AWS Lambda Cost Optimization Fundamentals Quiz Quiz

Explore essential concepts of cost optimization for AWS Lambda, including resource allocation, invocation patterns, monitoring, and best practices. This quiz helps users understand how to manage function costs efficiently and make effective decisions for serverless workloads.

1. Optimize Memory Allocation

   How can you reduce the cost of a Lambda function that is consistently using less than half of its allocated memory?

   1. Enable multi-threading in the function
   2. Add more environment variables
   3. Increase the memory to improve performance
   4. Reduce the memory setting to meet actual usage

   Explanation: Reducing the memory allocation to match actual usage directly lowers function costs since pricing is based on memory and duration. Increasing memory raises costs and is unnecessary if the function does not need more. Adding environment variables does not impact memory allocation or cost. Enabling multi-threading is not supported in all environments and does not affect the pricing structure.

2. Effect of Function Duration on Cost

   Which factor is most directly responsible for increasing the compute charges of a Lambda function when it is invoked frequently?

   1. The duration of function execution
   2. The package size of the function
   3. The function timeout setting
   4. The color of the logging statements

   Explanation: Compute charges are determined by how long the function runs and the amount of memory allocated. The duration is measured from start to finish of each invocation. The package size impacts deployment, not run-time cost. Logging colors do not influence billing. Timeout setting is just a maximum allowable duration, not an actual usage metric.

3. Use of Reserved Concurrency

   Why might setting reserved concurrency on a Lambda function help control costs in a busy system?

   1. It increases the function's speed
   2. It disables logging automatically
   3. It limits the maximum number of concurrent executions
   4. It enables batch processing

   Explanation: By setting a reserved concurrency, you cap the number of simultaneous executions, helping to prevent unplanned spikes in cost. Increasing speed can sometimes increase cost if memory is raised. Reserved concurrency does not enable batch processing or affect logging settings. Batch processing and logging are unrelated to managing function concurrency directly.

4. Efficient Function Packaging

   How does minimizing the package size of a Lambda function positively affect cost optimization?

   1. It halves the function cost regardless of performance
   2. It allows more environment variables to be set
   3. It increases the function timeout value
   4. It reduces cold start latency, which can lower execution duration

   Explanation: Smaller packages load faster, reducing cold start times, which may shorten total execution duration and lower costs. Package size does not halve costs directly and does not change function timeout settings. The size of the package does not impact the number of environment variables you can set.

5. Monitoring for Cost Efficiency

   What’s the primary purpose of monitoring invocation counts and error rates in Lambda functions when aiming to optimize costs?

   1. It enables third-party billing integration
   2. It predicts the weather for deployment days
   3. It helps identify unnecessary or failed executions increasing costs
   4. It changes the billing model automatically

   Explanation: Monitoring these metrics allows you to spot inefficient or failing invocations that could generate excess costs. The billing model cannot be changed by monitoring alone. Monitoring does not provide weather predictions or automatically enable billing integration with third parties.

6. Reducing Costs with Event Filtering

   How does using event source filtering impact AWS Lambda cost for data stream triggers?

   1. It ensures the function is triggered only by relevant events, reducing unnecessary executions
   2. It increases the memory allocation automatically
   3. It doubles the execution time for each event
   4. It requires functions to be written in a specific language

   Explanation: Event source filtering ensures that only relevant events trigger the Lambda, which avoids spending resources on unnecessary invocations. The filtering does not change memory allocation or execution time. Lambda does not force the use of a specific programming language for event filtering.

7. Optimizing Function Code

   Why is it important to write efficient code within Lambda functions when considering cost optimization?

   1. Efficient code disables monitoring
   2. Efficient code changes the function name
   3. Efficient code automatically increases storage size
   4. Efficient code executes faster, reducing billed duration and overall cost

   Explanation: Faster execution means shorter duration and therefore lower charges for each invocation. Efficient code does not affect storage size, monitoring, or function naming. Improving code quality is a direct cost-saving measure.

8. Cost Impact of Function Timeouts

   What is a possible negative cost impact if a Lambda function’s timeout is set much longer than needed?

   1. It doubles the concurrency setting
   2. Longer timeouts directly improve efficiency
   3. Longer timeouts may allow errors or hangs to last longer, causing increased charges
   4. It triggers function versioning automatically

   Explanation: Setting an unnecessarily long timeout can let errors or stuck processes accumulate higher cost before being stopped. Longer timeouts do not improve function efficiency or affect concurrency. Timeout values do not control automatic versioning.

9. Handling Idle Functions

   What is the recommended action for retaining rarely used Lambda functions in terms of cost optimization?

   1. Switch their language to one with shorter durations
   2. Double their memory allocation
   3. Set their timeout to the maximum value
   4. Review and remove unused functions to prevent unwanted invocations

   Explanation: Unused functions can still generate cost if accidentally triggered, so it's best to remove them or disable their triggers. Doubling memory increases potential cost, not savings. Language changes may not impact cost for infrequently run functions. Setting maximum timeout could exacerbate cost if the function is invoked.

10. Choosing the Right Invocation Type

    How can using asynchronous invocation for suitable workloads help optimize Lambda costs?

    1. It decouples processing, allowing for efficient retry and batching to avoid repeated immediate charges
    2. It changes the base price per invocation
    3. It requires double memory allocation
    4. It triggers network isolation automatically

    Explanation: Asynchronous invocation can support batching and retry logic, preventing repeated failed attempts from incurring unnecessary charges. It does not require more memory or change base pricing. Network isolation is not automatically triggered by using asynchronous invocation.