Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running
Google Cloud Functions is a tool in the Serverless / Task Processing category of a tech stack.
43 companies use Google Cloud Functions including Policygenius, OTOBANK Inc., and Kalibrr.
Firebase, Google Cloud Storage, Cloud Functions for Firebase, Google Cloud Pub/Sub, and Prisma Cloud are some of the popular tools that integrate with Google Cloud Functions. Here's a list of all 8 tools that integrate with Google Cloud Functions.
Here’s a list of reasons why companies and developers use Google Cloud Functions.
Here are some stack decisions and reviews by companies and developers who chose Google Cloud Functions in their tech stack.
CodeFactor being a #SAAS product, our goal was to run on a cloud-native infrastructure since day one. We wanted to stay product focused, rather than having to work on the infrastructure that supports the application. We needed a cloud-hosting provider that would be reliable, economical and most efficient for our product.
CodeFactor.io aims to provide an automated and frictionless code review service for software developers. That requires agility, instant provisioning, autoscaling, security, availability and compliance management features. We looked at the top three #IAAS providers that take up the majority of market share: Amazon's Amazon EC2 , Microsoft's Microsoft Azure, and Google Compute Engine.
AWS has been available since 2006 and has developed the most extensive services ant tools variety at a massive scale. Azure and GCP are about half the AWS age, but also satisfied our technical requirements.
It is worth noting that even though all three providers support Docker containerization services, GCP has the most robust offering due to their investments in Kubernetes. Also, if you are a Microsoft shop, and develop in .NET - Visual Studio Azure shines at integration there and all your existing .NET code works seamlessly on Azure. All three providers have serverless computing offerings (AWS Lambda, Azure Functions, and Google Cloud Functions). Additionally, all three providers have machine learning tools, but GCP appears to be the most developer-friendly, intuitive and complete when it comes to #Machinelearning and #AI.
The prices between providers are competitive across the board. For our requirements, AWS would have been the most expensive, GCP the least expensive and Azure was in the middle. Plus, if you #Autoscale frequently with large deltas, note that Azure and GCP have per minute billing, where AWS bills you per hour. We also applied for the #Startup programs with all three providers, and this is where Azure shined. While AWS and GCP for startups would have covered us for about one year of infrastructure costs, Azure Sponsorship would cover about two years of CodeFactor's hosting costs. Moreover, Azure Team was terrific - I felt that they wanted to work with us where for AWS and GCP we were just another startup.
In summary, we were leaning towards GCP. GCP's advantages in containerization, automation toolset, #Devops mindset, and pricing were the driving factors there. Nevertheless, we could not say no to Azure's financial incentives and a strong sense of partnership and support throughout the process.
Bottom line is, IAAS offerings with AWS, Azure, and GCP are evolving fast. At CodeFactor, we aim to be platform agnostic where it is practical and retain the flexibility to cherry-pick the best products across providers.
Running background triggers based on events provides a simple, scalable way to create complex interactions. Google Cloud Functions
Useful for personal projects where I have extremely low traffic. Scalability not taken advantage of for personal projects because of lack of funds.
I use it in a more microservice style. A recent use case was subscribing to a free tier of a 3rd party geolocation service (take lat and long, return address), and exposing an endpoint to trigger it, so that I could centralize credentials for the 3rd party service and reuse the endpoint across all proofs of concept and personal projects.
Used equally as often as AWS Lambda, depending on where the rest of the tech stack is hosted. Google Cloud Functions