DevOps Terms

Introduction

In software development and IT operations, understanding terms like CI/CD and pipeline is crucial for effective collaboration and automation.

Check out our DevOps Terms for definitions covering continuous integration, deployment, and more. Enhance your knowledge of DevOps practices and improve your skills in modern software development effortlessly.

DevOps Terms

A

Agile: Agile refers to a dynamic method of creating software that highlights collaboration, flexibility, and adaptability, with a strong focus on customer satisfaction. DevOps integrates Agile methodologies, like Scrum and Kanban, which release software in brief cycles, facilitating consistent feedback, quick adjustments, and early value delivery.

B

Behavior-Driven Development (BDD): An Agile software development approach that promotes collaboration and teamwork among software developers, Quality Assurance professionals, and business stakeholders involved in a software project.

Build Agent: A tool utilized in continuous integration, which can be installed either locally or remotely, depending on the server. The agent is responsible for transmitting and receiving messages associated with the creation of software builds.

C

CI/CD (Continuous Integration/Continuous Delivery): CI/CD, or Continuous Integration/Continuous Delivery, is a collection of practices and principles that promote regular automated software releases. Continuous Integration entails automatically constructing and testing code adjustments to ensure seamless integration and detect issues early. Continuous Delivery, on the other hand, automates the release and deployment processes to consistently and frequently deliver software to production environments, enhancing reliability.

Configuration Management: Configuration Management refers to the administration and maintenance of consistent and dependable configurations for software and infrastructure. This process involves monitoring and regulating modifications, maintaining consistency across environments, and managing configuration items throughout their lifecycle. Tools like Puppet or Ansible, which are frequently utilized in DevOps, automate and manage configurations to streamline this process.

Containerization: An OS-level virtualization technique utilized for deploying and running distributed applications without the need to initiate a separate virtual machine for each instance.

Containers: A software package represents a standardized unit that encompasses all necessary components for its execution, including code and dependencies. Containers facilitate the swift and dependable operation of an application when transferred from one computing environment to another, ensuring consistent performance.

D

Dark Launch: A development approach that involves releasing a new code version, incorporating novel features, to a team or a subset of the organization's users, but either not activating it visibly or partially activating it. This strategy bears resemblance to a Canary Release.

Deployment: The integration of all processes required to render hardware or a software program accessible for use, encompassing installations, configuration, testing, and transitioning the program to its designated environment.

Deployment Pipeline: A fully automated multi-stage process that advances software from version control to its availability for an organization's users.

DevOps: A term derived from the combination of "development" and "operations", representing a collaborative design philosophy that brings together development and operations teams in software development and deployment. The objective of this approach is to enhance software production agility while fulfilling business objectives.

Deployment: Deployment refers to the process of introducing software or applications into production environments. DevOps's deployment strategies prioritize automating deployment procedures, minimizing manual intervention, and maintaining consistency across environments. Deployments may encompass allocating resources, configuring services, and implementing new code modifications.

DevSecOps: The process of bringing security into DevOps methodology and giving it a significant role.

E

Elasticity: Elasticity in the context of DevOps signifies the capacity to adaptively scale computing resources up or down based on demand. This ability is achieved by capitalizing on cloud infrastructure or containerization technologies to allocate and deallocate resources in real-time, ensuring optimal performance and cost efficiency in response to fluctuating workloads.

Event-Driven Architecture: A software architecture design in which the system is equipped to generate messages or events and is simultaneously structured to recognize, respond to, and consume other events.

G

Git: Git is a widely used distributed version control system in software development and DevOps practices, facilitating collaboration among multiple developers on projects, tracking modifications, and efficiently managing source code repositories. Git offers features such as branching, merging, and conflict resolution, promoting seamless collaboration and version control in distributed teams.

I

Infrastructure as Code (IaC): Infrastructure as Code (IaC) is a method that regards infrastructure provisioning and management as code entities. This approach entails defining infrastructure configurations in a declarative or programmable format, encompassing servers, networks, and storage. IaC tools, such as Terraform or CloudFormation, facilitate automation, consistency, and versioning of infrastructure deployments, making it easier to manage and replicate infrastructure environments.

Incident Management: Incident Management refers to the process of addressing and resolving incidents or service disruptions within an organization. In DevOps, incident management strategies prioritize minimizing downtime, swiftly restoring services, and learning from incidents to prevent future occurrences. This process typically involves identifying incidents, triaging, resolving, and conducting post-incident analysis.

Infrastructure Monitoring: Infrastructure Monitoring encompasses gathering and analyzing data from diverse infrastructure elements like servers, networks, and applications to guarantee their performance, availability, and reliability. DevOps teams employ monitoring tools and methodologies to enhance visibility into infrastructure health, identify issues, and preemptively tackle potential bottlenecks or failures.

Issue Tracking: A procedure that enables programmers and quality assurance experts to monitor the progression of both defects and new features, from their initial identification to final resolution.

J

Jenkins: Jenkins is a popular open-source automation server extensively utilized in DevOps for constructing, testing, and deploying software applications. It furnishes a sturdy foundation for continuous integration and delivery workflows, enabling teams to automate build processes, execute tests, and deploy software consistently. Jenkins boasts extensibility via a broad plugin ecosystem, rendering it highly flexible and suitable for various DevOps environments.

K

Kubernetes: Kubernetes is an open-source container orchestration platform that streamlines the deployment, scaling, and administration of containerized applications. It offers a structure for overseeing containers across numerous hosts, guaranteeing high availability, scalability, and robustness. Kubernetes abstracts the underlying infrastructure and presents a declarative method for application deployment, establishing it as a favored solution for handling containerized workloads in DevOps settings.

L

Lead Time: In the manufacturing context, this refers to the duration required to transition a work in progress (WIP) into a completed state. In the DevOps realm, the concept is analogous to the time taken to advance code modifications into the production stage.

M

Mean Time Between Failures (MTBF): An assessment of the average system downtime caused by failures, this metric gauges the reliability of a specific system or its components.

Mean Time to Recovery (MTTR): The average duration required for a system or component to recover from a failure and resume production status.

Microservices: Microservices is an architectural strategy in which applications are constructed as a set of small, autonomous services that collaborate to provide distinct functionalities. Each microservice concentrates on a singular business capability and can be created, deployed, and expanded autonomously. This modular method empowers teams to independently develop and manage services, enhancing flexibility, scalability, and resilience within intricate applications.

O

Orchestration: Orchestration in DevOps signifies the automated coordination and management of multiple tasks, services, and components to achieve a desired outcome. This process entails defining workflows, dependencies, and sequences of actions to ensure seamless execution and integration across various systems and processes. Orchestration tools empower teams to automate complex deployment, provisioning, and configuration tasks, minimizing manual effort and ensuring consistency.

Observability: Obtaining knowledge about a system's internal operations and behavior by examining its outputs, logs, metrics, and traces is referred to as observability. In the context of DevOps, observability is vital for monitoring the condition, performance, and behavior of applications and infrastructure. Observability tools and methods offer insights into the system's internal workings, enabling teams to identify issues, resolve problems, and enhance performance.

P

Pipeline: In the DevOps world, a pipeline represents a sequence of interconnected steps and actions designed to compile, test, and deploy software applications. Automation of the software delivery process is achieved through DevOps pipelines, which allows teams to continuously integrate and deliver software. The pipeline comprises stages such as code compilation, testing, artifact creation, deployment, and monitoring, ensuring a smooth and dependable software delivery lifecycle.

Production: The final phase in the software deployment pipeline, in which the intended end-users ultimately engage with the application.

Provisioning: In the realm of DevOps, provisioning involves the establishment and configuration of infrastructure, resources, and dependencies necessary for deploying applications. Automated provisioning utilizes infrastructure-as-code tools to specify and deploy resources, guaranteeing uniformity and replicability across various environments. Provisioning tasks may encompass activities like creating virtual machines, setting up networks, and installing essential software packages.

Q

Quality Assurance (QA): Quality Assurance guarantees that software products and services meet defined requirements and conform to established quality benchmarks. Within the DevOps framework, QA procedures concentrate on embedding quality assessments and testing tasks into the software delivery pipeline. This encompasses automated testing, ongoing monitoring, and feedback mechanisms to identify and rectify quality concerns across the development and deployment phases.

R

Release Management: Release Management refers to the process of organizing, scheduling, and managing the deployment of software releases into production environments. DevOps teams utilize release management practices to ensure seamless and regulated software deployments, minimizing user disruption and enhancing system stability. This process includes release planning, change management, version control, and rollback strategies.

S

Service Level Agreement (SLA): A Service Level Agreement (SLA) represents a formal agreement between a service provider and a client that specifies the anticipated service and performance level. In the DevOps context, SLAs outline the quality, availability, and reliability targets for services and applications. SLAs serve as a foundation for evaluating and monitoring service performance, establishing responsibility, and ensuring that service delivery aligns with customer expectations.

Source Control: Also known as revision control or version control, this process involves storing, tracking, and managing changes to code, documents, websites, and other information pieces. Typically, this is accomplished by creating branches from the stable master version of the software, and subsequently merging the stable feature branches back into it.

Staging Environment: A near-identical replica of a production environment designed for software testing purposes, where the latest software iteration is tested before its live deployment using an environment that closely resembles the live production setting.

T

Test Automation: Test Automation entails mechanizing the execution of tests to verify software functionality, performance, and reliability. In DevOps, test automation is critical for attaining continuous testing and facilitating prompt feedback on code modifications. Automated testing frameworks and tools, such as Selenium or JUnit, enable teams to design and execute tests automatically, minimizing manual effort, expanding test coverage, and expediting the overall software delivery process.

U

Unit Testing: A testing strategy that entails segregating the smallest unit of testable code from the rest of the software and executing tests on it to verify if it operates as intended.

V

Version Control: Version Control, also known as Source Code Management, is responsible for monitoring and managing modifications to source code files. DevOps teams utilize version control systems, such as Git or Subversion, to store and monitor various versions of their codebase, promoting collaboration, preserving a record of changes, and simplifying code integration and rollback. Version control guarantees code integrity, fosters teamwork, and enhances efficient code management throughout software development.

Virtualization: Virtualization refers to the creation of virtual instances or environments of computer resources, including servers, operating systems, or networks. This technology enables multiple virtual machines or containers to operate on a single physical machine, enhancing resource utilization, isolation, and flexibility. DevOps teams utilize virtualization technologies, such as hypervisors or containerization platforms (e.g., Docker), to establish replicable and scalable development and deployment environments.

W

Workflow: In DevOps, a Workflow represents the sequence of tasks, activities, and steps executed to accomplish a specific goal or deliver a software product. Workflows establish the order and dependencies of actions, ensuring consistent and replicable processes throughout the software development and delivery lifecycle. DevOps teams optimize workflows by automating them, promoting efficient collaboration, accelerating time-to-market, and enhancing overall productivity.