CI/CD Pipeline: 7 Advantages To A Continuous Integration Approach to Data Pipelines
When it comes to modern software development, it’s not surprising that companies have a need for speed. But if you develop software too quickly, it can mean sacrificing quality, security and compliance. DevOps and continuous integration & continuous delivery (CI/CD) are proven capabilities that help companies maintain a healthy balance between agility and quality. More and more companies are bringing DevOps to their data pipeline. Here are seven benefits for taking a DevOps approach to your data pipeline:
- Reusability with data artifact lifecycle management
It’s powerful when you can treat data pipelines as product. For data lifecycle management, DevOps/DataOps methods serve as a guardrail that makes it easier to test and release data to the production environment. A continuous feedback mechanism helps data engineers and the DevOps team to, for example, optimize data delivery pipelines, improve code quality and reuse objects later for no-code/no-build data integration activities.
- Deliver value faster and at scale
CI/CD ensures faster release cycles. Your team will be more productive when they are able to, for example, automate testing at each level of data pipeline development with CI/CD. With automation, scaling becomes easier even when the data processing workload increases overnight. CI/CD also helps ensure faster and accurate integration for enhanced business value.
- Meet enterprise-level SLAs
CI/CD tools help you deliver on your service level agreements (SLAs). DevOps methods allow any data engineer to modify the data pipeline. It also ensures that only quality jobs pass through the drill.
- Collaborate seamlessly
DevOps methods and CI/CD pipelines speed up releases by enabling teams to work in parallel. With check-in and check-out options for code, multiple team members can work independently on the same objects, with fewer conflicts. With real-time feedback, data engineers can iterate faster and use automation to optimize operational overhead more easily.
- Control versioning
Tracking software versions encourages transparency and ownership. This reduces avoidable concerns about who else is working on specific versions and other dependencies. And role-based privileges and permissions ensure data pipeline reliability and security.
- Enable experimentation and monitoring
DevOps encourages agile experimentation. It lets you roll back to the previous data management version at any time. This is critical when the new version is not working. Developers can also try out new technologies and tasks. With an automated alert and response system, it’s easier to troubleshoot and monitor CI/CD pipelines.
- Get ready for DataOps, MLOps and AIOps
Depending on your organization’s data maturity level, you can apply the knowledge of DevOps to customize data products and operationalize machine learning (ML) models and artificial intelligence (AI) projects in the future.
An Example of a Continuous Integration Approach to Data Pipelines
Guy Carpenter, a leading global risk and reinsurance specialist, used a DevOps approach in a hybrid cloud landscape. While moving through multiple release stages, the company can streamline and automate their data processes. In the development stage, they write a task and conduct unit testing. Once committed, the code moves into the system integration testing environment. Next, it passes through the QA testing phase, pre-production performance or user acceptance tests, and finally, production. Thanks to automation, the whole process takes care of itself. This brings agility, productivity and efficiency together to enhance business results.
How Informatica Can Help
Informatica’s cloud-native data integration solutions enable you to break down silos across development, operations and security to deliver a consistent experience across the development lifecycle.