Serverless computing encourages a __________ approach to development, promoting small, focused functions.
- Distributed
- Microservices
- Modular
- Monolithic
Serverless computing promotes a microservices architecture, where applications are composed of small, independent functions that each perform a specific task.
Scenario: You are developing a web application that needs to process user uploads asynchronously. Which AWS service would you choose for this task in a serverless architecture?
- AWS Lambda
- Amazon EC2
- Amazon RDS
- Amazon S3
Amazon S3 is a highly scalable object storage service that can store user uploads securely and reliably, making it suitable for asynchronous processing in a serverless architecture.
In AWS Lambda, what triggers the execution of a function?
- Command-line interface (CLI)
- Events
- Manual invocation
- Scheduled intervals
Events such as changes to data in Amazon S3 or updates to DynamoDB tables trigger the execution of functions in AWS Lambda.
The duration of a cold start in AWS Lambda depends on factors such as __________ and __________.
- AWS region and service integration
- CloudWatch logs and event triggers
- Function size and language runtime
- Network speed and memory allocation
The size of the function package and the chosen language runtime affect the duration of a cold start in AWS Lambda.
AWS Lambda function execution can be optimized through __________ and __________ adjustments.
- Billing options and service quotas
- Language runtime and AWS region
- Memory allocation and timeout
- Network configuration and security settings
Optimizing memory allocation and adjusting timeout settings can improve the performance and efficiency of AWS Lambda functions.
AWS Lambda allocates resources dynamically based on __________ and __________.
- Data size, memory requirements
- Incoming request rate, configured concurrency limits
- Instance types, availability zones
- Time of day, network bandwidth
AWS Lambda dynamically allocates resources based on the incoming request rate and the configured concurrency limits. This allows it to scale automatically to handle varying workloads.
The execution model of AWS Lambda ensures __________ and __________ for functions.
- Fixed resource allocation, high latency
- Manual intervention, resource constraints
- Predictable execution time, low throughput
- Scalability, fault tolerance
AWS Lambda's execution model ensures scalability by automatically scaling resources based on demand and fault tolerance by handling failures transparently.
Scenario: You are designing a real-time data processing system using AWS Lambda. How would you optimize the execution model to handle sudden spikes in incoming data?
- Implement asynchronous processing
- Increase memory allocation
- Reduce function timeout
- Scale concurrency settings
Scaling concurrency settings dynamically allocates resources to match the workload, making it an effective way to handle sudden spikes in incoming data.
Scenario: Your company is considering migrating its existing applications to a serverless architecture. What factors would you consider during the migration planning phase?
- Application architecture, performance requirements, and cost optimization
- Data center location
- Hardware specifications
- Network bandwidth
Factors such as application architecture, performance requirements, and cost optimization should be considered during the planning phase of migrating existing applications to a serverless architecture.
Scenario: You are experiencing unexpected spikes in traffic to your serverless application, causing performance issues. How would you address this scalability challenge?
- Configure auto-scaling policies for AWS Lambda
- Increase instance size for Amazon EC2
- Manually add more servers
- Optimize database queries
Configuring auto-scaling policies for AWS Lambda allows it to automatically scale up or down based on incoming traffic, making it a suitable solution for addressing unexpected spikes in traffic in a serverless application.