3. Automation is the cornerstone of DevOps engineering. Learn the basics of automation with Ansible and shell scripting.
4. CI/CD. The purpose of DevOps is to create a culture and practice where developers can ship their applications to customers quickly, safely and continuously. The CI/CD pipelines often constitute the backbone of the DevOps practice. Jenkins is a popular tool to create CI/CD pipelines. Learn the basics of Jenkins and create pipelines to automatically test and deploy applications.
5. Observability and monitoring. Start with Linux commands such as top, free, du and progress towards Prometheus. The typical Prometheus stack includes Alert Manager and Grafana. Then explore the world of traces with tools such as Jaeger and OpenTelemetry.
6. Kubernetes. The quintessential container orchestration platform.
7. Cloud engineering. Start with one of the popular clouds such as AWS, Azure or GCP.
8. IAC. Take automation to the next level in the cloud. Use Terraform to orchestrate resources in the cloud.

Tech Chorus References

• Learning Linux For Devops
• Preparing For A DevOps Engineer Job With A Personal Project
• Three Day Plan To Learn Git

Learning Resources

DevOps

• Coursera Course: Google IT Automation with Python Professional Certificate
  • Crash Course On Python
  • Using Python to Interact with the Operating System
  • Introduction to Git and GitHub
  • Troubleshooting and Debugging Techniques
  • Configuration Management and the Cloud
  • Automating Real-World Tasks with Python

Python

• Free interactive Python tutorial: LearnPython.org

As soon as you are ready to deploy services and applications on the Internet, the first thing you need is a registered domain and a DNS server. Often people just use the DNS service provided by the domain registrar or the hosting or cloud provider. Using the managed service is not a requirement. You can host your own DNS server and manage the DNS for your domains. There are many open source software using which you can build your own DNS servers. Bind is the traditional and probably the most popular DNS solution out there. There are other options such as Knot, PowerDNS and Unbound.

Introduction

The Linux Kernel parameters are settings that can be configured to control the behavior of the Linux kernel. They are typically used to fine-tune system performance or to enable/disable certain features.

Some examples of kernel parameters include:

Memory-related parameters: These parameters control how the kernel manages system memory, including how much memory is allocated to user processes and how aggressively the kernel caches data.

Processor-related parameters: These parameters control how the kernel interacts with the system’s processors, including how it schedules processes and how it handles interrupts.