Understanding and recognizing the appropriate use of different serverless compute options is a critical component of preparing for the AWS Certified Cloud Practitioner (CLF-C02) exam. These options include AWS Fargate and Lambda, among others. This article will outline the purpose of these services and offer scenarios for when and how to use them most effectively.
AWS Lambda
AWS Lambda is a serverless compute service. With Lambda, your applications will not need to provision or manage servers. AWS Lambda executes your code only when needed. In addition, it automatically scales your applications, from thousands of requests per day to thousands per second.
In terms of application structure, AWS Lambda is ideal for microservices, as it enables you to implement your application as loosely coupled, independently scalable, stateless functions. You input triggers, such as changes to data in an Amazon S3 bucket, updates to DynamoDB tables, data streams in Kinesis, or user actions.
An example of appropriate use of AWS Lambda would be implementing a real-time file processing system. For instance, Lambda can be triggered whenever a new file is uploaded to an S3 bucket. Lambda can then process the file, generate thumbnails for images, transcode videos, validate and sanitize data, and any other processing that needs to be done.
AWS Fargate
On the other hand, AWS Fargate is a serverless compute engine for containers. AWS Fargate removes the need to provision and manage servers, allowing you to focus on designing and building your applications. AWS Fargate is compatible with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS).
AWS Fargate is particularly beneficial for workloads that are intermittent and have unpredictable scaling requirements. For example, you may have a batch processing workload that experiences a significant surge in computing needs at the end of every month. With AWS Fargate, you do not need to maintain utilization levels; instead, capacity will be there when it is required.
Comparison
When making a decision between AWS Fargate and Lambda, there are a few key factors to consider:
- Compute Resources: AWS Fargate provides more resources compared to AWS Lambda. AWS Lambda provides up to 10GB of space and six vCPUs, while AWS Fargate offers up to 120GB of space and 4 vCPUs per task, with a maximum of 10 tasks running in parallel per service.
- Runtime: AWS Lambda functions can run for up to 15 minutes, making it ideal for short executions. On the other hand, AWS Fargate is suitable for longer-running jobs, as it does not possess any similar restrictions.
- Pricing: AWS Lambda charges are based on the number of requests and the execution time whereas AWS Fargate charges are based on the vCPU and memory resources consumed.
In conclusion, AWS Fargate and AWS Lambda provide various benefits depending on your compute needs. The primary difference between the two services is the hosting method – serverless or containerized – but they both allow you to have a server management-free experience. While AWS Lambda is ideal for small functions triggered by events, AWS Fargate is better suited for longer-running and resource-intensive applications. Ultimately, the choice between AWS Fargate and AWS Lambda will come down to the needs of your specific workloads, cost and scalability expectations.
Practice Test
True/False: AWS Fargate is a serverless compute engine for containers.
- True
- False
Answer: True
Explanation: AWS Fargate is indeed a serverless compute engine for containers. It works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS).
Single Select: Which AWS service is used for building serverless applications?
- A. AWS Fargate
- B. AWS Lambda
- C. AWS EC2
- D. AWS RDS
Answer: B. AWS Lambda
Explanation: AWS Lambda allows you to run your code without provisioning or managing servers.
True/False: You can use AWS Lambda to automatically scale your applications in response to the incoming request traffic.
- True
- False
Answer: True
Explanation: AWS Lambda automatically scales applications by running code in response to each trigger. Your application is available for processing traffic as soon as it is required.
Multiple Select: Which of the following services are serverless compute options on AWS?
- A. AWS Fargate
- B. AWS Lambda
- C. AWS S3
- D. AWS EC2
Answer: A. AWS Fargate, B. AWS Lambda
Explanation: Both AWS Lambda and AWS Fargate are serverless compute options. AWS S3 is a storage service and AWS EC2 is a compute service but not serverless.
True/False: With AWS Fargate, you can only run applications on Amazon ECS.
- True
- False
Answer: False
Explanation: AWS Fargate can run applications on both Amazon ECS and Amazon EKS (Elastic Kubernetes Service).
Single Select: What type of architecture does AWS Lambda fit best into?
- A. Monolithic
- B. Microservices
- C. Server
- D. Client-server
Answer: B. Microservices
Explanation: AWS Lambda fits best into a microservices architecture, as it allows you to break down your application into small, stateless, and independent functions.
Multiple Select: Which of the following benefits are associated with AWS Fargate and AWS Lambda?
- A. Automatic scaling
- B. No server management
- C. Built-in storage
- D. In-depth access control
Answer: A. Automatic scaling, B. No server management
Explanation: AWS Fargate and AWS Lambda both offer automatic scaling and remove the need to manage servers. However, they do not provide built-in storage and in-depth access control is regulated by other AWS services.
Single Select: Which serverless compute option would be best for an event-driven application?
- A. AWS Fargate
- B. AWS Lambda
- C. AWS EC2
- D. AWS RDS
Answer: B. AWS Lambda
Explanation: AWS Lambda is an event-driven computing service, making it an excellent choice for event-driven applications.
True/False: AWS Lambda functions have a maximum execution time.
- True
- False
Answer: True
Explanation: AWS Lambda functions do have a maximum time limit for execution, which is 15 minutes.
Single select: AWS Fargate eliminates the need to _________.
- A. Choose server types
- B. Scale containers
- C. Provision and manage servers
- D. Both A and C
Answer: D. Both A and C
Explanation: AWS Fargate removes the need to select server types and provision and manage servers, making it simpler to run containerized applications on AWS.
Interview Questions
What is the primary distinction between AWS Fargate and AWS Lambda?
AWS Lambda executes your code only when needed and scales automatically from a few requests per day to thousands per second. While AWS Fargate is a serverless compute engine for containers that eliminates the need to manage the underlying EC2 instances.
Which AWS service is primarily used for executing background tasks?
AWS Lambda is used primarily for executing background tasks.
When should you use AWS Fargate instead of AWS Lambda?
AWS Fargate is ideal for long-running applications, microservices, backend services, data processing, and batch processing, as these applications require a flexible compute capacity.
Are you billed for idle compute time in AWS Fargate and AWS Lambda?
No, both AWS Lambda and Fargate follow a “pay for what you use” billing method where you’re only billed for the time your code runs.
Is it possible to run containers without managing servers or clusters in AWS?
Yes, AWS Fargate lets you run containers without having to manage servers or clusters.
What is the maximum execution time allowed for AWS Lambda?
AWS Lambda allows a maximum execution time of 15 minutes per request.
What is the primary difference between AWS Fargate and AWS EC2?
The primary difference is that you manage the underlying infrastructure with AWS EC2, while with AWS Fargate, Amazon manages it for you, which makes it a serverless solution.
How does AWS Lambda deal with hardware failure?
AWS Lambda automatically retries failed execution and performs health checks to automatically replace failed instances.
Can you run Docker containers on AWS Lambda?
No, Docker containers cannot be run directly on AWS Lambda. Lambda is designed to run code snippets in response to events.
What integrations does AWS Fargate offer?
AWS Fargate integrates with services like Amazon ECS and EKS, allowing you to manage containers at scale.
What is the storage limit for an AWS Lambda function?
AWS Lambda functions have a maximum storage limit of 512 MB in the /tmp directory.
Can you increase the maximum execution time for AWS Lambda functions?
Yes, you can configure the timeout value for a Lambda function to a maximum of 900 seconds (15 minutes).
Does AWS Fargate support persistent storage?
AWS Fargate does not natively support persistent storage. However, it can be implemented through integrations with services like EFS for persistent storage.
What is the maximum size of a deployment package that I can upload to AWS Lambda?
The total unzipped size of the function and all its layers cannot exceed 250 MB.
Can AWS Lambda function connect to an RDS instance?
Yes, it is possible for AWS Lambda function to connect to an RDS instance. However, the RDS instance should be publicly accessible and you should manage connection pooling to ensure maximum performance.
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