AWS Services Cheat Sheet
Each section of the exam domains for the AWS Certified Solutions Architect – Associated (SAA-C03) exam is covered in a separate chapter in this book. You can quickly understand a variety of AWS services that are covered by the exam domains via a short explanation provided by the following list. You can review additional details on each of these services by reading the related FAQs for each service. There might be exam questions about some of these services, and then again, there might not be. For the purposes of preparing for the exam, the following details for these particular AWS services should be sufficient in answering the test questions that may mention them.
- AWS AppSync: A service designed for mobile applications that require user and data synchronization across multiple devices. AWS AppSync supports iOS, Android, and JavaScript (React and Angular). Select data records can be synchronized automatically across multiple devices using the GraphQL query language.
- Amazon AppFlow: A hosted integration service for securely exchanging data records, such as events from external SaaS applications such as Salesforce and ServiceNow.
- Amazon Athena: A serverless query service that analyzes Amazon S3 data. Queries can be performed in a variety of standards, including CSV, JSON, ORC, Avro, and Parquet. Queries can also be executed in parallel, resulting in extremely high performance.
- AWS Audit Manager: Audit Manager’s prebuilt frameworks map your AWS resources to industry standards such as CIS AWS Foundations Benchmark, the General Data Protection Regulation (GDPR), and the Payment Card Industry Data Security Standard (PCI DSS).
- Amazon Comprehend: A natural language processing (NLP) service that uses machine learning to find meaning and insights in text.
- Amazon Cognito: Add mobile user sign-up, sign-in, and access controls to your web and mobile apps using a hosted identity store that supports both social media and enterprise identity federation.
- Amazon Detective: Analyze, investigate, and quickly identify the root cause of potential security issues or suspicious activities collecting log data from your AWS resources using machine learning, statistical analysis, and graph theory, ingesting data from AWS CloudTrail logs, Amazon VPC Flow Logs, and Ama-zon GuardDuty findings.
- AWS Device Farm: An application testing service that lets you improve the quality of your web and mobile apps during development by running tests concurrently on multiple desktop browsers and real physical mobile devices hosted at AWS. Device support includes Apple, Google, and Android devices.
- AWS Data Exchange: Supports the secure exchange of third-party data files and data tables into AWS. Customers can use the AWS Data Exchange API to copy selected third-party data from AWS Data Exchange into Amazon S3 storage. Data Exchange third-party products include weather, healthcare, data sciences, geospatial and mapping services.
- AWS Data Pipeline: Process and move data between different AWS compute and storage services, and from on-premises siloed data sources, and transfer the results into Amazon S3 buckets, Amazon RDS, Amazon DynamoDB, and Amazon EMR.
- Amazon EMR: EMR is a big data platform for data processing, interac-tive analysis, and machine learning using Apache Spark, Apache Hive, and Presto. Run petabyte-scale analysis much cheaper than traditional on-premises solutions.
- Amazon Forecast: Provides accurate time-sensitive forecasts for retail, manu-facturing, travel demand, logistics, and web traffic markets.
- Amazon Fraud Detector: A managed fraud detector that helps identify potentially fraudulent online activities such as online payment fraud and fake account creation.
- AWS Glue: A fully managed extract, transform, and load (ETL) service that helps discover details and properties of data stored in Amazon S3 and Amazon Redshift for analytics, machine learning, and application development. AWS Glue has the following key components:
- AWS Glue Data Catalog: Stores structural and operational metadata, including its table definition, physical location, and the data’s historical and business relevance.
- Glue Crawlers: Crawlers are used to scan various data stores populating the AWS Glue Data Catalog with relevant data statistics.
- AWS Glue Studio: Create jobs that extract structured or semi-structured data from a data source.
- AWS Glue Schema Registry: Validate and control streaming data using registered schemas for Apache Avro and JSON.
- AWS Glue DataBrew: A visual data preparation tool that can be used by data analysts to clean and normalize data for analysis and machine learning.
- Amazon Kendra: Highly accurate machine learning enterprise search service for all unstructured data stored in Amazon S3 and Amazon RDS databases.
- Amazon Kinesis: Allows customers to connect, process, and analyze real-time streaming data to quickly gather insights to the incoming data flow of informa-tion. The use case for Amazon Kinesis is for ingesting, buffering, and processing streaming video, audio applications, logs, website clickstreams, and IoT telem-etry data for machine learning, analysis, and storage at any scale.
- Amazon Kinesis Video Streams: Developers can use the Kinesis Video Streams SDK to develop applications with connected camera devices, such as phones, drones, and dash cams, to securely stream video to custom real-time or batch-oriented applications running on AWS EC2 instances. The video streams can also be stored and encrypted for further monitor-ing and analytics.
- Amazon Kinesis Data Firehose: Streaming data is collected and deliv-ered in real time to Amazon S3, Amazon Redshift, Amazon Open Search Service, custom HTTP/HTTPS endpoints, and to third-party service
providers including Splunk, Datadog, and LogicMonitor. Kinesis Data Firehouse can also be configured to transform data records before the data is stored.
Amazon Kinesis Data Streams: Collect and process gigabytes of streaming data that is generated continuously from thousands of locations such as log files, e-commerce purchases, game player activity, web click-stream data, and social media information. Multiple data streams ingested into Kinesis are sent into custom applications running on EC2 instances, or data stored in a DynamoDB table, Amazon S3 storage, Amazon EMR, or Amazon Redshift.