DevOps: Development and Operation of SDLC

This curriculum is structured to give a comprehensive understanding of the DevOps process and roadmap. It is aimed at learners ranging from beginners to intermediate and advanced levels.

Overview of DevOps

DevOps is a set of practices and cultural philosophies that aim to shorten the systems development life cycle and provide continuous delivery with high software quality. DevOps is primarily a response to the challenges of traditional software development, focusing on collaboration, automation, integration, and constant feedback between software development and IT operations.

Rancher is a powerful open-source platform for managing Kubernetes clusters, and its enterprise version comes with additional features for scalability, security, and integrations to support large-scale organizations. Rancher simplifies the deployment, scaling, and operations of Kubernetes clusters, providing a unified view across multiple clusters with strong security mechanisms.

GitHub Actions is a powerful CI/CD (Continuous Integration and Continuous Delivery) tool integrated directly into GitHub. It automates the process of building, testing, and deploying applications. This platform allows you to set up workflows that respond to various events on GitHub, such as pull requests, commits, or releases.

Integrating Bitbucket Server (also known as Bitbucket Data Center) with Jenkins allows for a more streamlined Continuous Integration/Continuous Deployment (CI/CD) process. With this integration, Jenkins can automatically trigger builds based on commits to your Bitbucket repositories, and in turn, Bitbucket can display detailed build information.

  - Install Java 11

  - Jenkins Setup: 

  - Install Jenkins

  - Access Jenkins in web browser

  - Create another EC2 instance for installing Tomcat and make sure you open port 8080 as well

  - Tomcat Installation: Install Tomcat 9 on Ubuntu server | Setup Tomcat 9 on Ubuntu in AWS EC2

To automate the deployment of a Java web application (MyWebApp) using Jenkins, Maven, Tomcat, and JaCoCo for code coverage, follow these detailed implementation steps. This includes configuring Jenkins, installing necessary plugins, and setting up the build and deployment pipeline. Below are the prerequisites and step-by-step instructions, including resources and GitHub links where applicable

SonarQube, also known as Sonar, is an open-source tool for continuous code quality that measures and analyzes the source code. It is built in Java, but capable of analyzing code in 20 diverse languages. SonarQube that not only checks the code and highlights the issues, but also tracks and monitors the code continuously and ensures flawless code integration as well as deployment. It can display the result of the analysis in a visually appealing way using nice charts, ‘green & red lights’, and issues list. it tries to detect bugs, code smells and security vulnerabilities. Many plugins are available to use it as part of continuous integration pipelines, including for Maven, Jenkins and GitHub.

How to enable open source plug-in for SonarQube.

Create a new Redhat EC2 instance with small type. Choose Redhat Enterprise 8.

How to install Nexus Artifact Uploader plug-in to integrate Nexus with Jenkins.

JFrog Artifactory is the single solution for housing and managing all the artifacts, binaries, packages, files, containers, and components for use throughout your software supply chain.

  - What is the Scripted Pipeline in Jenkins?
  - How to Create Your Jenkins Scripted Pipeline
  - Creating Your Jenkins Pipeline Script
  - The Jenkinsfile
  - Jenkins Scripted Pipeline Security

Jenkins master comes with the basic installation of Jenkins, and in this configuration, the master handles all the tasks for your build system. If you are working on multiple projects you may run multiple jobs on each and every project. Some projects need to run on some particular nodes, and in this process, we need to configure slaves.

The Jenkins master acts to schedule the jobs and assign slaves and send builds to slaves to execute the jobs.

It will also monitor the slave state (offline or online) and getting back the build result responses from slaves and the display build results on the console output. The workload of building jobs is delegated to multiple slaves.

Several companies already have Jenkins server setup, let us create Jenkins project, clone repository, build the CICD and deploy accordingly using Webhook trigger to slack channel

Install AWS CLI - AWS CLI Installation Steps on Windows

Executing the below command after login to EC2 where you installed Terraform.

Bootstrapping in AWS allows you to automate the initial setup of an EC2 instance by adding custom commands and scripts to the EC2 instance’s User Data section. These commands are executed when the instance starts. This is extremely useful for automating configuration tasks like installing software, setting environment variables, or configuring network settings.

Azure DevOps supports a collaborative culture and set of processes that bring together developers, project managers, and contributors to develop software.

Ansible is a radically simple IT automation system. It handles configuration management, application deployment, cloud provisioning, ad-hoc task execution, network automation, and multi-node orchestration. Ansible makes complex changes like zero-downtime rolling updates with load balancers easy. More information on the Ansible website.

Puppet is a tool that helps you manage and automate the configuration of servers.

LAMP stands for Linux, Apache, MySQL, and PHP. Together, they provide a proven set of software for delivering high-performance web applications. Each component contributes essential capabilities to the stack:

The MERN stack consists of MongoDB, Express.js, React.js, and Node.js. These technologies are used to build full-stack web applications, where MongoDB handles the database, Express.js and Node.js manage the backend logic, and React.js takes care of the front-end user interface.

Here’s an in-depth step-by-step guide to deploying a MERN stack application on a virtual machine (VM) such as an Azure VM and installing the stack on Ubuntu 20.04.

Below is a detailed explanation with resource links, GitHub repositories, and implementation steps for Docker Engine installation on Ubuntu.

Amazon Elastic Container Registry (Amazon ECR) is a fully managed Docker container registry service provided by AWS. It enables developers to store, manage, and deploy container images. It is tightly integrated with other AWS services like Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS), making it a key part of the containerized application deployment workflow.

Jenkins is an automation server often used to build and deploy applications. We’ll be cloning our code repository, build image, test image and publish image using Jenkins Pipeline.

To configure Nexus 3 as a Docker private registry, you need to go through a series of steps to set up and configure Nexus 3 to store Docker images securely. Below, I will outline the entire process in detail, providing resources, links, and the necessary commands.

Kubernetes is a powerful container orchestration tool that automates the deployment, scaling, and management of containerized applications. It allows you to manage large-scale distributed systems and ensures high availability and fault tolerance. This guide explains how to set up a Kubernetes cluster using Kubeadm on Ubuntu 18.04.

Deploying Prometheus, Grafana, and Helm in Kubernetes is a common practice for monitoring and visualizing application metrics. Below is a comprehensive guide to deploying these tools in a Kubernetes cluster, along with implementation steps, resources, and GitHub links for reference.

Grafana is a powerful platform for querying, visualizing, alerting, and exploring your metrics, regardless of where they are stored. It allows you to collect, monitor, and analyze various types of telemetry data such as logs, metrics, and traces. Grafana is used widely in environments such as Kubernetes clusters and cloud services like Azure and AWS, making it highly versatile. Below is an elaborate guide on setting up Grafana for monitoring, particularly in the context of Azure Kubernetes Service (AKS), as well as a breakdown of key components, tools, and resources.

Creating a comprehensive curriculum that focuses on Big Data, AI/ML, Terraform Infrastructure, and Monitoring for a Site Reliability Engineer (SRE) is crucial for acquiring the necessary skills for working with modern infrastructure and ensuring system reliability at scale. Below is a structured curriculum with resource links, GitHub repositories (where applicable), and implementation steps for each area of focus.

Big Data is a term used to describe vast volumes of structured, semi-structured, and unstructured data that is too large or complex for traditional data-processing software. Learning about Big Data architectures, tools, and techniques, such as Hadoop and Spark, is crucial for handling and analyzing massive datasets. Below is an overview of the key topics, resources, and practical implementation steps to help you get started in Big Data technologies.

Objective:
Learn the basics of Machine Learning (ML) and understand how it can be applied to infrastructure management, particularly in areas such as anomaly detection, predictive maintenance, and automating operations.

Objective:

The goal is to learn Terraform for managing and provisioning cloud infrastructure in a repeatable, automated manner. Terraform is a popular tool used for automating the management of infrastructure resources across various cloud providers such as AWS, Azure, and Google Cloud. With Terraform, you define infrastructure as code (IaC), making it possible to provision, update, and version infrastructure in a consistent and scalable way.

Monitoring and observability are essential for maintaining and optimizing the health, performance, and reliability of applications and infrastructure in real-time. By combining metrics, logs, and traces, you gain the visibility needed to detect and resolve issues before they affect your end users.

Objective: Master tools and practices for monitoring system health, application performance, and infrastructure in real-time.

The Site Reliability Engineering (SRE) discipline aims to bring software engineering principles to infrastructure and operations, enabling teams to maintain large-scale systems in a reliable, scalable, and efficient manner. As SREs deal with production systems at scale, they focus on critical topics like incident management, disaster recovery, scalability, and cost optimization. This guide delves deeper into these advanced SRE concepts.

The integration of Kubernetes and containerization plays a crucial role in the modern SRE paradigm, where scalability, resilience, and automation are key principles for managing complex applications. This approach allows for more efficient resource utilization, improved application portability, and faster recovery in the event of failures.

Objective:

The objective of this guide is to help you understand how Kubernetes and containerization fit into the Site Reliability Engineering (SRE) paradigm for managing scalable and resilient applications. We’ll walk through the core concepts, key tools, and real-world implementation steps you can take to start using Kubernetes in your SRE workflows.

Objective:
The goal is to automate and optimize SRE (Site Reliability Engineering) tasks using scripting and automation tools. These practices will improve scalability, efficiency, and response times for monitoring, alerting, provisioning, and deployment.

The objective of this project is to integrate various learned topics into a real-world Site Reliability Engineering (SRE) solution. The steps outlined in this document cover the full cycle of cloud infrastructure management, containerized application deployment, monitoring, anomaly detection, disaster recovery, incident management, and cost optimization. The goal is to automate deployment, scaling, and monitoring while ensuring reliability and efficiency in the system.

Configuration management is a systems engineering process for establishing consistency of a product’s attributes throughout its life. A Configuration management system allows the enterprise to define settings in a consistent manner, then to build and maintain them according to the established baselines. A configuration management plan should include a number of tools that:

Terraform is an adequate tool meant for changing, versioning, or building a complete infrastructure by keeping in mind efficiency and safety. It has the potential to manage all the popular service providers and in-house solutions efficiently.

Azure DevOps is a suite of services that support software development, providing integrated features for planning, developing, testing, deploying, and monitoring applications. Whether you’re working on a small project or managing large-scale enterprise systems, Azure DevOps helps teams collaborate efficiently, facilitating rapid development cycles and streamlined workflows. It supports a variety of Agile methodologies and integrates with multiple open-source and third-party tools to ensure that development, testing, and deployment pipelines are smooth and efficient.

Azure Web Apps provides an extensive platform to build an app in Azure without having to deploy, configure and maintain your own Azure virtual machines. We can build any web app using different languages such as ASP.NET, PHP, Node.js, and Python. Web Apps can host a User Interactive application or even a backend service like a WCF Service or Web APIs. With Web Apps, we can leverage the power of Microsoft Azure and build a multi-functional, immensely scalable, highly secured, and seamlessly accessible internet or intranet-based applications. We can also build our applications on-premise and migrate them to Azure Web Apps.

Azure Kubernetes Service (AKS) simplifies deploying a managed Kubernetes cluster in Azure by offloading the operational overhead to Azure. As a hosted Kubernetes service, Azure handles critical tasks, like health monitoring and maintenance. When you create an AKS cluster, a control plane is automatically created and configured. This control plane is provided at no cost as a managed Azure resource abstracted from the user. You only pay for and manage the nodes attached to the AKS cluster.

This guide provides an in-depth procedure for integrating Azure DevOps pipelines with AWS resources, specifically using Auto Scaling Groups (ASG), Elastic Load Balancers (ELB), and other AWS services, to automate the deployment of applications across AWS and Azure environments.

Overview

As cloud workloads are becoming more hybrid, organizations are increasingly looking to avoid being locked into a single cloud provider. This integration tutorial aims to create an environment where Azure DevOps is used for CI/CD, and AWS resources like EC2, ASG, and ELB are managed and deployed automatically using Azure DevOps pipelines.

Prerequisites:

• Azure DevOps organization
• AWS Account
• A repository in GitHub or any Git-based service
• A running EC2 instance with IIS (for example, if deploying a Windows-based app)
• AWS CLI configured on your local machine
• Azure DevOps personal access token (PAT)

A Vulnerability Scanner is a software tool used to identify security flaws, misconfigurations, and weaknesses in applications and network infrastructures. These tools are essential in modern cybersecurity, especially when dealing with cloud networks, as they help detect vulnerabilities that could be exploited by malicious actors. Automated vulnerability scanning tools save time and ensure consistent security practices by regularly scanning systems, services, and networks for threats.

Key Features of Vulnerability Scanners:

1. Automated Security Tests: Automatically detects common vulnerabilities like SQL injection, cross-site scripting (XSS), insecure configurations, and outdated software.
2. Cloud Security Integration: Many modern scanners are integrated with popular cloud services like AWS, Azure, and Google Cloud, allowing seamless detection of vulnerabilities in cloud infrastructures.
3. Comprehensive Reporting: Provides detailed reports, including risk levels and remediation recommendations.
4. Continuous Monitoring: Some tools provide continuous monitoring, alerting you to vulnerabilities as they are discovered.

Saviynt is a cloud-based Identity Governance and Administration (IGA) platform designed to help businesses manage and secure access to sensitive resources. It provides services for identity lifecycle management, risk management, compliance, access governance, and privileged access management.

Saviynt enables businesses to have more granular control over who has access to what, and ensures that access is granted in compliance with corporate policies and regulations. It integrates with various enterprise systems, applications, and cloud environments to ensure that security and compliance requirements are met.

Strata Identity and Access Governance (IAG) solutions are designed to manage, secure, and govern digital identities and access across an organization's IT infrastructure. Strata IAG ensures that users have the appropriate level of access to systems, data, and applications, according to their roles, responsibilities, and policies. It helps organizations protect sensitive data while maintaining compliance with regulations such as GDPR, HIPAA, and other data privacy and protection laws.

Strata IAG solutions typically include:

• Identity Management (IDM): Management of user identities, authentication, and authorization.
• Access Control: Managing user access to resources based on roles, policies, and permissions.
• Governance: Auditing and monitoring user activities, ensuring compliance, and reporting on access permissions.

In this guide, we'll go through how to implement a Strata Identity and Access Governance solution using modern tools, frameworks, and best practices.

Qualys offers a comprehensive set of solutions for vulnerability management, compliance, and security monitoring. The Qualys Cloud Agent, as a lightweight data collector, serves a critical role in continuously monitoring and assessing hosts for various security needs. Below is a breakdown of various Qualys functionalities and how to implement them using the Qualys platform.

CrowdStrike, a leading cybersecurity platform, integrates with multiple security domains like cloud security, endpoint security, identity protection, and observability/log management. These integrations enable organizations to detect, prevent, and respond to threats across various attack vectors.

This guide will help you understand how to integrate CrowdStrike with Azure Sentinel, including creating analytics rules for CrowdStrike detections, getting access to the CrowdStrike API, and integrating it with cloud services like AWS and Azure.

Rapid7 Insight Cloud Security (formerly known as InsightAppSec or InsightVM) is a comprehensive cloud-based security solution that enables you to secure your cloud infrastructure, automate vulnerability management, and protect your digital assets. This curriculum will guide you from the basics of cloud security to mastering Rapid7’s Insight Cloud Security platform, covering its features, implementation, and best practices.

Splunk Cloud Security is an advanced cloud-based security platform designed to provide comprehensive visibility into security data across various environments. It enables organizations to monitor, investigate, and respond to security threats in real-time while taking advantage of the scalability and flexibility of the cloud.

Splunk Cloud Security integrates various security technologies, provides security operations center (SOC) capabilities, and helps organizations detect and mitigate threats quickly. It leverages Splunk's powerful data indexing and analytics engine and delivers insights through machine learning, data analytics, and correlation of security events.

In this guide, we will elaborate on Splunk Cloud Security, its capabilities, and the necessary steps to set up and use it effectively. We will also share resources such as GitHub repositories, Splunk documentation, and implementation steps.

Overview of Serverless Cloud

Serverless Cloud simplifies the development of highly scalable, secure, pay-per-use applications without the complexity of configuring cloud services. The platform handles all the infrastructure management, enabling developers to focus solely on building software. By abstracting cloud complexities like provisioning, scaling, and configuration, Serverless Cloud offers a fast, developer-friendly experience for deploying and managing applications.

Serverless Computing is a cloud computing model where cloud providers automatically manage the infrastructure required to run the code. This eliminates the need for developers to worry about provisioning and maintaining servers, allowing them to focus more on writing code and delivering business value. Despite the name "serverless," the code still runs on servers, but the management of these servers is abstracted away from the developers.

Serverless Computing on Google Cloud Platform (GCP) enables developers to focus on building applications without worrying about managing infrastructure. GCP provides a variety of serverless offerings that allow developers to write, deploy, and scale their code automatically without the need to manage servers or virtual machines. This helps businesses and developers save time and resources while optimizing cost and scaling.

Serverless Computing on Oracle Cloud Infrastructure (OCI) enables developers to build and deploy applications without the need to manage infrastructure. In a serverless environment, the cloud provider, Oracle in this case, automatically provisions, scales, and manages the infrastructure required to run the code, allowing developers to focus on writing business logic rather than worrying about servers and virtual machines.