Overview

Choosing between AWS Lambda and EC2 involves understanding the specific requirements and constraints of the application or service you are developing. AWS Lambda, a serverless compute service, allows you to run code in response to events without provisioning or managing servers. This scenario focuses on identifying use cases where AWS Lambda is more advantageous than EC2, highlighting its importance in building scalable, efficient, and cost-effective solutions.

Key Concepts

• Serverless Architecture: Understanding how AWS Lambda fits into the serverless model.
• Event-driven Processing: Recognizing scenarios that benefit from Lambda's event-driven nature.
• Cost Optimization: Comparing the cost implications of using Lambda versus EC2.

Common Interview Questions

Basic Level

1. What is AWS Lambda, and how does it differ from EC2?
2. Can you describe a simple use case where AWS Lambda would be preferable over EC2?

Intermediate Level

3. How does AWS Lambda's pricing compare to EC2 for intermittent workloads?

Advanced Level

4. Discuss a scenario where you would architect a solution using AWS Lambda instead of EC2, considering factors like scalability, cost, and maintenance.

Detailed Answers

1. What is AWS Lambda, and how does it differ from EC2?

Answer: AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources for you. EC2, on the other hand, provides scalable computing capacity in the cloud where you manage the servers. The main difference lies in the management of the compute resources and the scalability model. Lambda abstracts away the server layer entirely, offering a pay-as-you-go model based directly on usage, not reserved capacity.

Key Points:
- AWS Lambda is serverless; EC2 is server-based.
- Lambda manages compute resources automatically; EC2 requires user management.
- Lambda pricing is based on the number of requests and execution time; EC2 pricing is based on server instance size and running time.

Example:

// Example not applicable for conceptual explanation

2. Can you describe a simple use case where AWS Lambda would be preferable over EC2?

Answer: A suitable use case for AWS Lambda over EC2 is a file processing system where files are uploaded to an S3 bucket, and each upload triggers a Lambda function to process the file (e.g., image thumbnail creation, data transformation). This scenario benefits from Lambda due to its event-driven nature, automatic scaling to handle multiple files concurrently without managing servers, and cost savings for the on-demand execution model.

Key Points:
- Event-driven: Lambda functions are ideal for responding to events like S3 uploads.
- Automatic scaling: Lambda can seamlessly scale to handle spikes in file uploads.
- Cost-effective: You pay only for the compute time you consume with no idle capacity.

Example:

// Example of S3 trigger and Lambda function in pseudo C# (AWS SDK for .NET)

public void ProcessUploadedFile(string uploadedFilePath)
{
    // Assume this method is invoked by an AWS Lambda function responding to an S3 upload event
    Console.WriteLine($"Processing file: {uploadedFilePath}");

    // Code to process the file goes here
    // For example, generating a thumbnail for an image
}

3. How does AWS Lambda's pricing compare to EC2 for intermittent workloads?

Answer: For intermittent workloads, AWS Lambda can be significantly more cost-effective than EC2 because you pay only for the compute time you consume (measured in milliseconds) with no charge when your code is not running. In contrast, EC2 instances incur costs as long as they are running, regardless of whether they are being actively used. Lambda's pricing model is advantageous for applications with variable traffic and can lead to substantial cost savings for workloads that do not require continuous server availability.

Key Points:
- Lambda is cost-effective for intermittent, event-driven workloads.
- EC2 costs are based on instance uptime, not usage.
- Lambda's fine-grained billing can lead to savings for sporadic tasks.

Example:

// Cost comparison example in comments

// AWS Lambda: 
// Assuming 1 million requests per month, with each request executing for 1 second on a 512MB function
// Cost = Number of requests * Execution duration * Memory size

// EC2: 
// Assuming a t3.micro instance running 24/7 for a month
// Cost = Instance cost per hour * Hours in a month

4. Discuss a scenario where you would architect a solution using AWS Lambda instead of EC2, considering factors like scalability, cost, and maintenance.

Answer: Consider a real-time data processing system where data is continuously ingested from IoT devices into a Kinesis stream. AWS Lambda can be used to process and analyze this data in real-time, triggering Lambda functions for each data record inserted into the stream. This scenario benefits from Lambda due to its ability to scale automatically with the volume of incoming data, reducing the need for manual intervention and server management. The cost model of Lambda also allows for efficient resource usage, as you pay only for the execution time. This setup minimizes maintenance overhead and operational costs while ensuring the system can handle variable loads efficiently.

Key Points:
- Scalability: Lambda's automatic scaling matches the real-time workload without manual intervention.
- Cost: Paying only for execution time aligns with the sporadic nature of data ingestion, optimizing costs.
- Maintenance: Reduced operational overhead as there's no need to manage or provision servers.

Example:

// Example of processing data from a Kinesis stream with a Lambda function in pseudo C# (AWS SDK for .NET)

public void ProcessDataStreamRecord(KinesisEvent kinesisEvent)
{
    foreach (var record in kinesisEvent.Records)
    {
        Console.WriteLine($"Processing record: {record.Kinesis.PartitionKey}");
        // Add logic to process each record here
        // For example, analyzing IoT device data for anomalies
    }
}