Google Cloud Run - FAQ
⚠️ This repository is a community-maintained knowledge base. It does not reflect Google’s product roadmap. Refer to the Cloud Run documentation for the most up-to-date information, as this page may go out of date.
- Is this repo useful? Please ⭑Star this repository and share the love.
- Curious about something? Open an issue, someone may be able to add it to the FAQ.
- Contribute if you learned something interesting about Cloud Run.
- Trouble using Cloud Run? Ask a question on Stack Overflow.
- Check out awesome-cloudrun for a curated list of Cloud Run articles, tools and examples.
- Follow me on Twitter as I frequently share Cloud Run news and tips.
- Basics
- Developing Applications
- Which applications are suitable for Cloud Run?
- What if my application is doing background work outside of request processing?
- Which languages can I run on Cloud Run?
- Can I run my own system libraries and tools?
- Where do I get started to deploy a HTTP web server container?
- How do I make my web application compatible with Cloud Run?
- Can Cloud Run receive events?
- How to configure secrets for Cloud Run applications?
- How can I have cronjobs on Cloud Run?
- Can I mount storage volumes or disks on Cloud Run?
- Deploying
- Cold Starts
- Serving Traffic
- What's the maximum request execution time limit?
- Does my service get a domain name on Cloud Run?
- Are all Cloud Run services publicly accessible?
- How much additional latency does running on Cloud Run add?
- Does my application get multiple requests concurrently?
- What if my application can’t handle concurrent requests?
- How do I find the right concurrency level for my application?
- Can I make request to a specific container instance?
- Can serve Cloud Run services with Cloud HTTP(S) Load Balancer?
- How can I configure CDN for Cloud Run services?
- Does Cloud Run offer SSL/TLS certificates (HTTPS)?
- How can I redirect all HTTP traffic to HTTPS?
- Is traffic between my app and Google’s load balancer encrypted?
- Is HTTP/2 supported on Cloud Run?
- Is gRPC supported on Cloud Run?
- Are WebSockets supported on Cloud Run?
- Autoscaling
- Runtime
- Which operating system Cloud Run applications run on?
- Can I use the local filesystem?
- Which system calls are supported?
- Which executable ABIs are supported?
- What happens if my container exits/crashes?
- What is the termination signal for Cloud Run services?
- Where can I find the "instance ID" of my container?
- How can I find the number of instances running?
- How can my service can tell it is running on Cloud Run?
- Is there a way to get static IP for outbound requests?
- Monitoring and Logging
- Pricing
Cloud Run is a service by Google Cloud Platform to run your stateless HTTP containers without worrying about provisioning machines, clusters or autoscaling.
With Cloud Run, you go from a "container image" to a fully managed web application running on a domain name with TLS certificate that auto-scales with requests in a single command. You only pay while a request is handled.
GAE Flexible and Cloud Run are very similar. They both accept container images as deployment input, they both auto-scale, and manage the infrastructure your code runs on for you. However:
- GAE Flexible is built on VMs, therefore is slower to deploy and scale.
- GAE Flexible does not scale to zero, at least 1 instance must be running.
- GAE Flexible billing has 1 minute granularity, Cloud Run in 0.1 second.
- GAE Flexible supports Websockets in beta, unlike Cloud Run.
Read more about choosing a container option on GCP.
GCF lets you deploy snippets of code (functions) written in a limited set of programming languages, to natively handle HTTP requests or events from many GCP sources.
Cloud Run lets you deploy using any programming language, since it accepts container images (more flexible, but also potentially more tedious to develop). It also allows using any tool or system library from your application (see here) and GCF doesn’t let you use such custom system executables.
Cloud Run can only receive HTTP requests or Pub/Sub push events. (See this tutorial).
Both services auto-scale your code, manage the infrastructure your code runs on and they both run on GCP’s serverless infrastructure.
Read more about choosing between GCP's serverless options
AWS Fargate and Cloud Run both let you run containers without managing the underlying infrastructure.
- Fargate can run a wide range of container workloads, including but not limited to HTTP servers, background or long running tasks.
- Fargate requires an ECS cluster to run tasks on. This cluster doesn't expose the underlying VM infrastructure to you. However, while using Fargate, you still need to configure infrastructure aspects like VPCs, subnets, load balancers, auto-scaling, health checks and service discovery.
- Fargate also has a fairly more complex resource model than Cloud Run, it doesn't allow request-based autoscaling, scale-to-zero, concurrency control, and it exposes container instances and their lifecycle to you.
Cloud Run is a standalone compute platform, abstracting cluster management and focusing on fast automatic scaling. Cloud Run supports running only HTTP servers, and therefore can do request-aware autoscaling, as well as scale-to-zero.
The pricing model is also different:
- On Cloud Run, you only pay while a request is being handled.
- On AWS Fargate, you pay for CPU/memory while containers are running, and since Fargate doesn't support scale-to-zero, a service receiving no traffic will still incur costs.
Azure Container Instances and Cloud Run both let you run containers without managing the underlying infrastructure (VMs, clusters). Both ACI and Cloud Run give you a publicly accessible endpoint after deploying the application.
Cloud Run supports running only HTTP servers and offers auto-scaling, and scale to zero. ACI is for long-running containers. Therefore, the pricing model is different. On Cloud Run, you only pay while a request is being handled.
"Cloud Run on Anthos" gives you the same Cloud Run experience on your Kubernetes clusters on Anthos (either on GCP with GKE, or on-prem/other clouds). This gives you the freedom to choose where you want to deploy your applications.
"Cloud Run" and "Cloud Run on Anthos" are the same product, but running in different places:
- the same application format (container images)
- the same deployment/management experience (
gcloudor Cloud Console) - the same API (Knative serving API).
Look at this diagram, or watch this video to decide how to choose between the two.
Cloud Run on Anthos basically installs and manages a Knative installation (with some additional GCP-specific components for monitoring etc) on your Kubernetes cluster so that you don’t have to worry about installing and managing Knative yourself.
Sort of.
Cloud Run implements most parts of the Knative Serving API. However, the underlying implementation of the functionality could differ from the open source Knative implementation.
With Cloud Run on Anthos, you actually get a Knative installation (managed by Google) on your Kubernetes/GKE cluster
Cloud Run is designed to run stateless request-driven containers.
This means you can deploy:
- publicly accessible applications: web applications, APIs or webhooks
- private microservices: internal microservices, data transformation, background jobs, potentially triggered asynchronously by Pub/Sub events or Cloud Tasks.
Other kinds of applications may not be fit for Cloud Run.
If your application is doing processing while it’s not handling requests or storing in-memory state, it may not be suitable.
Your application’s CPU is significantly throttled nearly down to zero while it's not handling a request.
Therefore, your application should limit CPU usage outside request processing to a minimum. It might not be entirely possible since the programming language you use might do garbage collection or similar runtime tasks in the background.
If an application can be packaged into a container image that can run on Linux (x86-64), it can be executed on Cloud Run.
Web applications written in languages like Node.js, Python, Go, Java, Ruby, PHP, Rust, Kotlin, Swift, C/C++, C# can work on Cloud Run.
🍄 Users managed to run web servers written in x86 assembly, or 22-year old Python 1.3 on Cloud Run.
Yes, see the section above. Since Cloud Run accepts container images as the
deployment unit, you can add arbitrary executables (like grep, ffmpeg,
imagemagick) or system libraries (.so, .dll) to your container image and
use them in your application.
See this tutorial
using Graphviz dot that generates PNG diagrams.
See Cloud Run Quickstart which has sample applications written in many languages.
Your existing applications must listen on PORT environment variable to work
on Cloud Run (see container contract). (This value is
currently only 8080, but it may change in the future.)
If your existing application doesn't allow you to configure port number it
listens on, Cloud Run currently doesn't allow customizing the PORT value.
Yes.
Cloud Run integrates securely with Pub/Sub push subscriptions:
- Events are delivered via HTTP to the endpoint of your Cloud Run service.
- Pub/Sub automatically validates the ownership of the
*.run.appCloud Run URLs - You can leverage Pub/Sub push authentication to securely and privately push events to Cloud Run services, without exposing them publicly to the internet.
Many GCP services like Google Cloud Storage are able to send events to a Pub/Sub topic. You can publish your own events to a Pub/Sub topic and push them to a Cloud Run service.
Follow this tutorial for instructions about how to push Pub/Sub events to Cloud Run services.
You can use Secret Manager with Cloud Run. Read how to write code and set permissions to access the secrets from your Cloud Run app in the documentation.
Alternatively, if you'd like to store secrets in Cloud Storage (GCS) using Cloud KMS envelope encryption, check out the Berglas tool and library (Berglas also has support for Secret Manager).
If you need to invoke your Cloud Run applications periodically, use Google Cloud Scheduler. It can make a request to your application’s specific URL at an interval you specify.
Cloud Run currently doesn’t offer a way to bind mount additional storage volumes
(like FUSE, or persistent disks) on your filesystem. If you’re reading
data from Google Cloud Storage, instead of using solutions like gcsfuse, you
should use the supported Google Cloud Storage client libraries.
However, Cloud Run on GKE allows you to mount Kubernetes Secrets and ConfigMaps, but this is not yet fully supported. See an example here about mounting Secrets to a Service running on GKE.
(If you know of articles about other CI/CD system integrations, add them here.)
For other CI/CD systems, roughly the steps you should follow look like:
-
Create a new service account with a JSON key.
-
Give the service account IAM permissions to deploy to Cloud Run.
-
Upload the JSON key to the CI/CD environment, and authenticate to
gcloudby calling:gcloud auth activate-service-account --key-file=[KEY_JSON_FILE] -
Deploy the app by calling:
gcloud beta run deploy [MY_SERVICE] --image=[...] [...]
Cloud Run currently only allows deploying images hosted on Google Container
Registry (*.gcr.io/*).
If you're deploying from GCR registries on another GCP project:
- public registries: should be deploying without additional configuration
- private registries: need to give GCR access to service account used by Cloud Run.
To give access, go to IAM&Admin on Cloud Console, and find the email for "Google Cloud Run Service Agent". Then follow this document to give this service account GCR access on the other project.
If you updated your Cloud Run service, you probably realized it creates a new revision for every new configuration of your service.
However, Cloud Run (currently) only supports serving traffic from the last healthy revision of your service. Therefore, it currently does not support revision based traffic splitting and canary deployments.
This is subject to change soon. See also issue 144717649.
For applications running on Cloud Run, you don't need to deliver JSON keys for
IAM Service Accounts, or set GOOGLE_APPLICATION_CREDENTIALS environment
variable.
Just specify the service account (--service-account) you want your application
to use automatically while deploying the app. See configuring service
identity.
Cloud Run supports the Knative Serving API. However, currently some
parts of Kubernetes Discovery API required by kubectl are not yet offered on
Cloud Run API.
As a solution, you can write your Knative Service resource as a .yaml
file and use the following command to deploy to Cloud Run:
gcloud beta run services replace --platform=managed <file.yaml>Since "Cloud Run on Anthos" runs Knative natively, you can use
kubectl to deploy Knative Services to your GKE cluster by writing YAML
manifests and running kubectl apply. See Knative tutorials for more info.
Yes. If a Cloud Run service does not receive requests for a long time, it will take some time to start it again. This will add additional delay to the first request.
Cold start latency depends on many factors, however many users observe additional ~2 seconds latency on cold starts. [more user data needed!]
Cloud Run does not provide any guarantees on how long it will keep a service "warm". It depends on factors like capacity and Google’s implementation details.
Some users see their services staying warm up to an hour, or longer. [more user data needed!]
See performance optimization tips, basically:
- minimize the number and size of the dependencies that your app loads
- keep your app’s "time to listen for requests" startup time short
- prevent your application process from crashing
(The size of your container image has almost no impact on cold starts).
Cloud Run does not have the notion of App Engine warmup requests. You can perform initialization of your application (such as loading data) until you start listening on the port number.
Note that delaying the listening on the port number causes longer cold starts, so consider lazily computing/fetching the data you need to reduce cold start latencies.
You can work around "cold starts" by periodically making requests to your Cloud Run service which can help prevent the container instances from scaling to zero.
Use Google Cloud Scheduler to make requests every few minutes.
UPDATE: Cloud Run no longer marks request logs with information about whether they caused a cold start or not.
Each request to Cloud Run services is logged to Stackdriver logging, with an
indicator whether instance was "warm" or "cold" during that request (see
Viewing Logs).
If you view logs from Cloud Run console, these requests are marked (and if you
view them in Stackdriver Logging, you can see the structured log label
indicating "cold" request):
Currently, a request times out after 15 minutes. See limits.
Yes, every Cloud Run service gets a *.run.app domain name for free. You can
also use your domain names.
No. Cloud Run allows services to be either publicly accessible to anyone on the Internet, or private services that require authentication.
TODO(ahmetb): Write this section. Ideally we should link to some blog posts doing an analysis of this.
Contrary to most serverless products, Cloud Run is able to send multiple requests to be handled simultaneously to your container instances.
Each container instance on Cloud Run is (currently) allowed to handle up to 80 concurrent requests. This is also the default value.
If your application cannot handle this number, you
can configure this number while deploying your service in gcloud or Cloud
Console.
Most of the popular programming languages can process multiple requests at the same time thanks to multi-threading. But some languages may need additional components to do concurrent requests (e.g. PHP with Apache, or Python with gunicorn).
Each application and language can process different levels of simultaneously without having them time out. That's why Cloud Run allows you to configure concurrency per service.
You should do "load testing" to find out where your application should stop handling additional request and additional instances should be created. Read Tuning concurrency for more.
No, Cloud Run does not offer a "sticky session" primitive. All requests are load balanced between available container instances.
Currently, you can’t route traffic to Cloud Run services via the Cloud HTTP(S) Load Balancer (a.k.a. GCLB) yet.
Therefore many features only available on Load Balancers are not yet available for Cloud Run applications (e.g. CDN, IAP, Cloud Armor, URL Maps...).
Since you can’t use Cloud HTTP(S) Load Balancer with Cloud Run, you cannot use Cloud CDN.
However, you can have CDN from Firebase Hosting by:
- responding to requests with a
Cache-Controlheader, and - configuring a rewrite configuration in
firebase.jsonof your Firebase app.
Yes. If you’re using the domain name provided by Cloud Run (*.run.app), your
application is immediately ready to serve on https:// protocol.
If you’re using your own custom domain name, Cloud Run provisions a TLS
certificate for your domain name. This may take ~15 minutes to provision and
serve traffic on https://. Cloud Run uses Let’s
Encrypt to get a certificate for your domains.
This is built in and required. To make Cloud Run secure by default, Cloud Run services will only be accessible via HTTPS.
Any HTTP requests are automatically returned an HTTP 302 response pointing to the HTTPS version of the current URL. This was rolled out as a change in the beta service in August 2019.
Since your app serves traffic on PORT (i.e. 8080) unencrypted, you might think
the connection between Google’s load balancer and your application is
unencrypted.
However, the transit between Google’s frontend/load balancer and your Cloud Run container instance is encrypted. Google terminates TLS/HTTPS connections before they reach your application, so that you don’t have to handle TLS yourself.
Yes. If you query your application with https://, you should be seeing HTTP/2
protocol used:
$ curl -v https://<url>
...
< HTTP/2 200
...
Cloud Run supports unary calls on gRPC. Streaming RPCs are not yet supported.
Since Cloud Run on GKE runs on GCE networking stack, gRPC works natively on that platform.
WebSockets are currently not supported on Cloud Run fully managed.
However, running WebSockets currently works on Cloud Run on Anthos because of its GCE-based native networking layer.
Yes. When your service is not receiving requests, you are not paying for anything.
Therefore, after not receiving any requests for a while, the first request may observe cold start latency.
By setting the Maximum number of instances parameter when deploying a new revision.
Each Cloud Run service can scale by default up to 1000 container instances, a limit that can be increase via a quota request. Each container instance can handle up to 80 simultaneous requests.
Linux.
However, since you bring your own container image, you get to decide your system libraries like libs (e.g. musl libc in alpine, or glibc in debian based images).
Your applications run on gVisor which only supports Linux (currently).
Yes, however files written to the local filesystem count towards available memory and may cause container instance to go out-of-memory and crash.
Therefore, writing files to local filesystem are discouraged, with the exception
of /var/log/* path for logging.
Cloud Run applications run on gVisor container sandbox, which executes Linux kernel system calls made by your application in userspace.
gVisor does not implement all system calls (see
here). If your app
has such a system call (quite rare), it will not work on Cloud Run. Such an
event is logged and
you can use
strace
to determine when the system call was made in your app.
Applications compiled for 64-bit Linux are supported. To be precise, ELF executables compiled to x84-64. See Container Contract.
If the entrypoint process of a container exits, the container is stopped. A crashed container triggers cold start while the container is restarted. Avoid exiting/crashing your server process by handling exceptions. See development tips.
Currently, Cloud Run terminates containers while scaling to
zero with unix signal 9 (SIGKILL).
SIGKILL is not trappable (capturable) by applications. Therefore, your
applications should be okay to be killed abruptly.
The logs collected from a container instance specify the unique instance ID of the container when the logs are viewed on Stackdriver Logging. This instance ID is not made available to the application.
To identify your container instance while it’s running, generate a random UUID during the startup of your process and store it in a variable.
You can't see the number of instances running at a time on Cloud Run.
However, you can use the Billable container instance time metric on Cloud Run service dashboard to infer this information.
Ideally you should not care about "instant value" of number of instances in a serverless world, since your applications autoscale based on traffic patterns better and you only pay while a request is being handled (not the idle instance time).
Cloud Run provides some environment variables standard in Knative. Ideally you should explicitly deploy your app with an environment variable indicating it is running on Cloud Run.
You can also access instance
metadata
endpoints like
http://metadata.google.internal/computeMetadata/v1/project/project-id to
determine if you are on Cloud Run. However, this will not distinguish "Cloud
Run" vs "Cloud Run on Anthos" as the metadata service is available on GKE nodes as
well.
Since, currently Cloud NAT or Serverless VPC Connector are not supported on Cloud Run, your applications will not get a static IP for outbound connections.
However, there is a workaround to route the traffic through a Google Compute Engine instance by running a persistent SSH tunnel inside the container and making your applications use it.
Anything your application writes to standard output (stdout) or standard error (stderr) is collected as logs by Cloud Run.
Some existing apps might not be complying with that (e.g. nginx writes logs to
/var/log/nginx/error.log). Therefore any files written under /var/log/* are
also aggregated. Learn more here.
All your log lines must be JSON objects with fields recognized by Stackdriver
Logging,
such as timestamp, severity, message.
Yes. See this document on how to view various metrics about your Cloud Run container instances.
TODO(ahmetb): Write this section.
Cloud Run Pricing documentation has the most up-to-date information.
Yes! See Pricing documentation.
You only pay while a request is being handled on your container instance.
This means an application that is not getting traffic is free of charge.
Based on "time serving requests" on each instance. If your service handles multiple requests simultaneously, you do not pay for them separately. (This is a cost saver!)
Each billable timeslice is rounded up to the nearest 100 milliseconds.
Read how the billable time is calculated, it is basically like this:
request1 response1
| request2 ʌ response2
| | | ʌ
v........|......./ |
| |
v.............../
|-----FREE-----|----------BILLED----------|----FREE...
You are paying for CPU, memory and the traffic sent to the client from your application (egress traffic).
This is not an official Google project or roadmap. Refer to the Cloud Run documentation for the authoritative information. This project is licensed under Creative common Attribution 4.0 International (CC BY 4.0) license.
Your question not answered here? Open an issue and see if we can answer.