As described in How to increase the Socket Connect Count quota for app engine we had hit a quota limitation for GAE socket connect counts ( https://cloud.google.com/appengine/quotas). We end up creating new projects often, so it's a pain to ask for quota increases every time since it takes days. We were wondering if moving to Cloud run will fix this issue, since the quota page for cloud run does not say anything https://cloud.google.com/run/quotas. Just wondering if anyone has any experience on this front.
There are no socket quotas for Cloud Run. Per documentation, no such quotas exist. The documentation is up-to-date.
According to the official documentation link:
Inbound WebSockets and gRPC streaming are not currently supported for
Cloud Run (fully managed). However, those protocols do work outbound
and unary gRPC is supported.
Related
This may be the wrong place for this question, so please re-direct me if necessary.
I have deployed a couple simple functions using Google Cloud Functions that do the following:
Read files from AWS and write to Cloud SQL
Aggregate Cloud SQL data and write csv file to Cloud Storage bucket
Simple OLS prediction model on aggregated data
I have these as separate functions because (1) often takes longer than the Cloud Function maximum timeout. Because of this, I am considering moving this whole thing to App Engine as a service. My question about App Engine Standard are:
What do the request timeouts mean? If I were to run this service, do I still have a short time-limit after which it will no longer run?
Is App Engine the best thing to use for this task?
Thanks for all your help
According to Google Documentation, GAE Standard has a maximum timeout of 1 minute for http requests and 10 minutes for cron/tasks for the older environments. Newer env have it as 10 minutes for both http requests & tasks. If your functions are taking longer than these, then GAE standard won't work for you. For such a case, you should take a look at GAE Flex - see this Google documentation which compares Flex to Standard).
Secondly, it seems to me that what you have are endpoints that are only hit occasionally or at specific scheduled times. If that is the case, I would also recommend taking a look at Cloud Run. We have a blog article about it and we have this
....Another thing to note about Cloud Run is that it only runs when it receives an HTTP request. It plays dead and comes alive to execute your code when an HTTP request comes in. When it is done executing the request, it goes 'dead' again till the next request comes in. This means you're not paying for time spent idling i.e. when it is not doing anything....
You can keep your Cloud Functions and the strong cohesion implemented by each of your 3 Functions, then you can use Cloud Workflows a serverless solution to orchestrate the 3 CF calls. The drawback : you pay for 3 CF invocations and 3 Workflows steps. But does it matter ? Since 2millions CF invocations are free and 5000 Workflows steps are free.
As proposed by #NoCommandLine Cloud Run is indeed an alternative, with its timeout of 3600s(1h). The drawback: you need to wrap your code in a http request and provide a webserver like express or gunicorn.
A hack is to build a docker container for your code with no need for a webserver and run it using Cloud Build which have a timeout of 24 hours.
I'm fairly new to things that aren't strictly front end, so after reading the Google pub/sub docs and doing a few searches its not clear to me whether using it with react is possible.
My use case is I (hypothetically) have tens of thousands of people on my webpage at a time that all need to be told at the same time that some external event occurred (the message would be very small).
I know Google Firestore has a listener feature but based on this specification it would not be within the free tier usage anymore. I've seen libraries that allow Google Pub/Sub to be used with IOT devices so I'm confused on why I can't find any resources on using it in the browser.
Creating a Cloud Pub/Sub subscriber in the frontend would be an anti-pattern for several reasons. First of all, the quota limits only allow 10,000 subscriptions per topic. Since you say you have tens of thousands of people on the web page at a time, you would not be able to create enough subscriptions for this case. Additionally, subscriptions created when users come to the website would not be able to get any notifications from before the time the subscription was created; Cloud Pub/Sub only guarantees delivery of messages published after the subscription was successfully created. Finally, you'd have the issue of security and authentication. In order to start a subscriber from the client, you'd need to pass it credentials that it could use. If you use separate credentials for each webpage viewer, then you'd have to create these credentials on the fly and revoke them when the user disappears. If you use the same credentials across all of the subscribers, then one subscriber could intercept the feed of another subscriber.
Overall, Cloud Pub/Sub is designed for the torrents use case: fewer feeds with a lot of data that has to be processed by fewer subscribers. What you are talking about is the trickles use case: a small number of messages that need to be distributed among a large number of subscribers with individual ACLs. Firebase Cloud Messaging is the product designed for this latter case.
While it is true that Cloud Pub/Sub is on the path for Google Cloud IoT, it is used on the publish side: many devices send their events to a topic that can be processed by subscribers. Note that these messages from devices don't come directly into Cloud Pub/Sub; they go through a Cloud IoT server and that server is what publishes the messages to Cloud Pub/Sub. Device authentication is done via Cloud IoT and not via permissions on Cloud Pub/Sub topics. The delivery of messages to IoT devices is not done with Cloud Pub/Sub.
I have jobs and APIs hosted on cloud composer and App Engine that works fine. However for one of my job I would need to call an API that is IP restricted.
As far as I understand, I see that there's no way to have a fixed IP for app engine and cloud composer workers and I don't know what is the best solution then.
I thought about creating a GCE with a fixed IP that would be switched on/off by the cloud composer or app engine and then the API call would be executed by the startup-script. However, it restrains this to only asynchronous tasks and it seems to add a non desired step.
I have been told that it is possible to set up a proxy but I don't know how to do it and I did not find comprehensive docs about it.
Would you have advice for this use-case ?
Thanks a lot for your help
It's probably out of scope to you, but you could whitelist the whole range of app engine ip by performing a lookup on _cloud-netblocks.googleusercontent.com
In this case you are whitelisting any app engine applications, so be sure this api has another kind of authorization and good security. More info on the App Engine KB.
What I would do is install or implement some kind of API proxy on GCE. It's a bummer to have a VM on 24/7 for this kind of task so you could also use an autoscaler to scale to 0 (not sure about this one).
As you have mentioned: you can set up a TCP or UDP proxy in GCE as a relay, and then send requests to the relay (which then forwards those requests to the IP-restricted host).
However, that might be somewhat brittle in some cases (and introduces a single point of failure). Therefore, another option you could consider is creating a private IP Cloud Composer environment, and then using Cloud NAT for public IP connectivity. That way, all requests from Airflow within Composer will look like they are originating from the IP address of the NAT gateway.
I am hitting this quota and I was wondering wether this quota for External IP?
INVALID_ARGUMENT: The following quotas were exceeded: IN_USE_ADDRESSES (quota: 8, used: 7 + needed: 2).
I have a few services that work via pub/sub and making request outside. Do I still need External IP? Or somehow I can set and use Internal IP?
Meantime I made a request to increase but want to understand this.
This quota is related to the ephemeral IPs used by App Engine. Actually App Engine will always use External IPs, you cannot avoid that, you may want to take a look on how App Engine manages IPs in this documentation.
Everytime you deploy a new version of your app, App Engine by default will retain the old versions with its IPs. You can avoid this situation by stopping the previous versions on deployment with the flag --stop-previous-version.
This is also already answered here.
I have been writing a Google Chrome extension for Stack Exchange. It's a simple extension that allows you to keep track of your reputation and get notified of comments on Stack Exchange sites.
Currently I've encountered with some issues that I can't handle myself.
My extension uses Google App Engine as its back-end to make external requests to Stack Exchange API. Each single client request from extension for new comments on single site can cause plenty of requests to api endpoint to prepare response even for non-skeetish user. Average user has accounts at least on 3 sites from Stack Exchange network, some has > 10!
Stack Exchange API has request limits:
A single IP address can only make a certain number of API requests per day (10,000).
The API will cut my requests off if I make more than 30 requests over 5 seconds from single IP address.
It's clear that all requests should be throttled to 30 per 5 seconds and currently I've implemented request throttle logic based on a distributed lock with memcached. I'm using memcached as a simple lock manager to coordinate the activity of GAE instances and throttle UrlFetch requests.
But I think it's a big failure to limit such powerful infrastructure to issue no more than 30 requests per 5 sec. Such api request rate does not allow me to continue development of new interesting and useful features and one day it will stop working properly at all.
Now my app has 90 users and growing and I need come up with solution how to maximize request rate.
As known App Engine makes external UrlFetch requests via the same pool of different IP's.
My goal is to write request throttle functionality to ensure compliance with the api terms of usage and to utilize GAE distributed capabilities.
So my question is how-to provide maximum practical API throughput while complying with api terms of usage and utilizing GAE distributed capabilities.
Advise to use another platform/host/proxy is just useless in my mind.
If you are searching a way to programmatically manage Google App Engine shared pool of IPs, I firmly believe that you are out of luck.
Anyway, quoting this advice that is part of the faq, I think you have more than a chance to keep on running your awesome app:
What should I do if I need more
requests per day?
Certain types of applications -
services and websites to name two -
can legitimately have much higher
per-day request requirements than
typical applications. If you can
demonstrate a need for a higher
request quota, contact us.
EDIT:
I was wrong, actually you don't have any chance.
Google App Engine [app]s are doomed.
First off: I'm using your extension and it rocks!
Have you consider using memcached and caching the results?
Instead of taking the results from the API directly, try first to find them on the cache if they are use it and if they are not: retrieve them and cache them and let them expire after X minutes.
Second, try to batch up users requests, instead of asking the reputation of a single user ask the reputation of several users together.