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Function Compute (2.0):Limits

Last Updated:Feb 20, 2024

This topic describes limits on usage of Function Compute resources, such as service resources, function resources, triggers, layers, regions, image sizes, and the number of GPU cards.

Important

This topic helps new users have a clear understanding of function principles and prevent unexpected costs incurred due to incorrect configurations or code errors, such as cyclical invocations and infinite loops. If you want to increase the limits on resources, join the DingTalk group 11721331 for technical support. Only resources whose quota is adjustable, as described in the following tables, can be adjusted.

If provisioned function instances are not properly used under the resource limits, unexpected costs may surge. For more information, see Instance types and usage modes.

Resource limits on services

Item

Limit

Adjustable

Functions per service

50

Yes

Apsara file storage NAS (NAS) mount targets per service

5

No

Object Storage Service (OSS) mount targets per service

5

No

Resource limits on function execution

Item

Limit (elastic instances)

Limit (GPU-accelerated instances)

Adjustable

Temporary disk space

10 GB

10 GB

No

File descriptor

100000

100000

No

Total processes and threads

1024

1024

No

Memory for a function

32 GB

32 GB

No

Function execution duration

86400s

86400s

No

Execution duration for an Initializer hook

300s

300s

No

Maximum running time of a PreFreeze hook

90s

90s

Supported

Maximum running time of a PreStop hook

90s

90s

Supported

Request payload size of a synchronous invocation

32 MB

32 MB

No

Request payload size of an asynchronous invocation

128 KB

128 KB

No

Code package size (ZIP or JAR file)

500 MB

N/A

Yes

Bandwidth

1 Gbit/s to 5 Gbit/s

1 Gbit/s to 5 Gbit/s

No

Size of a log entry

32 KB

32 KB

No

Trigger limits

Item

Limit

Adjustable

Triggers per function

10

Yes

Number of native OSS triggers that can be created for a bucket

10

No

Number of EventBridge-based OSS triggers that can be created for a bucket

50

Yes

Limits on layers

Item

Limit (elastic instances)

Limit (GPU-accelerated instances)

Adjustable

Layer size

500 MB

500 MB

Yes

Layer versions

100

100

Yes

Layers for a single function

5

5

Yes

Total size of layers for a single function

2 GB

2 GB

Yes

Limits on resources for an account per region

Item

Limit

Adjustable

On-demand instances

300

Yes

Concurrently-processed requests per instance

1~200

No

Limits on sizes of instance images

Instance type

Limit

Adjustable

CPU image size

10 GB of compressed images (about 20 GB of uncompressed Docker images)

Yes

GPU image size

15 GB of compressed images (about 28 GB of uncompressed Docker images)

Yes

Limits on GPUs

Item

Limit

Adjustable

Physical GPUs per region

Note

GPU-accelerated instances in Function Compute can be configured with GPU cards of NVIDIA Tesla T4 or NVIDIA Ampere A10.

30

Yes

Relationship between GPU-accelerated instance types and instance concurrency

  • NVIDIA Tesla T4 and 2 GB GPU memory

    • If the concurrency of GPU-accelerated instances in a region is set to 1, eight containers can simultaneously run on each physical GPU, and 240 containers can simultaneously run on all physical GPUs in the region. A GPU-accelerated instance can concurrently process 240 inference requests in the region.

    • If the concurrency of GPU-accelerated instances in a region is set to 5, 8 containers can simultaneously run on each physical GPU, and 240 containers can simultaneously run on all physical GPUs in the region. A GPU-accelerated instance can concurrently process 1200 inference requests in the region.

  • NVIDIA Ampere A10 and 2 GB GPU memory

    • If the concurrency of GPU-accelerated instances in a region is set to 1, 12 containers can simultaneously run on each physical GPU, and 360 containers can simultaneously run on all physical GPUs in the region. A GPU-accelerated instance can concurrently process 360 inference requests in the region.

    • If the concurrency of GPU-accelerated instances in a region is set to 5, 12 containers can simultaneously run on each physical GPU, and 360 containers can simultaneously run on all physical GPUs in the region. A GPU-accelerated instance can concurrently process 1800 inference requests in the region.

Limits on accessing other Alibaba Cloud services or resources

If Function Compute in your region is allowed to access resources in virtual private clouds (VPCs), the following limits on networks apply when your functions call other Alibaba Cloud services and resources:

  • You cannot access the resources, such as web services and file systems, on an Elastic Compute Service (ECS) instance by using the internal IP address of the instance in the classic network. You must use the public IP address of the instance to access the resources or migrate the resources to a VPC.

  • You cannot use the internal IP address in the classic network to access an ApsaraDB RDS instance. You must use the public IP address to access an ApsaraDB RDS instance or migrate the ApsaraDB RDS instance to a VPC.

  • You cannot access an Alibaba Cloud service by using its internal endpoints. You must use a VPC endpoint or a public endpoint that is provided by the Alibaba Cloud service.