Azure Functions vs. Engine Yard vs. Google Cloud Run

They're great to embed logic and code in a medium-small, cloud-native application, but they can become quite limiting for complex, enterprise applications.

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It is best for rapidly getting your application to the cloud without worrying about standing up cloud infrastructure

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Microservices and RestFul API application as it is fast and reliant. Seamless integration with event triggers such as pubsub or event arc, so you can easily integrate that with usecases with file uploads, database changes, etc. Basically great with short-lived tasks, if however, you have long-running processses, Cloud Run might not be idle for this. For example if you have a long running data processing task, other solutions such as kubeflow pipelines or dataflow are more suited for this kind of tasks. Cloud Run is also stateless, so if you need memory, you will have to connect an external database.

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• They natively integrate with many triggers from other Azure services, like Blob Storage or Event Grid, which is super handy when creating cloud-native applications on Azure (data wrangling pipelines, business process automation, data ingestion for IoT, ...)
• They natively support many common languages and frameworks, which makes them easily approachable by teams with a diverse background
• They are cheap solutions for low-usage or "seasonal" applications that exhibits a recurring usage/non-usage pattern (batch processing, montly reports, ...)

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• Quick deployments
• Easily integrate your code from GitHub
• Ability to recover site quickly to different zone when AWS has a widespread outage

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• Auto scaling is the best one
• provide direct VPC connectivity and rigid network
• Cloud SQL and Pub/Sub services
• Handling latency issues

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• My biggest complaint is that they promote a development model that tightly couples the infrastructure with the app logic. This can be fine in many scenarios, but it can take some time to build the right abstractions if you want to decouple you application from this deployment model. This is true at least using .NET functions.
• In some points, they "leak" their abstraction and - from what I understood - they're actually based on the App Service/Web App "WebJob SDK" infrastructure. This makes sense, since they also share some legacy behavior from their ancestor.
• For larger projects, their mixing of logic, code and infrastructure can become difficult to manage. In these situations, good App Services or brand new Container Apps could be a better fit.

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• Embracing new Amazon Web Servicess(AWS) features
• Security groups need more granularity
• Audit trails of what happens by who in environment, especially when VM is deleted

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• The UI can be made simpler. Currently the UI is bloated and it takes time to find out what you want
• More integrations with container registry providers (ECR, dockerhub)
• Better permissions UX. Currently GCP requires service accounts to be used with cloud products, the experience adding/removing permissions is difficult to navigate

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Ease of use

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We definitely need to renew it because we dont own our own infrastructure and storage and we are happy with Cloud Run features

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The UI/console is great... the documentation is top-notch for developers, but the CLI itself when you have to script around it is very complex and easy to forget some options... the downside of a generic command line client.

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Not seen any major issues when we run applications its good

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Initially we felt slow but slowly it picked up and easy to manage

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I was involved in the initial implementation setup, Its easy with the given documentaiton we can do ourself. Not that critical

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This is the most straightforward and easy-to-implement server less solution. App Service is great, but it's designed for websites, and it cannot scale automatically as easily as Azure Functions. Container Apps is a robust and scalable choice, but they need much more planning, development and general work to implement. Container Instances are the same as Container Apps, but they are extremely more limited in termos of capacity. Kubernetes Service si the classic pod container on Azure, but it requires highly skilled professional, and there are not many scenario where it should be used, especially in smaller teams.

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More closely aligns to native AWS

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AWS Lambda supports code zip package, enabling lower cold start time. Also, AWS Lambda pricing is much simpler, easier to understand.

Other than that, the 2 products are very similar, including the Docker image support: the image must be built based on proprietary base image.

Obviously, if your other services are running in GCP, then Google Cloud Run is your only choice for tight integration, & private networking.

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Not part of purchase.

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It has good auto scale feature and reliable also

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We have very good support when needed

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• They allowed me to create solutions with low TCO for the customer, which loves the result and the low price, that helped me create solutions for more clients in less time.
• You can save up to 100% of your compute bill, if you stay under a certain tenant conditions.

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• Positive in the sense that we can deploy new applications quickly for MVP

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• Built in support for auto scaling helps reduce operational overhead
• Any application performance issues can be addressed quickly by allocating more resources while a proper fix can be planned and rolled out later
• Using Google Cloud Run enables development of microservices which provides granular control for scaling critical services in the platform

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