In recent years, DevOps Industry has been experiencing some transformation, with many of Platform as a Service (PaaS) new entrants, indicating that cloud computing and cloud automation are getting more popular. In 2025, the industry has been forecasted to grow, enhance software development, and functions of IT Operations. But before that, we have to dive into DevOps first.

DevOps is an operational and a technical approach that bridges the development of applications with IT Operational. This approach deeply emphasises collaboration, communication and automation to simplify the software development process. The DevOps team could create applications that have been developed by the software development team to be faster and more reliable with sophisticated application security. The best practices from DevOps include: Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as a Code (IaaC), and Monitoring & Logging.

One of cloud computing platform services that’s ubiquitously demanded is Google Cloud Platform (GCP). GCP provides a service that could improve DevOps experience made also by DevOps Experts. Specifically in this era, where there are so many machine learning programs, AI, and others, GCP could assist the DevOps team to create application environments that’s proper to store developed applications. Some of the services that GCP provides to help the development of DevOps Industry globally are:

Serverless Computing

1. Cloud Computing

This service is useful to run functions from code that we have developed in a la carte. For instance, we could have a function to send a mail blast. With this kind of cloud function, we could deploy the function as a runner without having to rent a server as a whole, we could recognise this as an event-driven application.

2. App Engine

App Engine is quite similar to cloud functions. But the difference is that App engine is usually used to deploy services, not functions. App engine has a great scalability with its auto-replicate function.

3. Cloud Run

Cloud run is one of the services that is commonly used to deploy a service, like App Engine. However, cloud run is a service that has a container-based characteristics, while App Engine has a Language-Specific Runtime characteristic, which means that cloud run will run an application as a deployed image container within the application. While on the other hand, the app engine will run the application as the used  programming language runtime. Both of them could be leveraged and used by pay-per-use payment scheme, but for the cloud run, the parameter of usage would be from its resource. While the app engine is counted from resources and also the usage.

AI and Machine Learning Integration

1. Intelligent Automation

AI and ML will help the DevOps team to automate complex tasks like the infrastructure development, application deployment or even disaster recovery from incidental events.

2. Predictive Analysis

By analysing some data, AI will help the DevOps team to decide some preventive actions for the infrastructure resiliency. For instance, after an analysis, the team recognised that the implemented architecture is overengineered. For then, the engineering team could reduce the specification and get the application running properly with a proper architecture.

3. Self Healing System

AI will assist the DevOps team to solve some happening issues. Whether it’s a memory heap, lagging or even bottlenecks. AI could get you some recommendations to configure the infrastructure that we are using.

To close this article, we believed that there are so many GCP services that could leverage the development of the DevOps Industry. With these developments and demands from the market, the implementation of DevOps should put automation forward, then the developed applications should be also complemented by proper architectures. Further exploration about GCP should be issued, especially for the DevOps team. Besides reducing costs, the initiative could also be concerned with creating some proper environment of application.