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Serverless Computing

5 minutes 5 Questions

Serverless computing, also known as Function as a Service (FaaS), is a cloud computing model that abstracts away infrastructure management, allowing developers to focus on writing and deploying application code. In serverless computing, the cloud provider automatically provisions, scales, and manages the infrastructure required to run the application code in response to events or triggers. The term 'serverless' is somewhat misleading since servers are still involved; however, the cloud provider handles all server management, and users are not required to manage or allocate resources directly. Serverless computing is ideal for event-driven architectures, where applications can execute code in response to events like file uploads, incoming messages, or database modifications. The serverless model helps to reduce operational complexity, improve resource utilization, and allows developers to build applications more efficiently by leveraging third-party services and microservices.

Guide to Serverless Computing

What is Serverless Computing:
Serverless computing is a cloud computing model where the cloud provider dynamically provisions and manages the backend infrastructure. Developers can focus on their core product instead of managing servers or runtimes. The provider charges based on the actual computation performed, not pre-purchased capacity.

Why is Serverless Computing important:
Serverless computing is important because it allows developers to focus on their application logic rather than infrastructure. It provides automatic scaling, operational flexibility, increased efficiency, and reduces operational costs.

How Serverless Computing works:
In serverless computing, the cloud provider runs the server and dynamically manages the allocation of machine resources. Developers deploy their code and the cloud provider executes the function only when needed, scaling up to meet the demand of incoming requests.

Exam Tips: Answering Questions on Serverless Computing:
Understand the main concept of serverless computing, its benefits, and how it works. Learn key terms related to serverless computing like Function as a Service (FaaS) and Backend as a Service (BaaS). Remember that serverless computing is not suitable for long-running applications as it is event-driven. Understand the difference between traditional cloud hosting and serverless computing. Be able to discuss scenarios where serverless computing is applicable.

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CompTIA Network+ - Virtualization and Cloud Computing Example Questions

Test your knowledge of Amazon Simple Storage Service (S3)

Question 1

You are a system administrator and your developers create an image processing application using AWS Lambda. However, they report slow processing times. What should you do to improve the performance?

Correct Answer: Increase memory allocation for the Lambda function

The performance of AWS Lambda functions is directly tied to the amount of memory that you allocate to them. When you increase memory, CPU power, network bandwidth and disk I/O will proportionally increase as well. Hence, increasing the memory allocation will speed up the image processing of the Lambda function, addressing the slow performance issue. On the other hand, adding more EC2 instances or creating a bigger S3 bucket doesn't directly impact the performance of a Lambda function as they are separate AWS services. Changing the programming language also isn't generally a quick or effective solution for performance issues as they normally depends on the design pattern or the correct utilization of AWS resources.

Question 2

A company is implementing a serverless application for image processing. What is the best approach to limit the number of requests that could impact the cost management?

Correct Answer: Implement API Gateway and set request throttling limits

'Implement API Gateway and set request throttling limits' is the best approach for handling the cost management of a serverless application for image processing. API Gateway provides throttling rules to manage the rate of incoming requests to prevent your backend from being overwhelmed, which can help manage costs by limit the number of processed requests. This approach allows you to manage the load on your infrastructure without the need to manually intervene every time there's a spike in requests. 'Use manual intervention to control the requests' would consume substantial resources and time and also would not be practical in real time scenarios. 'Remove IAM role permissions' would not be suitable because it might disrupt other processes which use the same permissions. 'Reduce the number of AWS Lambda Functions' could possibly impact the overall function of the serverless application as Lambda Functions are isolated computational units that enable the application to function in a distributed manner.

Question 3

A software company is developing an API using serverless computing. They need to securely manage query parameters passed to their API functions. What is the best method for handling query parameters securely?

Correct Answer: Use AWS API Gateway to validate query parameters before invoking serverless functions.

The best method for securely handling query parameters in a serverless API is to use AWS API Gateway to validate the parameters before invoking the serverless functions. API Gateway provides built-in features for request validation, allowing you to define validation rules for query parameters. This ensures that only valid and expected parameters are passed to the serverless functions, reducing the risk of injection attacks or unexpected behavior. Parsing query parameters directly in the function can be insecure if proper validation and sanitization are not implemented. Storing query parameters in environment variables is not a secure approach as they can be accessed by other functions or compromised. Using a custom authentication provider to validate query parameters adds complexity and may not provide the same level of built-in validation capabilities as API Gateway.

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