Merge pull request #4 from kananinirav/Nirav/cloud-integration-document
[Modified / Added] Cloud Integration doc
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- [Other Compute Section](sections/other_compute.md)
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- [Deploying and Managing Infrastructure at Scale](sections/deploying.md)
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- [Global Infrastructure](sections/global_infrastructure.md)
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- [Cloud Integration](sections/cloud_integration.md)
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### Contributors
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- [AWS Availability Zones](#aws-availability-zones)
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- [AWS Points of Presence (Edge Locations)](#aws-points-of-presence-edge-locations)
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- [Tour of the AWS Console](#tour-of-the-aws-console)
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- [Shared Responsibility Model diagram](#shared-responsibility-model-diagram)
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- [Shared Responsibility Model](#shared-responsibility-model)
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## What is Cloud Computing?
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- Rekognition (Software as a Service)
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- **Region Table:** <https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services>
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## Shared Responsibility Model diagram
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## Shared Responsibility Model
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- CUSTOMER = RESPONSIBILITY FOR THE SECURITY **IN** THE CLOUD
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- AWS = RESPONSIBILITY FOR THE SECURITY **OF** THE CLOUD
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sections/cloud_integration.md
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sections/cloud_integration.md
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# Cloud Integration
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- [Cloud Integration](#cloud-integration)
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- [Section Introduction](#section-introduction)
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- [Amazon SQS - Simple Queue Service](#amazon-sqs---simple-queue-service)
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- [Amazon Kinesis](#amazon-kinesis)
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- [Amazon SNS](#amazon-sns)
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- [Amazon MQ](#amazon-mq)
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- [Integration - Summary](#integration---summary)
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## Section Introduction
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- When we start deploying multiple applications, they will inevitably need to communicate with one another
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- There are two patterns of application communication
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1. Synchronous communications (application to application)
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2. Asynchronous / Event based (application to queue to application)
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- Synchronous between applications can be problematic if there are sudden spikes of traffic
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- What if you need to suddenly encode 1000 videos but usually it’s 10?
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- In that case, it’s better to **decouple** your applications:
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- using SQS: queue model
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- using SNS: pub/sub model
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- using Kinesis: real-time data streaming model (out of scope for the exam)
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- These services can scale independently from our application!
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## Amazon SQS - Simple Queue Service
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- Oldest AWS offering (over 10 years old)
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- Fully managed service (~serverless), use to decouple applications
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- Scales from 1 message per second to 10,000s per second
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- Default retention of messages: 4 days, maximum of 14 days
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- No limit to how many messages can be in the queue
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- Messages are deleted after they’re read by consumers
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- Low latency (<10 ms on publish and receive)
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- Consumers share the work to read messages & scale horizontally
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## Amazon Kinesis
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- **Kinesis = real-time big data streaming**
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- Managed service to collect, process, and analyze real-time streaming data at any scale
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- Too detailed for the Cloud Practitioner exam but good to know:
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- Kinesis Data Streams: low latency streaming to ingest data at scale from hundreds of thousands of sources
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- Kinesis Data Firehose: load streams into S3, Redshift, ElasticSearch, etc…
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- Kinesis Data Analytics: perform real-time analytics on streams using SQL
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- Kinesis Video Streams: monitor real-time video streams for analytics or ML
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## Amazon SNS
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- What if you want to send one message to many receivers?
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- Amazon Simple Notification Service is a notification service provided as part of Amazon Web Services since 2010. It provides a low-cost infrastructure for mass delivery of messages, predominantly to mobile users.
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- The “event publishers” only sends message to one SNS topic
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- As many “event subscribers” as we want to listen to the SNS topic notifications
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- Each subscriber to the topic will get all the messages
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- Up to 12,500,000 subscriptions per topic, 100,000 topics limit
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## Amazon MQ
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- SQS, SNS are “cloud-native” services, and they’re using proprietary protocols from AWS.
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- Traditional applications running from on-premise may use open protocols such as: MQTT, AMQP, STOMP, Openwire, WSS
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- When migrating to the cloud, instead of re-engineering the application to use SQS and SNS, we can use Amazon MQ
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- Amazon MQ = managed Apache ActiveMQ
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- Amazon MQ doesn’t “scale” as much as SQS / SNS
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- Amazon MQ runs on a dedicated machine (not serverless)
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- Amazon MQ has both queue feature (~SQS) and topic features (~SNS)
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## Integration - Summary
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- SQS:
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- Queue service in AWS
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- Multiple Producers, messages are kept up to 14 days
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- Multiple Consumers share the read and delete messages when done
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- Used to decouple applications in AWS
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- SNS:
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- Notification service in AWS
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- Subscribers: Email, Lambda, SQS, HTTP, Mobile…
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- Multiple Subscribers, send all messages to all of them
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- No message retention
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- Kinesis: real-time data streaming, persistence and analysis
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- Amazon MQ: managed Apache MQ in the cloud (MQTT, AMQP.. protocols)
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