Case studies of successful applications deployed on Google Cloud Run

Are you wondering about the real-world success stories of Google Cloud Run? Look no further! In this article, we'll dive into some exciting case studies of successful applications deployed on Google Cloud Run. By the end of this read, you'll be inspired to build and deploy your applications on this platform.

What is Google Cloud Run?

Before delving into the case studies, let's get a brief overview of Google Cloud Run.

Google Cloud Run is a serverless computing platform developed by Google Cloud. It allows developers to run stateless containers on a fully managed environment, where they can automatically scale to meet traffic demands. With Cloud Run, developers are not required to manage infrastructure or servers, and they only pay for the compute time their application uses. Moreover, Cloud Run is part of the larger Google Cloud platform, which provides a complete suite of tools for building, running, and managing applications on the cloud.

Case Study 1: Twitch

When it comes to streaming services, Twitch is easily one of the most popular platforms in the world. But did you know that they recently migrated their entire chat service to Google Cloud Run?

Before the migration, Twitch's chat service was run on a traditional server infrastructure, which meant that they had to manage the servers and scaling themselves. However, this approach was not scalable, and it became increasingly hard to manage as Twitch's user base grew. Additionally, it became more expensive and complex to manage over time.

So how did they make the shift to Cloud Run? Twitch built their chat service as containers and started deploying them to Kubernetes. Following this, they deployed their services on Cloud Run using the Knative-based serverless framework, which enables them to automatically scale the service based on incoming traffic.

The result? Twitch's chat service can now handle 3X more traffic than before, and the company has seen a significant cost reduction. Once the service was live on Cloud Run, Twitch was able to make configuration changes to size the infrastructure properly, which meant that they could save on costs by allocating the exact amount of resources they needed.

Case Study 2: OLX Brazil

OLX is a Brazilian online classifieds marketplace, and they recently migrated their entire backend to Cloud Run. The migration allowed them to streamline their operations, thereby enabling the company to focus on their core business- improving the user experience.

Before the migration, OLX was using an aging system that was hard to scale and manage. The company wanted a solution that was easy to manage and would enable them to scale their operations in real-time. Cloud Run was a perfect fit.

OLX migrated part of its backend to Cloud Run, starting with their core REST API. They built the service as containers and deployed it on Cloud Run using a standard CI/CD pipeline. One of the standout features of Cloud Run is that it supports multiple programming languages, enabling OLX to have language diversity in their team. They used Golang, Python, and Node.js to build the service.

The result? OLX has seen a reduction in infrastructure costs and an improvement in uptime since the migration. With Cloud Run, they can handle a vast array of operations and have a clear view of how their system is performing in real-time.

Case Study 3: Google Photos

Google Photos is one of the most popular photo storage and sharing services available in the market today. Interestingly, Google Photos is built entirely on a microservices architecture and runs on Google Cloud Platform.

Google Photos uses multiple microservices, and each microservice is designed to handle a specific task. For instance, the image processing microservice is dedicated to processing images, while the authentication microservice is responsible for managing user authentication. Since each microservice is built as a container, they can easily be deployed on Cloud Run.

Google Photos migrated some of their microservices to Cloud Run and deployed them as stateless containers. The company chose Cloud Run since it allowed them to benefit from the serverless computing model while still being able to run microservices. By deploying their microservices on Cloud Run, Google Photos was able to eliminate the infrastructure overhead and focus on their core business- offering a great user experience.

Conclusion

Google Cloud Run is an excellent platform for running stateless containers. With a variety of programming languages, CI/CD integrations, and serverless computing benefits, it's no surprise that companies are increasingly choosing this platform to streamline their operations.

These three case studies highlight the vast array of use-cases where Google Cloud Run can add value. From improving scalability, reducing infrastructure costs, and enhancing the user experience, there's no end to what you can achieve with Cloud Run.

So if you're looking for a platform that'll enable you to build and deploy your applications seamlessly, look no further than Google Cloud Run. It's an excellent way to move your applications to the cloud without the associated infrastructure concerns.

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