How does AWS Lambda handle scaling automatically?
- By adjusting the number of function instances based on incoming requests
- By increasing the memory allocation of functions
- By limiting the number of requests per function
- By manually configuring scaling policies
AWS Lambda automatically scales by adjusting the number of function instances to match the incoming request volume, ensuring that there are enough resources to handle the workload.
What happens when multiple requests are received simultaneously by an AWS Lambda function?
- AWS Lambda creates separate instances of the function to handle each request concurrently
- AWS Lambda queues the requests and processes them sequentially
- AWS Lambda randomly selects one request to process and discards the rest
- AWS Lambda rejects the additional requests until previous ones are processed
When multiple requests are received simultaneously, AWS Lambda creates separate instances of the function, allowing each request to be processed concurrently without impacting others.
What are some factors affecting the scalability of AWS Lambda functions?
- Concurrent executions
- Function duration
- Memory allocation
- Network bandwidth
The number of concurrent executions allowed for a function can affect its scalability, as high concurrency can lead to resource contention and increased latency.
What is the maximum size limit for a Lambda Layer?
- 1 GB
- 10 GB
- 250 MB
- 50 MB
The maximum size limit for a Lambda Layer is 50 MB, allowing you to include libraries, custom runtimes, and other dependencies.
What strategies can be employed to optimize concurrency and scaling in AWS Lambda?
- Horizontal scaling
- Manual scaling
- Provisioning concurrency
- Vertical scaling
Provisioning concurrency allows you to allocate a set number of execution environments, ensuring consistent performance and reducing cold start times in AWS Lambda.
What are some limitations to consider when designing highly concurrent AWS Lambda applications?
- Account-level concurrency limits
- Cold start latency
- Event source limits
- Resource contention
AWS Lambda imposes account-level concurrency limits, which can restrict the maximum number of concurrent executions across all functions in the account, requiring careful planning and monitoring.
AWS Lambda automatically handles __________, allowing multiple instances of a function to run concurrently.
- Authentication
- Containerization
- Load balancing
- Scaling
AWS Lambda automatically handles scaling, allowing multiple instances of a function to run concurrently.
When designing AWS Lambda functions for high concurrency, it's essential to consider the impact on __________ and resource consumption.
- Cost
- Latency
- Performance
- Security
When designing AWS Lambda functions for high concurrency, it's essential to consider the impact on performance and resource consumption.
AWS Lambda provides __________ concurrency limits per region by default.
- Account-based
- Function-based
- Global
- Region-based
AWS Lambda provides account-based concurrency limits per region by default.
To control concurrency in AWS Lambda, you can set __________ at the function level.
- Execution role
- Memory allocation
- Reserved concurrency
- Timeout duration
Reserved concurrency allows you to limit the number of concurrent executions of a function, helping you control costs and resource utilization in AWS Lambda.