Google Cloud Batch Job Creation Failed: Quota 'IN_USE_ADDRESSES' Exceeded. Limit: 8.0 In Region Us-east5

May 18, 2025 by ADMIN 105 views

**Google Cloud Batch Job Creation Failed: Quota 'IN_USE_ADDRESSES' Exceeded**

Introduction

Google Cloud Batch Jobs provide a scalable and efficient way to run large-scale computations on Google Cloud Platform. However, when creating a batch job, you may encounter quota-related errors, such as the "IN_USE_ADDRESSES" quota exceeded error. In this article, we will discuss the causes and solutions to this issue, focusing on the specific error message: "Quota 'IN_USE_ADDRESSES' exceeded. Limit: 8.0 in region us-east5".

Understanding the Error Message

The error message "Quota 'IN_USE_ADDRESSES' exceeded. Limit: 8.0 in region us-east5" indicates that the number of ephemeral IP addresses available in the us-east5 region has been exceeded. Ephemeral IP addresses are used to assign a temporary IP address to each task in your batch job. The limit of 8.0 in-use addresses per region means that you can only have up to 8 tasks running concurrently in the us-east5 region.

Causes of the Error

There are several reasons why you may encounter this error:

Insufficient Quota: The most common cause of this error is insufficient quota. If you have a large number of tasks running concurrently, you may exceed the available quota of ephemeral IP addresses.
Incorrect Region: If you are running your batch job in a region that has a low quota limit, you may encounter this error.
Incorrect Configuration: If your batch job configuration is not optimized for the available quota, you may exceed the limit.

Solutions to the Error

To resolve the "IN_USE_ADDRESSES" quota exceeded error, you can try the following solutions:

1. Increase the Quota

You can increase the quota by submitting a request to Google Cloud Support. To do this, follow these steps:

Go to the Google Cloud Console and navigate to the "IAM & Admin" section.
Click on "Quotas" and then click on "Request a quota increase".
Fill out the request form and submit it to Google Cloud Support.

2. Optimize Your Batch Job Configuration

To optimize your batch job configuration, you can try the following:

Reduce the Number of Tasks: If you have a large number of tasks running concurrently, try reducing the number of tasks to see if it resolves the issue.
Increase the Region: If you are running your batch job in a region with a low quota limit, try running it in a region with a higher quota limit.
Use a Different IP Address Type: If you are using ephemeral IP addresses, try using reserved IP addresses instead.

3. Use a Different Region

If you are running your batch job in a region with a low quota limit, try running it in a different region. You can do this by modifying your batch job configuration to use a different region.

4. Use a Different IP Address Type

If you are using ephemeral IP addresses, try using reserved IP addresses instead. Reserved IP addresses are not subject to the same quota limits as ephemeral IP addresses.

Example YAML File

Here is an example YAML file that you can use to schedule a batch job:

name: my-batch-job
region: us-east5
zone: us-east5-a
machineType: n1-standard-4
ephemeralStorage: 20GB
maxTasks: 50
maxConcurrentTasks: 25

Conclusion

In conclusion, the "IN_USE_ADDRESSES" quota exceeded error can be caused by insufficient quota, incorrect region, or incorrect configuration. To resolve this error, you can try increasing the quota, optimizing your batch job configuration, using a different region, or using a different IP address type. By following these solutions, you can successfully create and run your Google Cloud batch job.

Additional Resources

For more information on Google Cloud Batch Jobs, please refer to the following resources:

Troubleshooting Tips

Here are some additional troubleshooting tips to help you resolve the "IN_USE_ADDRESSES" quota exceeded error:

Check the Quota Limits: Make sure you have checked the quota limits for your region and adjusted your batch job configuration accordingly.
Check the Batch Job Configuration: Make sure your batch job configuration is optimized for the available quota.
Check the Region: Make sure you are running your batch job in a region with a high quota limit.
Check the IP Address Type: Make sure you are using the correct IP address type for your batch job.

Introduction

In our previous article, we discussed the causes and solutions to the "IN_USE_ADDRESSES" quota exceeded error when creating a Google Cloud batch job. In this article, we will provide a Q&A section to help you better understand the issue and find a solution.

Q: What is the "IN_USE_ADDRESSES" quota?

A: The "IN_USE_ADDRESSES" quota refers to the number of ephemeral IP addresses available in a region. Ephemeral IP addresses are used to assign a temporary IP address to each task in your batch job.

Q: Why do I need to increase the quota?

A: You need to increase the quota because the number of ephemeral IP addresses available in your region has been exceeded. This can happen when you have a large number of tasks running concurrently in your batch job.

Q: How do I increase the quota?

A: To increase the quota, you can submit a request to Google Cloud Support. To do this, follow these steps:

Go to the Google Cloud Console and navigate to the "IAM & Admin" section.
Click on "Quotas" and then click on "Request a quota increase".
Fill out the request form and submit it to Google Cloud Support.

Q: What are the benefits of increasing the quota?

A: Increasing the quota allows you to run more tasks concurrently in your batch job, which can improve performance and reduce processing time.

Q: What are the risks of increasing the quota?

A: Increasing the quota can lead to additional costs, as you will be using more resources to run your batch job.

Q: How do I optimize my batch job configuration?

A: To optimize your batch job configuration, you can try the following:

Reduce the number of tasks running concurrently in your batch job.
Increase the region to a region with a higher quota limit.
Use a different IP address type, such as reserved IP addresses.

Q: What are the benefits of optimizing my batch job configuration?

A: Optimizing your batch job configuration can improve performance, reduce processing time, and reduce costs.

Q: What are the risks of optimizing my batch job configuration?

A: Optimizing your batch job configuration can lead to additional complexity and require more expertise to manage.

Q: How do I use a different region?

A: To use a different region, you can modify your batch job configuration to use a different region. You can do this by changing the region in your batch job YAML file.

Q: What are the benefits of using a different region?

A: Using a different region can improve performance, reduce processing time, and reduce costs.

Q: What are the risks of using a different region?

A: Using a different region can lead to additional complexity and require more expertise to manage.

Q: How do I use a different IP address type?

A: To use a different IP address type, you can modify your batch job to use a different IP address type. You can do this by changing the IP address type in your batch job YAML file.

Q: What are the benefits of using a different IP address type?

A: Using a different IP address type can improve performance, reduce processing time, and reduce costs.

Q: What are the risks of using a different IP address type?

A: Using a different IP address type can lead to additional complexity and require more expertise to manage.