GCP cannot create Managed Notebook on Vertex AI - google-cloud-platform

Using a GCP account that started as free, but does have billing enabled, I can't create a managed notebook and get the following popup error:
Quota exceeded for quota metric 'Create Runtime API requests' and limit 'Create Runtime API requests per minute' of service 'notebooks.googleapis.com' for consumer 'project_number:....'
Navigating to Quotas --> Notebook API --> Create Runtime API requests per minute
Edit Quota: Create Runtime API requests per minute
Current limit: 0
Enter a new quota limit between 0 and 0.
0 doesn't work..
Is there something that I can do, or should have done already to increase this quota?
TIA for any help.

Managed notebooks is still pre-GA and is currently unavailable to the projects with insufficient service usage history.
You can wait for the GA of the service or use a project with more service usage.

Related

GCP Load balancing Quota 'BACKEND_SERVICES' exceeded. Limit: 9.0 globally

Background 1
In my account, the limited of Compute Engine API Backend services is increased to 75.
Background 2
I only have 9 Back-end service in Load balancing
Question
When I try to create a new Load Balancer, I receive below message:
Quota 'BACKEND_SERVICES' exceeded. Limit: 9.0 globally.
Suppose I should have enough quota for creating new backend service.....
Except removing other backend service, any suggestion for fixing this issue?
Thank you in advance!
Sometimes when a quota increase is approved, the deployment of that quota increase does not happen. I have experienced this several times.
My recommendation is to request a higher quota increase and explain the details about the previous quota increase being approved but not being deployed.
As John mentioned, it’s recommended to request a higher quota for backend services, also I share with you the backend services quotas that includes all backend services (INTERNAL, INTERNAL_MANAGED, INTERNAL_SELF_MANAGED, and EXTERNAL) in your project.

Not able to increase Quota for Compute Engine API in GCP

I have been trying to increase Quota for Google Cloud Platform(GCP) Compute Engine API for a Location and it is not allowing me to Edit or Even select the location.
I have tried the same thing before few months back and it was properly working then. I just created a new project and tried the same thing.
I do have the Owner Permission assigned to me.
After concluding that you are in Free Tier, that is part of constraints.
Your free trial credit applies to all Google Cloud resources, with the following exceptions:
You can't have more than 8 cores (or virtual CPUs) running at the same time.
You can't add GPUs to your VM instances.
You can't request a quota increase. For an overview of Compute Engine quotas, see Resource quotas.
You can't create VM instances that are based on Windows Server images.
You must upgrade your account to perform any of the actions in the preceding list.
Upgrading to a paid account:
https://cloud.google.com/free/docs/gcp-free-tier#how-to-upgrade
Free Tier conditions:
https://cloud.google.com/free/docs/gcp-free-tier
Update: To be able to increase Quotas or Submit Quota Increase, you need to:
For New Project need to wait for 48hrs
You need to have Billing Enabled (Enable it by going into top-left gift icon and following along to Enable Billing in GCP)

ERROR: (gcloud.compute.instances.create) Could not fetch resource: - Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally

I would like to try PEGASUS to summarize article.
https://github.com/google-research/pegasus
I followed this instruction.
https://github.com/google-research/pegasus/tree/f76b63c2886748f7f5c6c9fb547456d8c6002562#setup
I checked the region which I can use NVIDIA Tesla V100 and I decided to use us-central1-a
https://cloud.google.com/compute/docs/gpus
I used this command.
gcloud compute instances create pegasustest --zone=us-central1-a
--machine-type=n1-highmem-8 --accelerator type=nvidia-tesla-v100,count=1
--boot-disk-size=500GB --image-project=ml-images --image-family=tf-1-15
--maintenance-policy TERMINATE --restart-on-failure
I got this error message.
ERROR: (gcloud.compute.instances.create) Could not fetch resource:
- The zone 'projects/covid19agent/zones/us-central1-a' does not have enough
resources available to fulfill the request.
Try a different zone, or try again later.
I took 3 hours and tried again, but I got the same result.
So, I changed the region from us-central1-a to asia-east1-c.
I used this command.
gcloud compute instances create pegasustest --zone=asia-east1-c
--machine-type=n1-highmem-8 --accelerator type=nvidia-tesla-v100,count=1
--boot-disk-size=500GB --image-project=ml-images --image-family=tf-1-15
--maintenance-policy TERMINATE --restart-on-failure
Then I got this error message.
WARNING: Some requests generated warnings:
- Disk size: '500 GB' is larger than image size: '10 GB'.
You might need to resize the root repartition manually
if the operating system does not support automatic resizing.
See https://cloud.google.com/compute/docs/disks/add-persistent-disk#resize_pd
for details.
ERROR: (gcloud.compute.instances.create) Could not fetch resource:
- Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally.
Is it impossible for me to try PEGASUS? And, does it cost too much to try PEGASUS?
Let's start with the first issue. Have a look again at the error message:
ERROR: (gcloud.compute.instances.create) Could not fetch resource:
- The zone 'projects/covid19agent/zones/us-central1-a' does not have enough resources available to fulfill the request. Try a different
zone, or try again later.
When you start an instance it requests resources like vCPU, memory, GPU and if there's not enough resources available in the zone you'll get such message, more information available in the documentation:
If you receive a resource error (such as ZONE_RESOURCE_POOL_EXHAUSTED
or ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS) when requesting new
resources, it means that the zone cannot currently accommodate your
request. This error is due to Compute Engine resource obtainability,
and is not due to your Compute Engine quota.
Resource availability are depending from users requests and therefore are dynamic.
There are a few ways to solve this issue:
Wait for a while and try to start your VM instance again (as you tried, but fruitless this time).
Move your instance to another zone (as you did).
Reserve resources for your VM by following documentation to avoid such issue in future:
Create reservations for Virtual Machine (VM) instances in a specific
zone, using custom or predefined machine types, with or without
additional GPUs or local SSDs, to ensure resources are available for
your workloads when you need them. After you create a reservation, you
begin paying for the reserved resources immediately, and they remain
available for your project to use indefinitely, until the reservation
is deleted.
Now, let's have a look at the second issue. Have a look again at this error message:
ERROR: (gcloud.compute.instances.create) Could not fetch resource:
- Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally.
More information about quotas you can find in the documentation.
To solve this issue you should follow steps below:
Ensure that billing is enabled for your project.
Request an increase in quota:
Go to the Quotas page.
In the Quotas page, select the quotas you want to change.
Click the Edit Quotas button on the top of the page.
Check the box of the service you want to edit.
Fill out your name, email, and phone number, and click Next.
Enter your request to increase your quota, and click Next.
Submit your request.
A request to decrease quota is rejected by default. If you must reduce your quota, reply to the support email with an explanation of
your requirements. A support representative from the Compute Engine
team will respond to your request within 24 to 48 hours.
You're not able to request an increase in quota if you use 12-month, $300 free trial because of the limitations:
Your free trial credit applies to all Google Cloud resources, with the
following exceptions:
You can't have more than 8 cores (or virtual CPUs) running at the same time.
You can't add GPUs to your VM instances.
You can't request a quota increase. For an overview of Compute Engine quotas, see Resource quotas.
You can't create VM instances that are based on Windows Server images.
You must upgrade your account to perform any of the actions in
the preceding list.
You can estimate cost of usage with Google Cloud Pricing Calculator.

Not able to create a commitment

When trying to create a commitment
gcloud beta compute commitments create commitment-hyper-gpus-2 --region=europe-west1 --resources=vcpu=16,memory=104 --resources-accelerator=type=nvidia-tesla-p100,count=1 --plan 12-month --reservation=hyper-gpus-p100-2 --reservation-zone=europe-west1-d --machine-type=n1-highmem-16 --accelerator=type=nvidia-tesla-p100,count=1 --vm-count=1
Its giving me the below error.
ERROR: (gcloud.beta.compute.commitments.create) Some requests did not succeed:
- Quota 'COMMITTED_NVIDIA_P100_GPUS' exceeded. Limit: 0.0 in region europe-west1
But, there is no quota with name COMMITTED_NVIDIA_P100_GPUS
You will need to request a quote increase for all GPUs (global).
Make sure that you have setup billing and a payment method
Go to the Google Cloud Console Quotas page: https://console.cloud.google.com/iam-admin/quotas
Under "Metric" select GPUs (all regions). This will limit the number of services displayed.
Select (don't click on) Compute Engine APIs.
Click on "EDIT QUOTAS".
Fill out the form.
Wait to either be contacted or approved or declined.

Autoscaling: Unable to reach resize target for the worker pool in zone us-central1-f

I am running a pipeline using the Apache Beam model in Google Cloud Dataflow but I am unable to scale it up from 8 workers, even though the maximum number of workers is 32.
When I try to run the same pipeline setting the number of workers to 32, it gives me the following warnings:
Autoscaling: Startup of the worker pool in zone us-central1-f reached 30 workers, but the goal was 32 workers. The service will retry. QUOTA_EXCEEDED: Quota 'DISKS_TOTAL_GB' exceeded. Limit: 4096.0
Autoscaling: Unable to reach resize target in zone us-central1-f. QUOTA_EXCEEDED: Quota 'DISKS_TOTAL_GB' exceeded. Limit: 4096.0
But still doesn't pass 8 workers. Is there any particular reasons why a pipeline won't use more than 8 workers?
The problem was quota limits. Google Dataflow uses behind the scenes VMs of Google Compute Engine and their quotas apply. The specific limitation of 8 was being caused by the In use external IP adresses quota limitation. Others quotas were also violated when I tried to scale to 32, like the Disk space. So if anyone is having the same problem I suggest going to IAM Admin > Quotas on the console while the pipeline is running to check which quotas your pipeline may violate.
Also, the logs are different if you run using a deployed template or use the Eclipse plugin to run in debug mode. The later will give much more details than the first.
Visit https://console.cloud.google.com/iam-admin/quotas
Use the filter menu that says Quota type
You can tell by the color of the Current Usage column that API limit has reached limit.
Click Edit Quotas for the API that has exceeded usage and request for new limit. This will take from few hours to day.
Dataflow will use whatever number of workers you can get. In your case, it will reach 30 workers and will use them. It will however retry constantly to reach 32, as quota could be given back by other workflows.