AWS Lambda has resource limits in place to ensure fair usage and efficient management of serverless functions. These limits can affect the behavior of Lambda functions. The default resource limits for AWS Lambda:
1. Execution Duration: The maximum execution duration per Lambda function invocation is 15 minutes (900 seconds). If a function execution exceeds this limit, it will be terminated automatically, and any unprocessed work may be lost.
2. File Descriptor Counts: Each Lambda function execution environment has a maximum limit on the number of file descriptors it can open. This limit is typically 1,024 file descriptors. This limit can affect functions that require opening and managing many file descriptors, such as network connections, file I/O, or other resource handles. If a function exceeds this limit, it may encounter resource constraints and fail to open additional file descriptors.
3. Ephemeral Disk:
* Each Lambda execution environment includes a small amount of ephemeral disk storage, which is used for temporary file storage. The amount of ephemeral disk storage varies by the execution environment but is generally limited to around 512 MB.
* Functions can use this storage for temporary data, such as caches or intermediate processing results. However, this storage is not suitable for permanent data storage.
* The contents of the ephemeral disk are only available during the lifetime of a single function invocation. Subsequent invocations may run in different environments with different ephemeral disks, so data stored there will not persist across invocations.

These default resource limits are in place to ensure that Lambda functions are responsive, scalable, and efficient. Functions should be designed to work within these constraints. If a function requires more resources or longer execution times, you may need to consider alternative AWS services or approaches.
It's important to note that AWS may change these limits over time, and the specific limits may vary by AWS region. To check the current resource limits for Lambda in your region, refer to the official AWS documentation or AWS Management Console.
To mitigate the impact of resource limits, consider the following best practices:
* Optimize code and design to minimize resource usage, such as limiting file descriptor usage and efficient memory management.
* Use external storage services (e.g., Amazon S3, Amazon RDS, or DynamoDB) for persistent data storage.
* Implement error handling and retries to account for potential execution duration limits.
* Monitor function execution and adjust the function's resource configuration if necessary.
* Stay informed about AWS updates and announcements regarding Lambda resource limits.