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AWS Lambda is a serverless compute service provided by Amazon Web Services (AWS) that allows you to run code without provisioning or managing servers. It automatically scales your application by running code in response to triggers such as changes in data, shifts in system state, or user actions. Lambda is designed to handle various workloads, from simple data processing to complex machine learning models.
When working with AWS Lambda, you might encounter the ThrottlingException
error. This error typically manifests as a message indicating that your request has been throttled due to exceeding the allowed request rate. This can lead to failed executions and disrupted workflows, especially in high-demand applications.
The ThrottlingException
occurs when the number of requests sent to AWS Lambda exceeds the service's configured limits. AWS imposes these limits to ensure fair usage and to protect the service from being overwhelmed. Each AWS account has a default limit on the number of concurrent executions and requests per second, which can vary by region and account settings.
Throttling can occur due to:
To address the ThrottlingException
, consider the following steps:
One of the most effective ways to handle throttling is to implement retry logic with exponential backoff. This approach involves retrying the request after a delay, which increases exponentially with each subsequent retry. Here's a basic example in Python:
import time
import random
max_retries = 5
base_delay = 0.1 # 100ms
for attempt in range(max_retries):
try:
# Your AWS Lambda invocation code here
break
except ThrottlingException:
delay = base_delay * (2 ** attempt) + random.uniform(0, 0.1)
time.sleep(delay)
If your application consistently hits the throttling limits, consider requesting a service limit increase from AWS. You can do this through the AWS Support Center. Provide details about your use case and justify the need for higher limits.
Review your Lambda functions to ensure they are optimized for performance and efficiency. Consider:
Handling the ThrottlingException
in AWS Lambda requires a combination of strategic planning and technical adjustments. By implementing retry logic, requesting service limit increases, and optimizing your functions, you can mitigate the impact of throttling and ensure smoother operation of your serverless applications. For more information, refer to the AWS Lambda Limits Documentation.
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