Our project was running in GCP compute engine. For scaling purpose, it is moved to app engine. We had rabbitmq implemented for push messages and chatbots in compute engine. In app engine it is not feasible to implement rabbitmq. So I was going through alternate options. There I found cloud task option. But I have doubts in certain areas even after reading their documentation
In my understanding, we need an app engine instance for cloud tasks. In that case, can I implement it in same project itself as a different service? Will this affect the performance of the existing project?
Is there any better solution than cloud tasks in this case?
You can implement additional services under your app in the App Engine as shown in this diagram.
By default, App Engine scales your app to match the load. Your apps will scale up the number of instances that are running to provide consistent performance, or scale down to minimize idle instances and reduces costs.
You can consider running a RabbitMQ Cluster on Google Kubernetes Engine. You can find more information in the following documentation: rabbitmq.
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I want to deploy and app using compute engine as my company does not provide access to app engine yet. Is there a way to deploy the same app using compute engine rather than app engine on google cloud. I have searched multiple forum but unable to find relevant answers.
Any help would be much appreciated.
With python3, I recommend you to write a Flask web application. Your web application will be similar on App Engine and on your compute.
However, you have several things to perform at the infrastructure level. I recommend you to have a look to managed Instances group with auto scaling and health check and Global load balancer.
Note: Because, it's not serverless, you have to pay at least 1 instance even if there isn't traffic on your app
Alternatively, you can have a look to GKE (easier VM management and scaling) and Cloud Run.
After reading available answers/comments on similar questions on this forum, it is now evident that GAE app is not straight-forward ready to be deployed on Compute engine. I fully understand that what all the managed services(mostly as APIs be it, datastore, document/index Search, memcache, cloud storage, task queues, cron jobs etc.), App Engine offered being a platform, won't be the same-fashioned accessible/integration-ready if available on Compute engine at all.
We have a 5 years old fully-grown App engine app now.
I am considering a scenario to support high-level of customization/control and adding third party softwares/middlewares to our server environment which is not possible with App engine. So if we have all solutions(Compute Engines, Container Engines etc.) other than App engine, to migrate our application to meet such requirements, what is the cost of such migration?
Need of server provisioning and configuration at Compute engines with different pricing model[Understood, should not be a problem :)]
Full or partial code rewrite to continue using the same APIs esp. Datastore, Cloud Storage, Task Queues, Cron jobs, Document Search, Memcache etc.[Need confirmation here and any reference/link to migration guide would be help!!]
Does this lead to risk of losing any managed service/API offered from App Engine? Document Search, Memcache, Task Queues, Cron jobs seem the possible candidates. Please confirm.
As per my reading, Big Query, Cloud storage, Pub-Sub APIs integration should not be much affected with such migration(Client-libraries or Rest APIs should still help!). Please confirm.
In nut-shell, We wanted it fully managed in the beginning so PaaS seemed the right choice 5 years ago. Now we want App minus platform-managed plus customized/flexible to our choice. How complicated this transition is going to be?
Full or partial code rewrite to continue using the same APIs esp. Datastore, Cloud Storage, Task Queues, Cron jobs, Document Search, Memcache etc.[Need confirmation here and any reference/link to migration guide would be help!!]
Unfortunately, some of those service only be provided on GAE, such as Document Search. But most of service can be use directly for GCP, such as Datastore, Cloud Storage. GAE Flexible Environment is much like GCP environment, so you can read this article first Migration to GAE Flexible Environment
In following articles also have some answer：
How to migrate Google App Engine Project to Compute Engine completely
Google App Engine Blobstore to Google Cloud Storage Migration Tool
Does this lead to risk of losing any managed service/API offered from App Engine? Document Search, Memcache, Task Queues, Cron jobs seem the possible candidates. Please confirm.
Yes, Document Search only available on GAE.
As per my reading, Big Query, Cloud storage, Pub-Sub APIs integration should not be much affected with such migration(Client-libraries or Rest APIs should still help!). Please confirm.
Yes, but you may need to change SDK or library. It dependency on your language and how to call those service by Rest API directly or SDK.
I have a job that involves continuously listening to one or more websocket/mqtt feeds and forwarding this data to an event queue. This job is written in javascript and would run 24/7 in a continuous loop.
The most obvious solution is to run this job on a VM with Compute Engine, but I was wondering is there is a more elegant solution. Azure, for example, has WebJobs that's well-suited to this kind of task. It even restarts the script if there is an error.
Is there some other component on GCP that can run this job in a "managed" way?
Google Cloud does not have a product similar to Azure WebJobs at the moment. Both the standard and flexible environments of Google Cloud App Engine do not currently support websockets. In order to use websockets you can use Compute Engine or Kubernetes Engine.
I have a machine learning project and for this project, I have to get data from a website in evey 15 minutes. And I decided to use google cloud platform to do it. I've coded a python script to do the process(get the data from website and write down to a csv file) and when I run this script on my computer, it works well. I need to run this script for a couple weeks. So it should be running in google cloud's computers and it should continue running when I close my computer. How can I do this?
I can also use another cloud service if it's required to but google cloud would be better.
Disclaimer: I'm with Google Cloud Platform Support
Google Cloud Compute Engine is defined as an Infrastructure as a Service. It basically provides access to Virtual Machines (VMs), Disks and Networking functionalities. By using this product, you are able to configure your resources from scratch, defining one or multiple VM instances, configuring your work environment, etc. It might require more configuration and boiler plating than needed, but it offers the most control. You can always use some resources for free but in my opinion it is a lot of scratch to start from.
Google Cloud App Engine is defined as a Platform as a Service. It is basically a managed app platform. The management can be automatised to certain degrees. It is based on Compute Engine, in the sense that it provides functionalities, a platform, on top of the infrastructure defined by Compute Engine VMs. You can thus deploy your python script in an App Engine Flexible Python Environment. You can define your whole application as a collection of interrelated microservices, i.e. one service gets the data from a website, maybe another writes csv files and another might trigger ML jobs.
App Engine also provides the possibility to schedule jobs as cron jobs. So if your application needs to run periodical jobs or at a specific time, this is the tool to use. App Engine pricing is correlated with the used resources, but you can estimate eventual budgets by using the Google Cloud Platform Pricing Calculator.
You can store the csv files in Google Cloud Storage as objects in buckets or as data in Datastore, Cloud SQL or BigQuery. Components of Google Cloud Platform can communicate with each other via service acounts. This allows your App Engine deployment, for example, to perform CRUD operations in your Cloud SQL instance, programatically. Or... to trigger a Cloud Machine Learning job.
Your question is very broad and can be addressed in multiple, various ways. I would initially deploy the python script in App Engine Flexible. I would deploy a cron job if needed, to fetch data every 15 minutes. I would upload the csv files in Google Cloud Storage Buckets. I would then use the Cloud Machine Learning python client to trigger Machine Learning jobs programatically.
There are other products that might interest you:
Cloud Dataflow - configure stream/batch data processing
Cloud Dataprerp - transform/clean raw data
Cloud Pub/Sub - global real-time messaging.
All the products/components and sub-products/sub-components can communicate with each other and processes can easily be automated in the Cloud. So the whole project can run in Google's Cloud infrastructure when you close your computer. But, of course, you have to configure it beforehand, in your Google Cloud Platform Project(s).
I am aware that I met your broad question with a broad answer. For any specific issues along your path of implementing the project in the Cloud, the community will be here to provide support.
Good luck!
Google CloudSQL gives the option to allow it to follow an App Engine app for better performance.
How can I do the same with a Google Compute Engine instance? Otherwise what is the best Google data center to house my instance for best performance with a US based App Engine app?
Depending on what you're trying to achieve the way to go might be an app with two modules, one of which is a managed vm.
If you need a persistent disk in your managed vm you can mount cloud storage with fuse in your managed vm.