Platform

5 minutes 5 Questions

Platforms in AWS Elastic Beanstalk determine an application's underlying infrastructure, including operating system, webserver, and runtime. Furthermore, developers can choose from a wide range of platforms, such as Go, PHP, Python, Ruby, Node.js, Java, and .NET. Users can also create customized platforms to suit specific requirements. Elastic Beanstalk makes integrations easy by offering preconfigured platforms to simplify infrastructure management.

AWS Elastic Beanstalk: Platform

What it is:
AWS Elastic Beanstalk Platform is a service that automates the process of deploying and running applications in the AWS cloud environment. The platform is built on the foundation of infrastructures like EC2 and S3.

Why it is important:
With AWS Elastic Beanstalk Platform, developers can focus on developing their applications without worrying about the underlying infrastructure as it provides automatic management. This service is essential for ensuring scalability, reliability, security, and monitoring of applications.

How it works:
This service works by handling the infrastructure's orchestration, including capacity provisioning, load balancing, automatic scaling, and application health monitoring. Users only need to upload their application, and Elastic Beanstalk automatically handles the rest of the details.

Exam Tips: Answering Questions on 'Platform'
When answering questions related to AWS Elastic Beanstalk Platform in the AWS Solution Architect exam, it is crucial to:
1. Understand the components and functionalities of the AWS Elastic Beanstalk Platform.
2. Remember the benefits of using this service like reducing the management complexity.
3. Understand the relationship between AWS Elastic Beanstalk and other AWS services.
4. Be able to explain how it automatically handles the deployment details from capacity provisioning, load balancing, to auto-scaling and application health monitoring.

Equally, remember to explore the AWS documentation about Elastic Beanstalk for a deep understanding of the service to answer the exam questions accurately.

Test mode:

Exam (Timed)

Practice (With explanations)

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Question 1

A company has a web application hosted on an EC2 instance, and the application utilizes a DynamoDB table. They are experiencing high latencies during peak hours. How can you improve the performance of the application?

Enable S3 Transfer Acceleration Increase the EC2 instance size Enable DynamoDB Accelerator (DAX) Attach an AWS Load Balancer to the EC2 instance

Correct Answer: Enable DynamoDB Accelerator (DAX)

DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that can reduce DynamoDB response times from milliseconds to microseconds. Increasing the EC2 instance size would not improve latency between EC2 and DynamoDB. Attaching a Load Balancer only helps balance incoming traffic. S3 Transfer Acceleration improves transfers of files over the internet to S3. ElastiCache is for caching data in-memory for data store and not for DynamoDB. Migrating to ECS would not necessarily improve latency.

Question 2

Your company designed a multi-tier application with a web layer, application layer, and a database layer. The solution needs to be highly available and fault-tolerant. Which AWS service should be used for the database layer?

Amazon RDS with a single Availability Zone Amazon DynamoDB Amazon RDS with Read Replicas Amazon RDS with Multi-AZ Deployment

Correct Answer: Amazon RDS with Multi-AZ Deployment

Amazon RDS with Multi-AZ deployment provides high availability and fault tolerance by automatically provisioning a primary and standby database in different Availability Zones. Read Replicas are designed for read-heavy workloads. DynamoDB is a NoSQL database and may not be suitable for a multi-tier application. Single-AZ deployments and Aurora without Multi-AZ are not fault-tolerant. AWS Glue Catalog is a metadata store for your data, not a database service.

Question 3

You need to analyze log data and generate reports in near real-time based on specific keywords for a web-based application. Which combination of AWS services can be used to fulfill these requirements?

AWS Elastic Beanstalk and Amazon RDS Amazon EMR and Amazon S3 Amazon SQS and Amazon Redshift AWS Kinesis Data Firehose and Amazon Elasticsearch

Correct Answer: AWS Kinesis Data Firehose and Amazon Elasticsearch

Using AWS Kinesis Data Firehose can help stream log data, and Amazon Elasticsearch will enable near real-time data analysis with specific keywords. EMR and S3 are not built for near real-time analysis. Elastic Beanstalk and RDS are for deploying applications and relational databases. SQS and Redshift do not help with near real-time analysis. AWS Batch and EFS handle batch processing and shared storage. Glue and DynamoDB are not suitable for real-time log data analysis.

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