Module 1: Designing a serverless web backend on AWS

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In this post, I provide complete, accurate, and detailed explanations for the answers to Module 1: Designing a serverless web backend on AWS of  Course 2: Architecting Solutions on AWS

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Week 1 Assessment

Graded Assignment

1. A solutions architect must design a solution to help manage their customer’s containerized applications. Currently, the customer workload runs in Docker containers on top of Amazon Elastic Compute Cloud (Amazon EC2) instances and on-premises servers that run a hybrid Kubernetes cluster. The customer wants to migrate part of their hybrid Kubernetes deployment to the cloud with a minimum amount of effort, and they want to keep all the native features of Kubernetes. The customer also wants to reduce their operational overhead for managing their Kubernetes cluster. Which managed AWS service should the solutions architect suggest to best satisfy these requirements?

  • AWS Fargate with Amazon Elastic Container Service (Amazon ECS)
  • AWS Fargate with Amazon Elastic Kubernetes Service (Amazon EKS)
  • Amazon Elastic Container Service (Amazon ECS)
  • Amazon Elastic Kubernetes Service (Amazon EKS) ✅

Explanation:
The customer is already using Kubernetes and wants to retain native Kubernetes features while reducing operational overhead.

  • Amazon EKS is a managed Kubernetes service that supports native Kubernetes APIs and tools.
  • EKS handles the control plane operations, so customers don’t need to manage master nodes themselves.
  • AWS Fargate with EKS is good for serverless Kubernetes workloads but may not be the best “minimum effort” migration from hybrid setups.
  • ECS does not support native Kubernetes — it uses its own orchestration system.

2. An application needs to process events that are received through an API. Multiple consumers must be able to process the data concurrently. Which AWS managed service would best meet this requirement in the most cost-effective way?

  • Amazon Simple Notification Service (Amazon SNS) with a fan-out strategy ✅
  • Amazon Simple Queue Service (Amazon SQS) with FIFO queues
  • Amazon EventBridge with rules
  • Amazon Elastic Compute Cloud (Amazon EC2) with Spot Instances

Explanation:

  • The fan-out pattern with Amazon SNS allows you to broadcast events to multiple consumers, each of which can receive messages via SQS queues, Lambda functions, or other endpoints.
  • This supports concurrent processing by multiple consumers.
  • It’s also cost-effective and fully managed.
  • FIFO queues are meant for strict order and deduplication, not concurrency.
  • EventBridge is useful for routing events, but SNS with fan-out is more direct and cost-efficient for multi-consumer event processing.

3. True or False: Amazon Relational Database Service (Amazon RDS) is more suitable for databases that handle structured or relational data, where users can count with features like auto-increment and table joins. Amazon DynamoDB is more suitable for NoSQL database workloads, where tables are collection of items that have their own attributes.

  • True ✅
  • False

Explanation:

  • Amazon RDS is ideal for structured data in relational databases (e.g., MySQL, PostgreSQL), supporting features like auto-increment, joins, and ACID transactions.
  • DynamoDB is a NoSQL database suited for unstructured/semi-structured data, where each item can have different attributes. It’s optimized for high-scale, low-latency operations, but lacks advanced relational features.

4. Amazon DynamoDB is designed for scale and performance. In most cases, the DynamoDB response times can be measured in single-digit milliseconds. However, there are certain use cases that require response times in microseconds. For these use cases, DynamoDB Accelerator (DAX) delivers fast response times for accessing eventually consistent data. Which statements about DAX are correct? (Choose THREE.)

  • DAX reduces operational and application complexity by providing a managed service that is compatible with the DynamoDB API. ✅
  • Although using DAX has a cost, it can reduce the consumption of DynamoDB table capacity. If the data is read intensive (that is, millions of requests per second), DAX can result in cost savings by caching the data while also providing better read latency, being beneficial for scenarios in need of repeated reads for individual keys. ✅
  • DAX does not support server-side encryption (SSE).
  • DAX is not designed for applications that are write-intensive. It can also add cost to applications that do not perform much read activity. ✅
  • DAX does not support encrypting data in transit, which means that communication between an application and DAX cannot be encrypted.

Explanation:

  • DAX is a managed in-memory cache for DynamoDB that helps accelerate read operations.
  • It reduces the load on the main DynamoDB table, which can lead to cost savings for read-heavy workloads.
  • It’s not useful for write-heavy workloads because it doesn’t accelerate writes.
  • DAX supports server-side encryption and encryption in transit, so the incorrect options about encryption are false.

5. True or False: AWS Lambda is a compute service that runs code without the need to provision or manage servers. Lambda runs code on a high-availability compute infrastructure. It also performs all the administration of compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, and logging. Lambda can run code for virtually any type of application or backend service.

  • True ✅
  • False

Explanation:

  • AWS Lambda is a serverless compute service that executes your code without managing servers.
  • It handles scaling, fault tolerance, monitoring, and logging automatically.
  • It supports many languages and can integrate with many AWS services for event-driven architectures.

Related contents:

Module 2: Designing a serverless data analytics solution on AWS
Module 3: Designing a hybrid solution for container based workloads on AWS
Module 4: Designing a solution following account governance and management best practices

You might also like:

Course 1: AWS Cloud Technical Essentials
Course 3: Building Data Lakes on AWS
Course 4: Exam Prep: AWS Certified Solutions Architect – Associate

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