AWS Lambda automatically manages __________ to accommodate varying workloads and optimize resource utilization.
- Billing
- Networking
- Scaling
- Security
AWS Lambda automatically scales to accommodate varying workloads by provisioning the necessary compute resources, optimizing resource utilization, and ensuring efficient cost management.
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.
Scenario: Your team is designing a serverless architecture for a real-time chat application with thousands of concurrent users. What considerations would you make regarding AWS Lambda concurrency and scaling?
- Implement Event Source Mapping
- Monitor and Auto-scale
- Set Appropriate Concurrency Limits
- Use Multi-Region Deployment
Monitoring Lambda functions and enabling auto-scaling based on metrics such as invocation count or latency can dynamically adjust resources to match demand and ensure optimal performance for a real-time chat application with thousands of concurrent users.
Scenario: Your application requires bursty traffic handling, with occasional spikes in concurrent executions. How would you configure AWS Lambda to handle this effectively?
- Adjust Memory Allocation
- Configure Provisioned Concurrency
- Enable Auto Scaling
- Implement Queue-based Processing
Configuring provisioned concurrency in AWS Lambda ensures that a specified number of instances are always available to handle bursts of traffic, reducing cold start delays.
Scenario: You're experiencing performance issues with your AWS Lambda functions due to high concurrency. What steps would you take to diagnose and address the problem?
- Adjust Lambda Memory Allocation
- Analyze CloudWatch Metrics
- Optimize Code Efficiency
- Scale Lambda Concurrency
Analyzing CloudWatch metrics can provide insights into performance issues caused by high concurrency in AWS Lambda functions.
When architecting for high concurrency, it's crucial to design for __________ to ensure efficient resource utilization.
- Microservices architecture
- Monolithic architecture
- Stateful functions
- Stateless functions
Designing functions to be stateless allows them to scale horizontally and efficiently handle high concurrency in AWS Lambda, ensuring optimal resource utilization.
Strategies such as __________ can help mitigate issues related to cold starts and concurrent execution spikes.
- Auto scaling
- Elastic load balancing
- Provisioned concurrency
- Static scaling
Provisioned concurrency allows you to preallocate resources to a function, reducing cold starts and mitigating issues related to concurrent execution spikes in AWS Lambda.
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.
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.
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 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.
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.