DevOps Chapter 1: Introduction

DevOps combines development, quality assurance, and operations into a continuous process, extending Agile and continuous delivery.

A collection of key values, most notably Culture, Automation, Measurement and Sharing (CAMS), guiding the successful implementation of DevOps.

Improved technical processes, enhanced business outcomes, and a better company culture, all by focusing on team collaboration.

The collaborative mindset between development and operations teams vital for successful DevOps.

Automating development, testing, configuration, and deployment processes for efficiency and consistency in DevOps.

A framework used in DevOps comprising Culture, Automation, Measurement, and Sharing to showcase key aspects for success.

Methodologies that DevOps expands upon, aiming to accelerate software delivery and increase flexibility.

Important for DevOps, as it is pivotal for sharing responsibility and working collaboratively towards a common goal.

A set of practices that aims to automate and improve the software development lifecycle by fostering collaboration between development and operations teams.

Measurable metrics used to track the progress and performance of a system or process, crucial for decision-making.

Agile planning breaks down projects into short iterations to improve flexibility and allow for quick adjustments based on feedback.

Software development practice of dividing work into smaller portions for quicker delivery and better testing.

Automated testing of code changes to identify bugs and vulnerabilities promptly, crucial for quality assurance.

The sequence of steps involved in the software development lifecycle from planning to deployment and monitoring, emphasizing collaboration.

Working together between different teams within the DevOps workflow to improve efficiency and effectiveness.

Maintaining consistency in an application's environment and infrastructure across its lifespan, especially crucial for large-scale applications and distributed systems.

Tasks that are repeatedly performed and can be automated to free up specialists for more important, non-automation tasks.

Encapsulating an application and its dependencies into a self-contained unit (container) that runs independently on any system, promoting 'build once, run anywhere'.

The most popular containerization tool, allowing developers to package applications with all necessary components and deploy them efficiently.

Managing IT infrastructure through code, allowing automation, consistency, and repeatability in deployments, replacing manual configuration.

Popular configuration management tools that automate the provisioning, configuration, and management of servers and applications.

Combining tools like Docker (containerization) with Ansible, Puppet, or Chef (configuration management) to automate the deployment and configuration of containers across different environments.

Configuration management tools like Ansible, Puppet, and Chef automate the deployment of Docker images and manage the configuration settings of containers, ensuring consistency across various deployments.

Such integration allows for automated deployments, consistent configurations, and efficient scaling of applications across different environments.

A DevOps engineer bridges the gap between development and operations, implementing continuous integration and delivery workflows. They are experts in automation tools and have knowledge of relevant programming languages.

A DevOps engineer's key responsibilities include automating processes, configuring infrastructure, managing code deployments, monitoring system performance, and ensuring consistent and efficient software delivery.

A DevOps engineer needs a blend of skills, including programming, scripting, infrastructure management, automation, and problem-solving. They are adept at both technical and collaborative aspects of software development.

Traditional SDLC follows a sequential, waterfall approach, where each phase completes before the next begins. DevOps emphasizes a continuous flow of work through automation, with shorter feedback loops and faster iterations.

Traditional SDLC often has separate teams for development, testing, and operations, which can lead to communication silos. DevOps promotes cross-functional teams, fostering collaboration and faster feedback cycles.

Traditional SDLC can have longer delivery cycles due to its sequential nature. DevOps emphasizes speed and efficiency, prioritizing frequent, small releases with automated processes and continuous feedback.

Traditional SDLC often involves testing at a single stage towards the end of the development cycle. DevOps emphasizes continuous testing throughout the entire lifecycle, integrating testing with development and deployment.

Traditional SDLC may have limited automation, relying on manual processes and scripts. DevOps heavily emphasizes automation for everything from code building, testing, deployment, and infrastructure management.

IaC offers benefits like consistency, version control, collaboration, and automation, leading to reduced errors and faster deployments.

An open-source IaC tool that uses a declarative language (HCL) to define infrastructure across multiple cloud platforms.

An AWS-specific IaC service that uses a template language to define and manage AWS resources.

A declarative language used by Terraform to define infrastructure resources and configurations.

Modules that allow Terraform to interact with different cloud platforms and services, expanding its capabilities.

A file that stores the current state of managed infrastructure, enabling tracking and managing changes.

When infrastructure configurations change without a record or intention, leading to discrepancies and problems.

Managing and defining infrastructure through code to automate provisioning, configuration, and updates, ensuring consistency across environments.

IaC offers automation, consistency, repeatability, and version control for infrastructure deployments, reducing manual errors.

Terraform uses providers that interact with cloud platform APIs to create, modify, and delete resources, enabling automated deployments.

Integrating IaC into CI/CD pipelines automatically provisions and configures infrastructure during deployments, ensuring consistent configurations and updates.

Automating infrastructure provisioning and configuration ensures consistency, reduces errors, and improves efficiency in deployments.

Terraform providers are responsible for interfacing with specific cloud platform APIs, enabling interactions with resources on that platform.