Svg Vector Icons : http://www.onlinewebfonts.com/icon More Guides

What is a CI/CD Pipeline?

A continuous integration/continuous delivery (CI/CD) pipeline is a software development or engineering process that combines automated code building and testing with deployment. A CI/CD pipeline is used to deploy new and updated software safely. 

A CI/CD pipeline automates the following two processes for an end-to-end software delivery process: 

Continuous integration for automated code building and testing. CI allows developers to submit multiple changes to a shared repository or main code branch while maintaining version control. Many software development teams are geographically dispersed or isolated, but CI enables fast development while avoiding merge conflicts, bugs, and duplication. CI always keeps the main branch up to date but can also facilitate short-term isolated side or feature branches for smaller changes that can eventually be merged into the main branch.

Continuous delivery (or continuous deployment) for code releases. CD enables short-cycle, incremental development and allows dev teams to build and release software at any time. It also helps devops teams to reduce costs and speed up deployment for new releases. CD requires a highly repeatable structure and is often considered an extension of CI.

A CI/CD pipeline combines code building, testing, and deployment into one continuous process ensuring that all changes to the main branch code are releasable to production. An automated CI/CD pipeline prevents manual errors, provides standardized feedback loops to developers, and enables quick software iterations.

data engineering - data engineering training

Benefits of a CI/CD Pipeline

CI/CD is essentially a set of best practices for software development, enabling frequent, typically small code updates and releases. It enables developers to meet business requirements while maintaining code consistency and security. 

A CI/CD pipeline automates the CI/CD process, including regression and performance testing. Builds, testing, and deployment cycles occur regularly and frequently, as often as daily or even hourly. 

CI/CD pipelines enable:

- Code quality, consistency, and security

- Frequent, iterative updates 

- Scheduling flexibility for builds and deployments

- Developer consensus and collaboration

- Versioning control with logs of changes

- Customized, automated testing and timely feedback

- Visibility into build or delivery failures via dashboards and reports

- Environmental stability with automated rollback features

- Reliable, standardized builds

CI/CD Pipeline Workflow

A CI/CD pipeline workflow involves several stages, namely:

Source: A code change or automated or user-initiated workflow triggers the CI/CD pipeline to run.

Build: New code is merged with the source code.

Test: Automated tests are run to validate the code and reveal bugs.

Deploy: Code is released to staging or production environments. 

CI/CD Pipeline Solutions

A CI/CD pipeline tool automates many steps of the CI/CD pipeline workflow, freeing developers to focus on new functionality and features. A few of the most popular CI/CD pipeline solutions include:

Jenkins, an open-source automation server

CircleCI, which enables automated code building, testing, and deployment

TeamCity, a general-purpose CI/CD solution

GitLab, a web-based tool and Git-repository manager

Bamboo, a CI/CD tool with Jira and Bitbucket 

Microsoft Azure DevOps, tools for planning, collaborating, and building and deployment

Snowflake and CI/CD Pipelines

Snowflake’s Data Cloud powers applications with virtually no limitations on performance, concurrency, or scale. Trusted by fast-growing software companies, Snowflake handles all the infrastructure complexity so that application developers can focus on innovation.

Snowflake provides the perfect environment for dataops and devops, including CI/CD to accelerate software development, enhance collaboration and foster agility. Snowflake customers can industrialize data pipelines in and around Snowflake. 

Snowpark is a developer framework for Snowflake that brings data processing and pipelines written in Python, Java, and Scala to Snowflake's elastic processing engine. Snowpark allows data engineers, data scientists, and data developers to execute pipelines feeding ML models and applications faster and more securely in a single platform using their language of choice. 

Our ebook “DevOps for Data Apps on Snowflake” and DevOps guides provide details on how. See Snowflake’s capabilities for yourself. To give it a test drive, sign up for a free trial.