Serverless technologies have become increasingly popular in the tech world due to their scalability, efficiency, and cost-effectiveness. Two major offerings from Amazon Web Services (AWS) that represent this trend are AWS Fargate and AWS Lambda. They both offer serverless computing but in different modes. In this post, we will delve into these technologies, their patterns and how they contribute to the working knowledge required for the AWS Certified Solutions Architect – Associate (SAA-C03) exam.

Table of Contents

AWS Lambda

AWS Lambda is a compute service that lets you run the code without provisioning or managing servers. It automatically scales your application based on the incoming traffic and you only pay for the compute time that you use. This includes automatic load balancing, high availability, and failover, making it a preferred choice for most developers.

A typical Lambda use case includes real-time file processing (as soon as images or videos are uploaded to AWS S3, Lambda can process them), real-time stream processing (processing Kinesis or DynamoDB data streams), and extract, transform, load (ETL) jobs.

Lambda integrates with AWS CloudWatch Logs for log streaming. You can debug your lambda functions using AWS X-Ray which provides an end-to-end real-time view of your application.

Lambda works on an Event-Driven Model. An incoming event triggers the execution of your Lambda Functions. Following code snippet written in Python provides a basic understanding of how Lambda function works:

import json

def lambda_handler(event, context):
print(‘Event Received: ‘ + json.dumps(event, indent=2))
return {
‘statusCode’: 200,
‘body’: json.dumps(‘Hello from Lambda!’)

In the above code, `lambda_handler` is the entry point of the Lambda Function. The `event` parameter includes information about the triggering event and `context` parameter includes the runtime information.

AWS Fargate

AWS Fargate simplifies the management of Kubernetes or Amazon ECS environments by allowing you to focus on building and running applications, rather than the underlying infrastructure. With Fargate, you don’t need to provision, configure, and scale clusters of virtual machines to run containers.

A good usage scenario for Fargate would include microservices where each microservice runs in its container, batch processing where jobs start and end automatically, and hybrid cloud solutions allowing for on-premises and public cloud integrations.

Fargate integrates with AWS CloudWatch for logging purposes and supports container health checks and load balancing for better traffic management.

Comparison between AWS Lambda and AWS Fargate

Parameter AWS Lambda AWS Fargate
Execution Model Event-driven Long-running process
Use Case Real-time file/stream processing, ETL jobs Microservices, Batch processing, Hybrid solutions
Billing Pay only for the compute time Pay for the provisioned storage and compute resources
Management Fully managed Management of underlying infrastructure is abstracted
Execution Duration Max 15 minutes No maximum limit
Scaling Automatic Manual/Automatic (With Auto-scaling groups)

In conclusion, serverless architectures deliver significant benefits by abstracting away infrastructure management, allowing developers to focus solely on the application logic. Both AWS Lambda and AWS Fargate come with their strong points and their use depends largely on the nature and requirements of the application you are developing. Understanding these technologies is integral to the AWS Certified Solutions Architect – Associate (SAA-C03) exam, and would enable you to make more informed decisions in designing AWS-based solutions.

Practice Test

True/False: Amazon Fargate lets you run containers without managing servers or clusters.

  • True
  • False

Answer: True

Explanation: Amazon Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). It removes the need to provision and manage servers.

AWS Lambda works on an event-driven basis.

  • True
  • False

Answer: True

Explanation: AWS Lambda is a serverless compute service that automatically runs your code in response to events, such as changes to data in an Amazon S3 bucket, updates to a DynamoDB table, or custom events generated by applications or services.

Multiple Select: AWS Fargate and AWS Lambda support what types of compute?

  • A. Serverless
  • B. Server-based
  • C. On-demand
  • D. Elastic

Answer: A, C, D

Explanation: Both Fargate and Lambda are serverless technologies. They provide on-demand compute and the ability to quickly adapt to changes in workload demands (elastic).

True/False: AWS Lambda supports all programming languages.

  • True
  • False

Answer: False

Explanation: AWS Lambda does not support all programming languages. However, it does support a range of widely used languages like Python, Node.js, Java, Go, .NET, and Ruby.

Single Select: AWS Fargate is most closely associated with which AWS service?

  • A. EC2
  • B. ECS/EKS
  • C. ELB
  • D. S3

Answer: B. ECS/EKS

Explanation: Fargate is a technology that you can use with Amazon ECS and EKS to run containers without having to manage servers or clusters.

True/False: AWS Lambda functions can be triggered by external event sources.

  • True
  • False

Answer: True

Explanation: AWS Lambda can be configured to respond to a variety of event sources, including changes to data in S3 buckets, updates to DynamoDB tables, custom events from your own applications, and more.

AWS Lambda functions idle for long periods of time may experience what performance impact?

  • A. Increased Latency
  • B. Decreased Throughput
  • C. Loss of Data
  • D. No Impact

Answer: A. Increased Latency

Explanation: AWS Lambda functions may experience increased latency if they have been idle for some time due to the “cold start” problem.

True/False: AWS Fargate is cheaper than EC2 and Lambda due to its serverless nature.

  • True
  • False

Answer: False

Explanation: The cost of AWS Fargate can be higher compared to other services like EC2 and Lambda. While management overhead is reduced with Fargate, the cost depends on various factors including running time, resources used, and network bandwidth.

Which AWS service is typically used for deploying serverless applications?

  • A. AWS Code Deploy
  • B. AWS Lambda
  • C. AWS Fargate
  • D. AWS Amplify

Answer: B. AWS Lambda

Explanation: AWS Lambda is typically used for deploying serverless applications as it allows running code without provisioning or managing servers.

True/False: Amazon ECS supports Fargate launch type.

  • True
  • False

Answer: True

Explanation: Amazon ECS supports two launch types, Fargate and EC Fargate abstracts away the underlying server infrastructure, allowing you to focus on designing and building your applications.

True/False: AWS Lambda functions only run within your VPC.

  • True
  • False

Answer: False

Explanation: AWS Lambda functions can be configured to access resources within your VPC, but they do not have to be confined to your VPC. They are able to access internet resources or AWS services outside of your VPC.

Single Select: Which service would be best for running batch processing jobs that need to start and finish at fixed times every day?

  • A. Amazon EC2
  • B. Amazon ECS with Fargate
  • C. AWS Lambda
  • D. Amazon RDS

Answer: C. AWS Lambda

Explanation: AWS Lambda is ideal for running code that responds to events, such as time-based schedules, meaning it’s well-suited for batch processing jobs that need to start and finish at fixed times.

Multiple select: What are the pricing components of AWS Fargate?

  • A. Compute time
  • B. Number of requests
  • C. Quantity of data transferred
  • D. Storage type

Answer: A, C

Explanation: AWS Fargate charges you based on the amount of compute time your containers use and the quantity of outbound data transfer.

True/False: AWS Lambda automatically scales applications in response to incoming request traffic.

  • True
  • False

Answer: True

Explanation: AWS Lambda automatically scales applications by running code in response to each trigger and adjusting capacity to maintain consistent performance at the lowest cost.

Single Select: Which AWS service provides a serverless interactive query service?

  • A. AWS Athena
  • B. AWS Redshift
  • C. AWS EMR
  • D. AWS Data Pipeline

Answer: A. AWS Athena

Explanation: AWS Athena is an interactive query service that makes it easier to analyze data directly in Amazon S3 using standard SQL. It is serverless, so there is no infrastructure to manage.

Interview Questions

What is AWS Lambda and what benefits does it provide for developers?

AWS Lambda is a serverless computing service that runs your code in response to events and automatically manages the underlying compute resources for you. It allows developers to focus on coding, without worrying about managing servers, and it can scale automatically to handle the traffic of any size.

What can trigger an AWS Lambda function to execute?

An AWS Lambda function can be triggered by many AWS services like API Gateway, S3, DynamoDB, CloudWatch and many others or it can be called directly from any web or mobile application.

What is AWS Fargate and how does it differ from traditional container management?

AWS Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). Fargate makes it easy for you to focus on building your applications because it removes the need to manage the underlying servers.

What is the difference between AWS Lambda and AWS Fargate?

AWS Lambda is a service that lets you run your code without provisioning or managing servers. AWS Fargate, on the other hand, is a service that allows you to run containers without having to manage the underlying instances.

In Serverless architecture, how are costs managed?

In a serverless architecture, you pay only for the compute time you consume and not for the idle time. This means you are only billed for the time your functions run, down to the nearest 100 milliseconds.

Which AWS service can be used to create a serverless RESTful API?

Amazon API Gateway is a fully managed service that allows developers to create, publish, maintain, monitor, and secure APIs at any scale. It supports RESTful APIs and can be integrated with AWS Lambda to create serverless applications.

What are the languages supported by AWS Lambda?

AWS Lambda currently supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code, and also provides a Runtime API which allows you to use other programming languages to build functions.

What is the maximum execution time for a Lambda function?

The maximum execution time for a Lambda function is 15 minutes.

What is the AWS Serverless Application Model (SAM)?

The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It defines a simplified syntax for expressing serverless resources and automatically expands into AWS CloudFormation syntax, enabling you to build serverless applications easier and quicker.

How does AWS Fargate simplify network setup for containers?

AWS Fargate automatically manages the setup and configuration of networking for containers. It creates and manages elastic network interfaces in your VPC for each running Fargate task, and provides each task with its own isolated networking environment.

Can you debug a Lambda function locally?

Yes, using AWS SAM, you can invoke Lambda functions locally, simulate the API Gateway locally, and start a local step functions web server. Other tools like AWS Toolkit for Visual Studio Code also help in debugging Lambda functions locally.

How does concurrency work in AWS Lambda?

Concurrency is the number of requests that a function is serving at any given time. When a function is invoked, AWS Lambda launches an instance of the function to process the event. If the function is already serving requests, AWS Lambda uses the existing instance or starts a new one.

What are the data persistence options for serverless architecture in AWS?

There are several data persistence options, including object storage (S3), managed relational database service (RDS), NoSQL database (DynamoDB), in-memory data store (ElastiCache), and disk-based block storage (EBS).

How can you handle dependencies in AWS Lambda?

Dependencies in AWS Lambda can be handled using deployment packages. A deployment package is a ZIP archive that contains your code and any dependencies. Lambda needs these dependencies to run the code.

What is a cold start in AWS Lambda?

A cold start in AWS Lambda refers to a state where a new instance of a function is started and the code has to be loaded and the event is then processed. Cold starts occur when you execute an inactive function for the first time. They also happen when Lambda scales a function up with more instances to handle more invocations.

Leave a Reply

Your email address will not be published. Required fields are marked *