AWS-Periodic-Table services categorized
| Name | Summary | Details | Use cases |
|---|---|---|---|
| EC2 | Virtual Servers in the cloud | EC2 | Storage Optimized - Ideal for NoSQL databases, data warehousing, distributed file systems, and more. Ensures that your application always has the right amount of compute, and also proactively provisions capacity with Predictive Scaling. |
| EC2 Autoscaling | Scale compute capacity to meet demand | EC2 | Self Healing - can detect when an instance is unhealthy, terminate it, and replace it with a new one. |
| Lightsail | Launch and manage virtual private servers | Lightsail | Lightsail is ideal for simpler workloads, quick deployments, and getting started on AWS. |
| Lambda | Function as a Service - run your code in reponse to events | Lambda | Data processing - triggered by AWS services such as S3, DynamoDB, Kinesis, SNS, and CloudWatch, or it can be orchestrated into workflows by AWS Step Functions. REAL-TIME FILE PROCESSING - S3 to trigger AWS Lambda to process data immediately after an upload. For example, you can use Lambda to thumbnail images, transcode videos, index files, process logs, validate content, and aggregate and filter data in real-time. REAL-TIME STREAM PROCESSING - use AWS Lambda and Amazon Kinesis to process real-time streaming data for application activity tracking, transaction order processing, click stream analysis, data cleansing, metrics generation, log filtering, indexing, social media analysis, and IoT device data telemetry and metering. EXTRACT, TRANSFORM, LOAD - use AWS Lambda to perform data validation, filtering, sorting, or other transformations for every data change in a DynamoDB table and load the transformed data to another data store. Backends - You can build serverless backends using AWS Lambda to handle web, mobile, Internet of Things (IoT), and 3rd party API requests. |
| Elastic Beanstalk | Run and manage web apps | Elastic Beanstalk | - |
| Outposts | Run AWS services on prem | Outposts | - |
| Serverless Application Repository | Discover Deploy and Publish Serverless applications | SAR | - |
| Batch | Run batch jobs at any scale | Batch | Automate the analysis of the day’s transaction costs, execution reporting, and market performance. Automate content rendering workloads and reduce the need for human intervention due to execution dependencies or resource scheduling. |
| Name | Summary | Details | Use cases |
|---|---|---|---|
| Athena | Query data in S3 using SQL | Athena | NO ETL Just point to your data in Amazon S3, define the schema, and start querying using the built-in query editor. |
| CloudSearch | Managed search service | CloudSearch | - |
| Elasticsearch Service | Fully managed and scalable ES with built-in Kibana | Elasticsearch | Application monitoring analyze logs from its applications to identify and resolve performance bottlenecks or availability issues, ensuring streamlined experience. Amazon Elasticsearch Service with Kibana to quickly index, search, and visualize logs from its routers, applications, and other devices to find and prevent security threats. |
| Kinesis | Easily collect, process, and analyze video and data streams in real time | Kinesis | - |
| Kinesis Video Streams | Capture, process, and store media streams for playback, analytics, and machine learning | Video Streams | - |
| Kinesis Data Streams | Manually managed - Collect streaming data, at scale, for real-time analytics | Streams | - |
| Kinesis Data Firehose | Fully Managed - Prepare and load real-time data streams into load streaming data into data lakes, data stores and analytics tools. Use Kinesis Streams if you want to do some custom processing with streaming data. With Kinesis Firehose you are simply ingesting it into S3, Redshift or ElasticSearch | Firehose | |
| Kinesis Data Analytics | analyze streaming data, gain actionable insights | Analytics | - |
| Managed Kafka(MSK) | Fully managed, highly available, and secure Apache Kafka service | MSK | - |
| Redshift | The most popular and fastest cloud data warehouse for BI / Operational analytics | Redshift | - |
| Data Pipeline | Orchestration service for data movement. | Data Pipeline | - |
| Glue | ETL - Prepare and load data. Discovers your data and stores the associated metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once cataloged, your data is immediately searchable, queryable, and available for ETL. | Glue | Queries against an Amazon S3 data lake. Analyze log data in your data warehouse like RDS cleanse and flatten the data. Unified view of your data across multiple data stores AWS Glue Data Catalog to quickly discover and search across multiple AWS data sets without moving the data. |
| Lake Formation | Identify existing data stores in S3 or relational and NoSQL databases, and move the data into your data lake. | Lake Formation | - |
| Data Exchange | find and subscribe to third-party data in the cloud | Data Exchange | more than 1,000 data products now available from more than 80 qualified data providers in AWS Marketplace. |
| Name | Summary | Details | Use cases |
|---|---|---|---|
| Step Functions | Build distributed applications using visual workflows | Step Functions | Data processing - multiple ETL jobs execute in order, Automate tasks - routine deployments, upgrades, installations, and migrations, recurring tasks such as patch management, infrastructure selection, and data synchronization. , Modernize a monolith - carve off a few tasks from the rest of your codebase into microservices. Application orchestration - ombine multiple AWS Lambda functions into responsive serverless applications and microservices |
| AppFlow | Integrate Saas apps like Salesforce, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, and automate data flows , without code | AppFlow | Store or sync Salesforce data Hydrate data lakes - send Dynatrace insights on application performance to a data lake Routinely analyze events create a data flow that sends event and conversation data from a Slack Channel to an Amazon Redshift or Snowflake data warehouse for downstream analysis. Create routine reports of Datadog metrics Automate data back ups - send high severity Zendesk tickets to Amazon S3 for further analysis |
| EventBridge | Serverless event bus that connects application data from your own apps, SaaS, and AWS services | EventBridge | Customer support - send status changes in customer support tickets to EventBridge and trigger an automated workflow Security operations - include threat detection events in a Whispir communications workflow, or automate the delivery of security system reports with event-based rules. Business operations - to connect PagerDuty incidents to an Amazon Redshift data warehouse, so you can analyze the remediation velocity and average operational load on engineering teams. Application monitoring - send load volume alerts from DataDog to EventBridge to trigger an AWS Lambda function that scales your EC2 instances to handle the expected load increase. Directory registration - send new user creation events from OneLogin to EventBridge, and route them to a Lambda function that makes technical resources available to newly hired engineers. Customer data updates - you can send an event to EventBridge when the status of a SugarCRM opportunity changes to “Closed Won,” and trigger a workflow that will provision billing records |
| Simple Notification Service | Pub/Sub , Mobile Push and SMS | SNS | SNS reliably delivers messages to all supported AWS endpoints, such as Amazon SQS queues and AWS Lambda functions. In case the subscribed endpoint isn't available, Amazon SNS executes message delivery retry policies and can also move messages to dead-letter queues (DLQ). Message Filtering - simplify your pub/sub messaging architecture by offloading the message filtering logic from your subscriber systems, and message routing logic from your publisher systems. CloudWatch gives visibility into your filtering activity, and CloudFormation enables you to deploy subscription filter policies in an automated and secure manner. **** |
| Simple Queue Service / SQS FIFO | managed message queues for microservices, distributed systems, and serverless applications | SQS | Reliably deliver messages - tansmit any volume of data, at any level of throughput, without losing messages or requiring other services to be available sensitive data secure - exchange sensitive data between applications using server-side encryption (SSE) to encrypt each message body |
| AppSync | Power your applications with the right data, from one or more data sources, at global scale | AppSync | Real Time Collaboration - broadcasting data from the backend to all connected clients (one-to-many) or broadcasting data between clients themselves (many-to-many) Chat Applications - build a mobile and web application that supports multiple private chat rooms, offers access to conversation history, and enqueues outbound messages, even when the device is offline Internet of Things - build a real-time dashboard in a mobile or web application to visualize telemetry from a connected car Data Layer - AppSync as a single interface to access and combine data from multiple microservices in your application. Polyglot Backend Data Access - retrieve or modify data from multiple data sources (SQL databases in Amazon Aurora Serverless, NoSQL tables in Amazon DynamoDB, search data in Amazon Elasticsearch Service, REST endpoints in Amazon API Gateway, or serverless backends in AWS Lambda) with a single call Offline - Update data when the client reconnects. |
| Name | Summary | Details | Use cases |
|---|---|---|---|
| Cost Explorer | Visualize, understand, and manage your AWS costs and usage over time | Cost Explorer | Monthly Costs by AWS Service Hourly and Resource Level Granularity Savings Plans |
| AWS Budgets | Set custom budgets that alert you when you exceed your budgeted thresholds | Budgets | - |
| Cost & Usage Report | Comprehensive costs and usage report | CUR | Track your Amazon EC2 Reserved Instance (RI) usage Using the Amazon Athena data integration feature, you can quickly query your cost and usage information using standard SQL queries. You can also upload your data directly into Amazon Redshift or Amazon QuickSight. |
| Reserved Instance (RI) Reporting | Manage and monitor your instance reservations | RI | RI purchase recommendations via AWS Cost Explorer RI Coverage |
| Savings Plans | flexible pricing model that provides savings of up to 72% on your AWS compute usage | Savings Plans | On Demand, just like EC2 Reserved Instances, in exchange for a commitment to use a specific amount of compute power (measured in $/hour) for a one or three year period. You can sign up for Savings Plans for a 1- or 3-year term |