Functions & Logic Apps are two distinct offerings by Microsoft Azure. I wonder what are the use cases that one should favor the new Functions offering over Logic Apps.
Azure Functions is code being triggered by an event.
Logic Apps is a workflow triggered by an event.
That means that they are also, in fact, complementary. You can, as of sometime yesterday, add a Function as part of a workflow inside a Logic App via the Logic Apps UX.
TL;DR - It's Logic Apps + Functions, not Logic Apps OR Functions.
"Here are few use cases where you can decide to choose between Azure Functions and Azure Logic Apps.
Azure Functions:
Azure Function is code being triggered by an event
Azure Functions can be developed and debugged on local workstation, which is a big
plus to increase developer productivity
When dealing with synchronous request/response calls, that execute more complex logic, Azure function is preferred option
Logic Apps:
Logic Apps is a work flow triggered by an event
Logic Apps run only in the cloud, as it has a dependency on Microsoft-managed connectors. It cannot be debug, test or run Logic Apps locally
Logic Apps is better suited for asynchronous integration and fire-and-forget messaging that requires reliable processing.
Azure Functions has sufficient logging and troubleshooting capabilities and you can even build your custom monitoring tools. Functions does not depend on cloud, it can run locally too."
Logic Apps are used for automating your business process. They make integration with cloud and on premise systems easy with several out of the box connectors. Azure functions on the other hand do something in response to an event, for instance when a message is added to a queue, or a blob is added, process these etc. I guess you can even expose Azure functions as an HTTP API endpoint and integrate into your business process using Logic Apps.
The other obvious difference in my mind is the pricing, Azure functions are charged based on the compute used for the function to execute and the associated memory with the function (https://azure.microsoft.com/en-us/pricing/details/functions/).
Just wanted to add some of my thoughts
Azure Function Apps should be used for
High frequency tasks - 1,000,000 executions and 400,000 GB-s of memory is free and then the price is very low. Once you know any coding language functions support you can run millions and millions of executions at very low cost.
Very easy to bind with multiple Azure services - while Logic Apps also bind easily to external services if you want to do it from logic apps at high frequency it will cost you a buck or two. Functions also allow for easy input and output bindings to external azure services.
Stateful executions - with durable task framework you can run multiple functions, perform fan-in and fan-out and write stateful executions with ease.
Programming and Scripting Languages - if you already know programming languages then functions might be easy way to migrate some of your applications to the cloud with minimal changes.
Azure Logic Apps should be used for
Low frequency - biggest reason for this is pricing model. Imagine as if single action in logic app is what you pay for as it is separate execution.
For example, if you have 1 logic app with 3 steps and you run it every 10 seconds. This will be 18 actions per minute. So, 1080 per hour, 25920 per day. If those 3 actions connect to anything external, i.e. blobs/http, etc. They are connectors and as such simple logic app with 26,000 connector runs per day will net you 100$ a month. Compared to most likely under 1$ for functions.
Combining lots of external services/APIs - thanks to 200+ connectors you can easily combine multiple services without a need to learn APIs and such. This is simple TCO calculation, is it better to write X amount of API integrations for price of developer or just use out of the box connectors.
Extremely well-designed logging - with visual logging it is very easy to check every single execution step input, outputs, time etc. As if you did log every single line in Azure Functions.
Nicely extends other services like Data Factory - some services are extremely well designed for certain tasks, but they are not as good at other tasks. For instance, data factory can't send emails out of the box but in 10 minutes you can call HTTP webhook for Logic App from data factory and start sending emails at ease.
In short as other said. They pay different roles and should be used as such.
In general, Logic apps ❤️ functions.
If you want to check out some info, I encourage you to check
Function Apps intro video https://youtu.be/Vxf-rOEO1q4
Logic Apps intro video https://youtu.be/UzTtastcBsk
Logic Apps security with API management https://marczak.io/posts/2019/08/secure-logic-app-with-api-management/
The answer to this question might have changed after the release of Azure Durable Functions.
Now the overlap between the two platforms is greater. Both service offerings allow you to build serverless workflows; while Azure Durable Functions are code-based workflows, Logic Apps are visually designed workflows.
Logic Apps are better suited when building integration solutions due to the very extensive list of connectors that should reduce the time-to-market, and when rich visual tools to build and manage are preferred.
Durable Functions are a better fit if you require or prefer to have all the power and flexibility of a robust programming language, or you need more portability, and the available bindings and logging capabilities are sufficient.
A detailed comparison between the two platforms is in this post.
Logic Apps is the iPaas offering from Microsoft. It can be used to create easy-to-implement Integration Solutions on the Cloud. It comes with an array of out-of-the-box connectors that can be used to integrate solutions across On-Premises and Could based applications.
Azure functions, however, can be used to quickly run small pieces of code or functions on the "Cloud". Azure functions can be integrated with Logic Apps to run snippets of code from within Logic Apps.
I use both extensively. I prefer Logic Apps over Azure Function for simple apps/api. Knowledge transfer of Logic Apps is pretty easy as the next guy just have to look at the picture. Logging/tracing is also already built-in. However, Logic Apps (and Flow) will become messy and not easily readable when you have more than just a few if-else or case conditions or if you have several nested workflows. Error handling in Logic Apps also leaves a lot to be desired.
Azure Function
The azure function is a piece of code that gets triggered on some event or timer
it could be debugged and there are a couple of languages in which you can code in
and couple options to write code like Visual Studio Code, Visual studio, In-portal
Logic app
It is a workflow orchestration tool, it gets triggered in a similar way as the azure functions but it's a drag and drop tool you can't code in it
it provides a bunch of action to perform the functionality it is mainly used for integrating systems
Both the system is based on the serverless architecture but the azure logic app is easy to develop and debug but limited in scope
if you require a lot customized logic azure function is for you
Related
Sorry, if this is a naive question, but i've watched bunch of talks from google's staff and still don't understand why on earth i would use AE instead of CF?
If i understood it correctly, the whole concept of both of these services is to build "microservice architecture".
both CF and AE are stateless
both suppose to execute during limited period of time
both can interact with dbs and other gcp apis.
Though, AE must be wrapped into own server. Basically it utilizes a lot of complexities on top of the same capabilities as CF. So, when should i use it instead of CF?
Cloud Functions (CFs) and Google App Engine (GAE) are different tools for different jobs. Using the right tool for the job is usually a good idea.
Driving a nail using pliers might be possible, but it won't be as convenient as using a hammer. Similarly building a complex app using CFs might be possible, but building it using GAE would definitely be more convenient.
CFs have several disadvantages compared to GAE (in the context of building more complex applications, of course):
they're limited to Node.js, Python, Go, Java, .NET Core, and Ruby. GAE supports several other popular programming languages
they're really designed for lightweight, standalone pieces of functionality, attempting to build complex applications using such components quickly becomes "awkward". Yes, the inter-relationship context for every individual request must be restored on GAE just as well, only GAE benefits from more convenient means of doing that which aren't available on CFs. For example user session management, as discussed in other comments
GAE apps have an app context that survives across individual requests, CFs don't have that. Such context makes access to certain Google services more efficient/performant (or even plain possible) for GAE apps, but not for CFs. For example memcached.
the availability of the app context for GAE apps can support more efficient/performant client libraries for other services which can't operate on CFs. For example accessing the datastore using the ndb client library (only available for standard env GAE python apps) can be more efficient/performant than using the generic datastore client library.
GAE can be more cost effective as it's "wholesale" priced (based on instance-hours, regardless of how many requests a particular instance serves) compared to "retail" pricing of CFs (where each invocation is charged separately)
response times might be typically shorter for GAE apps than CFs since typically the app instance handling the request is already running, thus:
the GAE app context doesn't need to be loaded/restored, it's already available, CFs need to load/restore it
(most of the time) the handling code is already loaded; CFs' code still needs to be loaded. Not too sure about this one; I guess it depends on the underlying implementation.
App Engine is better suited to applications, which have numerous pieces of functionality behaving in various inter-related (or even unrelated) ways, while cloud functions are more specifically single-purpose functions that respond to some event and perform some specific action.
App Engine offers numerous choices of language, and more management options, while cloud functions are limited in those areas.
You could easily replicate Cloud Functions on App Engine, but replicating a large scale App Engine application using a bunch of discrete Could Functions would be complicated. For example, the backend of Spotify is App Engine based.
Another way to put this is that for a significantly large application, starting with a more complex system like App Engine can lead to a codebase which is less complex, or at least, easier to manage or understand.
Ultimately these both run on similar underlying infrastructure at Google, and it's up to you to decide which one works for the task at hand. Furthermore, There is nothing stopping you from mixing elements of both in a single project.
Google Cloud Functions are simple , single purpose functions which are fired while watching event(s).
These function will remove need to build your own application servers to handle light weight APIs.
Main use cases :
Data processing / ETL : Listen and respond to Cloud Storage events, e.g. File created , changed or removed )
Webhooks : Via a simple HTTP trigger, respond to events originating from 3rd party systems like GitHub)
Lightweight APIs : Compose applications from lightweight, loosely coupled bits of logic
Mobile backend: Listen and respond to events from Firebase Analytics, Realtime Database, Authentication, and Storage
IoT: Thousands of devices streaming events and which in-turn calls google cloud functions to transform and store data
App Engine is meant for building highly scalable applications on a fully managed serverless platform. It will help you to focus more on code. Infrastructure and security will be provided by AE
It will support many popular programming languages. You can bring any framework to app engine by supplying docker container.
Use cases:
Modern web application to quickly reach customers with zero config deployment and zero server management.
Scalable mobile backends : Seamless integration with Firebase provides an easy-to-use frontend mobile platform along with the scalable and reliable back end.
Refer to official documentation pages of Cloud functions and App Engine
As both Cloud Functions and App Engine are serverless services, this is what I feel.
For Microservices - We can go either with CF's or App Engine. I prefer CF's though.
For Monolithic Apps - App engine suits well.
Main differentiator as #Cameron points out, is that cloud functions reliably respond to events. E.g. if you want to execute a script on a change in a cloud storage bucket, there is a dedicated trigger for cloud functions. Replicating this logic would be much more cumbersome in GAE. Same for Firestore collection changes.
Additionally, GAE’s B-machines (backend machines for basic or manual scaling) have conveniently longer run times of up to 24 hours. Cloud functions currently only run for 9 minutes top. Further, GAE allows you to encapsulate cron jobs as yamls next to your application code. This makes developing a server less event driven service much more clean.
Of course, the other answers covered these aspects better than mine. But I wanted to point out the main advantages of Cloud Functions being the trigger options. If you want functions or services to communicate with each other, GAE is probably the better choice.
I'm trying to decide whether to build a Logic App or a Web App.
It has to do things I'm quite comfortable doing in C#: receive messages in various formats (a few thousand per day), translate them, make API calls and forward them. None of the endpoints are widely used, so the out-of-the-box connectors won't be a benefit. Some require custom headers, the contents of which are calculated using a hashing algorithm. Some of the work involves converting Json into XML and vice-versa.
From what I've read, one of the key points of difference of Logic Apps are that you don't have to write any code. Since our organisation is actually quite comfortable with code, that doesn't feel like it'll actually be a benefit.
Am I missing something? Are there any compelling reasons why a Logic App would be better than a Web App in this instance?
Using Logic Apps has a few additional benefits over just writing code which include:
Out of box monitoring. For every execution you get to see exactly what happened in each step of the process with a monitoring view that replicates your Logic App design view.
Built in failure handling. Logic Apps will automatically retry calls on failure cases and also allows you to either customize the retry policy or have a custom retry policy with a do-until pattern.
Out of box alerting. You can configure alerts to inform you of failures.
Serverless. You don't worry about sizing or scaling and you pay by consumption.
Faster development. Logic Apps allows you to build out the solution faster especially as you consider that you don't have to code for monitoring views, alerting, and error handling that comes out of the box with Logic Apps.
Easy to extend. If you are already using a Logic App access to over a 125 connectors to various services will make it easy to add business value or making it smarter by including things like cognitive services to your workflow with very little extra effort.
I've decided to keep away from Logic Apps for these reasons:
It is not supported outside Azure. We aren't tied to any other providers, and to use Logic Apps would break that independence.
I don't know how much of the problem is readily soluble using Logic Apps. (It seems I will be solving all sorts of problems which wouldn't be problems if I was using C#. This article details some issues encountered while developing a simple process using an earlier version of Logic Apps.)
Nobody has come up with an argument more compelling than the reasons I've given above (especially the first one) why we should use it, so it would be a gamble with little to gain and plenty to lose.
You can think of Logic Apps as an orchestrator - something that takes external pieces of functionality, and weaves a workflow together.
It has nothing to do with your requirement of "writing code" - your code can be external functions on any platform - on-prem, AWS, Azure, Zendesk, and all of your code can be connected together using Logic Apps.
Regardless of which platform you choose, you will still have cross-cutting concerns such as monitoring, logging, alerting, deployments, etc, and Logic Apps addresses very robustly all of those requirements.
We are currently looking into replacing one of our apps with possibly an ESB or some similar tool and was looking for some insights into how best to approach this.
We currently have a stand alone service that consumes/interact with different external services and data sources, some delivered through SOAP Web Services and others we just use a DB connection. This service is exposed through SOAP and we have other apps that consume this service but are very tightly coupled to it, now we also have other apps that need to consume some of the external services and would like to replace this all together with an ESB or some sort of SOA platform.
What would be the best way to replace this 'external' services integration layer with an ESB? We were thinking of having a 'global' contract/API in which all of the services we consume are exposed as one single contract where all the possible operations and data structures that we use are exposed under one single namespace, would this be the best way of approaching this? and if so are there any tools that could help us automate this process or do we basically have to handcraft this contract/API?. This would also mean that for any changes to the underlying services/API's we will have to update this new API as well.
If not then the other option I see is to basically use the 'ESB' as a 'proxy' layer in which all of our sources are exposed as they are, so we would end up with several different 'contracts' / API endpoints, but I don't really see the value in this.
Also given the above what would be the best tool for the job? is a full blown ESB an overkill or are we much better rolling our own using something like Apache Camel or Spring Integration?.
A few more details:
We are currently integrating over 5 different external services with more to come in the future.
Only a couple of apps consuming our current app at the moment but several other apps/systems in the future will need to consume some of these external services.
We are currently using a single method of communication (SOAP) between these services but some apps might use pub/sub messaging in the future, although SOAP will still be the main protocol used.
I am new to ESB integration so I apologize in advance if I'm misunderstanding a lot of these technologies and the problems they are meant to solve.
Any help/tips/pointers will be greatly appreciated.
Thanks.
You need to put in some design thoughts of what you want to achieve over time.
There are multiple benefits and potential pitfalls with an ESB introduction.
Here are some typical benefits/use cases
When your applications are hard to change or have very different release cycles - then it's convenient to have an ESB in the middle that can adopt the changes quickly. This is very much the case when your organization buys a lot of COTS products and cloud services that might come with an update the next day that breaks the current API.
When you need to adapt data from one master data system to several other systems and they might not support the same interfaces, i.e. CRM system might want data imported via web services as soon as it's available, ERP want data through db/staging tables and production system wants data every weekend in a flat file delivered via FTP. To keep the master data system clean and easy to maintain, just implement one single integration service in the master data system, and adapt this interface to the various other applications within the ESB plattform instead.
Aggregation or splitting of data from various sources to protect your sensitive systems might be a use case. Say that you have an old system that can take a small updates of information at a time and it's not worth to upgrade this system - then an integration solution that can do aggreggation or splitting or throttling can be a good solution.
Other benefits and use cases include the ability to track and wire tap every message passing between systems - which can even be used together with business intelligence tools to gather KPI:s.
A conceptual ESB can also introduce a canonical message format that is used for all services that needs to communicate. If a lot of applications share the same data with several other applications (not only point to point) - then the benefits of a canonical message format can outweight the cost (which is/can be high). An ESB server might be useful to deal with canonical data as it is usually very good at mapping from one format to another.
However, introducing an ESB without a plan what benefits you are trying to achieve is not really a good thing, since it introduces overhead - you need another server to keep alive, you need perhaps another team to understand all data flows. You need particular knowledge with your integration product. Finally, you need to be able to have some governance around it so that your ESB initiative does not drift away from the goals/benefits you have foreseen.
You should choose some technology that you are comfortable with - or think you can be comfortable with. Apache Camel is indeed very powerful and my favorite integration engine - but it's not an ESB as it does not come with a runtime that you can use to deploy/manage/monitor your integration services with. You can use it together with most Java EE application servers or even better - Apache ServiceMix (= Karaf+Camel+ActiveMQ+CXF) which is built for this task.
The same goes with spring integration - you need to run it somewhere, app servers or what not.
There is a large set of different products, both open source and commercial that does these things.
Please I need help.
I have project in which I need application which communicates with local DB server and simultaneously with central remote DB server to complete some task(read stock quotas from local server create order and then write order to central orders DB,...).
So, I don`t know which architecture and technology do this.
Web application, .NET WinForms client applications on each computer, or web services based central application with client applications?
What are general differences between this approaches?
Thanks
If you don't want to expose your database directly to the clients, I'd recommend having a web service layer in between. Depending on the sensitivity of your data and the security level of your network, I'd recommend either a web service approach (where you can manage the encryption of data yourself, and without need for expensive ssl certificates) or a web interface (which might be easier to construct, but with limitations in security).
I agree with Tomas that a web service layer might be good. However, when it comes to choosing between webforms or winforms I don't think your question includes enough information to make the choice.
I'd say that if you want a powerful and feature rich user interface and want to make development easy, Winforms is probably the way to go. But if you need it to be usuable from a varied array of clients and want easier maintenance and deployment, a web app might be best.
First, focus on the exact relationship between these databases. What does "local" mean. Right there on the user's desktop? Shared between all the users in their office? Presumably the local quotes (you do mean stock quotes and not quotas?) could potentiually be a little out of date relative to the central order server's view of the world. Does that matter? I place an order for 100 X at price 78.34, real price may be different. What is the intended behaviour.
My guess is that there is at least some business logic and so we need to decide where that runs. One (thick client) approach is to put that logic on the desktop, the desktop app then might write directly to the central DB. I don't tend to do this for several reasons:
Every client desktop gets a database connection. Scaling is not good, eventually the database gets unhappy when the number of users gets very large.
If we need a slightly different app, perhaps exposed to a different set of users via the Web or whatever, we end up reproducing that business logic.
An alternative approach (thin or browser based) keeps the UI on the desktop, but puts the logic on the server. The client can then invoke some kind of service. Now there's lots of possible ways of doing that, a simple Web Service or Rest Service will do the job. I hope it's clear that this service-based appraoch addressed my two points above.
By symmetry I would treat the local databases in the same way, wrap them in services. However it's possible that some more complex relationship between the databases exists and in which case you might need the local service layer to interact with the central service layer.
I'm touting the general pronciple of Do Not Repeat Yourself, implement each piece of business logic once.
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What alternatives are there to GAE, given that I already have a good bit of code working that I would like to keep. In other words, I'm digging python. However, my use case is more of a low number of requests, higher CPU usage type use case, and I'm worried that I may not be able to stay with App Engine forever. I have heard a lot of people talking about Amazon Web Services and other sorts of cloud providers, but I am having a hard time seeing where most of these other offerings provide the range of services (data querying, user authentication, automatic scaling) that App Engine provides. What are my options here?
AppScale
AppScale is a platform that allows users to deploy and host their own Google App Engine applications. It executes automatically over Amazon EC2 and Eucalyptus as well as Xen and KVM. It has been developed and is maintained by AppScale Systems. It supports the Python, Go, PHP, and Java Google App Engine platforms.
http://github.com/AppScale/appscale
In the mean time...
...it is amost 2015 and it seems that containers are the way to go forward. Alternatives to GAE are emerging:
Google has released Kubernetes, container scheduling software developed by them to manage GCE containers, but can be used on other clusters as well.
There are some upcoming PaaS on Docker such as
http://deis.io/
http://www.tsuru.io/
even Appscale themselves are supporting Docker
Interesting stuff to keep an eye on.
I don't think there is another alternative (with regards to code portability) to GAE right now since GAE is in a class of its own. Sure GAE is cloud computing, but I see GAE as a subset of cloud computing. Amazon's EC2 is also cloud computing (as well as Joyent Accelerators, Slicehost Slices), but obviously they are two different beasts as well. So right now you're in a situation that requires rethinking your architecture depending on your needs.
The immediate benefits of GAE is that its essentially maintenance free as it relates to infrastructure (scalable web server and database administration). GAE is more tailored to those developers that only want to focus on their applications and not the underlying system.In a way you can consider that developer friendly. Now it should also be said that these other cloud computing solutions also try to allow you to only worry about your application as much as you like by providing VM images/templates. Ultimately your needs will dictate the approach you should take.
Now with all this in mind we can also construct hybrid solutions and workarounds that might fulfill our needs as well. For example, GAE doesn't seem directly suited to this specific app needs you describe. In other words, GAE offers relatively high number of requests, low number of cpu cycles (not sure if paid version will be any different).
However, one way to tackle this challenge is by building a customized solution involving GAE as the front end and Amazon AWS (EC2, S3, and SQS) as the backend. Some will say you might as well build your entire stack on AWS, but that may involve rewriting lots of existing code as well. Furthermore, as a workaround a previous stackoverflow post describes a method of simulating background tasks in GAE. Furthermore, you can look into HTTP Map/Reduce to distribute workload as well.
As of 2016, if you're willing to lump PaaS (platform as a service) and FaaS (function as a service) in the same serverless computing category, then you have a few FaaS options.
Proprietary
AWS Lambda
AWS Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume - there is no charge when your code is not running. With Lambda, you can run code for virtually any type of application or backend service - all with zero administration. Just upload your code and Lambda takes care of everything required to run and scale your code with high availability. You can set up your code to automatically trigger from other AWS services or call it directly from any web or mobile app.
AWS Step Functions complements AWS Lambda.
AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly. Step Functions is a reliable way to coordinate components and step through the functions of your application. Step Functions provides a graphical console to arrange and visualize the components of your application as a series of steps. This makes it simple to build and run multi-step applications. Step Functions automatically triggers and tracks each step, and retries when there are errors, so your application executes in order and as expected. Step Functions logs the state of each step, so when things do go wrong, you can diagnose and debug problems quickly. You can change and add steps without even writing code
Google Cloud Functions
As of 2016 it is in alpha.
Google Cloud Functions is a lightweight, event-based, asynchronous compute solution that allows you to create small, single-purpose functions that respond to cloud events without the need to manage a server or a runtime environment. Events from Google Cloud Storage and Google Cloud Pub/Sub can trigger Cloud Functions asynchronously, or you can use HTTP invocation for synchronous execution.
Azure Functions
An event-based serverless compute experience to accelerate your development. It can scale based on demand and you pay only for the resources you consume.
Open
Serverless
The Serverless Framework allows you to deploy auto-scaling, pay-per-execution, event-driven functions to any cloud. We currently support Amazon Web Service's Lambda, and are expanding to support other cloud providers.
IronFunctions
IronFunctions is an open source serverless computing platform for any cloud - private, public, or hybrid.
It remains to seen how well FaaS competes with CaaS (container as a service). The former seems more lightweight. Both seem suited to microservices architectures.
I anticipate that functions (as in FaaS) are not the end of the line, and that many years forward we'll see further service abstractions, e.g. test-only development, followed by plain-language scenarios.
Alternatives:
1. AppScale
2. Heroku.
Ref: Alternative for Google AppEngine?
Amazon's Elastic Compute Cloud or EC2 is a good option. You basically run Linux VMs on their servers that you can control via a web interface (for powering up and down) and of course access via SSH or whatever you normally set up...
And as it's a linux install that you control, you can of course run python if you wish.
Microsoft Windows Azure might be worth consideration. I'm afraid I haven't used it so can't say if it's any good and you should bear in mind that it's a CTP at the moment.
Check it out here.
A bit late, but I would give Heroku a go:
Heroku is a polyglot cloud application platform. With Heroku, you
don’t need to think about servers at all. You can write apps using
modern development practices in the programming language of your
choice, back it with add-on resources such as SQL and NoSQL databases,
Memcached, and many others. You manage your app using the Heroku
command-line tool and you deploy code using the Git revision control
system, all running on the Heroku infrastructure.
https://www.heroku.com/about
You may also want to take a look at AWS Elastic Beanstalk - it has a closer equivalence to GAE functionality, in that it is designed to be PaaS, rather than an IaaS (i.e. EC2)
If you're interested in the cloud, and maybe want to create your own for production and/or testing you have to look at Eucalyptus. It's allegedly code compatible with EC2 but open source.
I'd be more interested in seeing how App Engine can be easily coupled with another server used for CPU intensive requests.
TyphoonAE is trying to do this. I haven't tested it, but while it is still in beta, it looks like it's atleast in active development.
The shift to cloud computing is happening so rapidly that you have no time to waste for testing different platforms.
I suggest you trying out Jelastic if you are interested in Java as well.
One of the greatest things about Jelastic is that you do not need to make any changes in the code of your application, except the changes for your application functionality, but not for the reason the chosen platform demands this. With reference to this you do not actually waste your time.The deployment process is just flawless, and you can deploy your .war file anywhere further.Using GAE requires you to modify the app around their system needs. In case if you happen to get working with Java and start looking for a more flexible platform, Jelastic is a compatible alternative.
You can also use Red Hat's Cape Dwarf project, to run GAE apps on top of the Wildfly appserver (previously JBoss) without modification.
You can check it out here:
http://capedwarf.org/