The abbreviation refers to continuous integration, which is an integral part of today’s DevOps architecture. It comprises a set of principles and practices that emphasizes continuously integrating feature enhancements, security patch updates, version upgrades, and so on. The act of constantly and consistently integrating features to an existing application, to ensure staying in sync with the prevailing market standards, is termed as ‘Continuous Integration’.
Continuous Delivery is the act of delivering updates to the end-users. It is the process of automating the upgrades through an established cloud network, by following a procedure for development, testing, and deployment, automatically done by cloud mechanisms.
Google’s cloud platform is one of the most widely adopted public clouds, offering a wide range of Google cloud services. Google cloud facilitates the management of data by implementing CI/CD methodologies that ensure high quality, maintainability, and more flexible data processes and workflow. A CI/CD integration in Google cloud typically consists of the following steps:
A few of the Google Cloud products can be enlisted as follows:
It is used for building, testing, and deploying a data processing workflow. Cloud Build can efficiently be used for builds in all programming languages, which includes Java, Node.js, and so on. Developers can deploy the builds across platforms/environments such as Kubernetes, Virtual Machines (VM’s), etc. Cloud Build is scalable enough to adjust to the varying loads, can be integrated with any in-house tool as part of the build process. It also comes with compliance mechanisms to deal with security threats.
This product is used to set a workflow that begins with data processing, followed by testing and verification of the end results. This product is based on Apache Airflow, which helps the developers to create, schedule, monitor, and manage complex workflows. It can be integrated well with other Google cloud products, such as BigQuery, Dataflow, Dataproc, and various AI platforms, along with support for multi-cloud as well as on-premise infrastructure.
A platform that offers data processing in a faster and cost-effective manner. It has features like auto-scaling of manpower to enable maximum resource utilization, simpler and faster data pipeline, resource auto-scaling, along with cost-optimized batch processing, ensuring limitless capacity for dataflow.
Some approaches for implementing Google Cloud:
By deploying Jenkins, a single virtual host can handle jobs against different operating systems, if the build process uses containers. Users can access the Kubernetes Engine via Google’s global load balancer, which handles the routing of users to the front end with the help of a global IP address.
The tools enable continuous integration and delivery approach, ensuring that each build deployed on the cloud is tested for adherence to passing criteria, post which the build is successfully deployed. The ease of operating Google cloud to accomplish the objectives of CI/CD in a production-like environment offers an edge to stay ahead at every stage of the new development taking place.
Google cloud is a solution that offers great ease for deploying builds in a serverless environment and auto-scaling according to a given volume. With tools like Cloud Build, integrating Kubernetes or Jenkins adds more reasons for adopting Google cloud. Moreover, it offers the most flexible platform for implementing CI/CD in an agile software development environment.