[Modified / Added] Cloud Integration doc

sections/cloud_integration.md

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+# Cloud Integration
+
+- [Cloud Integration](#cloud-integration)
+  - [Section Introduction](#section-introduction)
+  - [Amazon SQS - Simple Queue Service](#amazon-sqs---simple-queue-service)
+  - [Amazon Kinesis](#amazon-kinesis)
+  - [Amazon SNS](#amazon-sns)
+  - [Amazon MQ](#amazon-mq)
+  - [Integration - Summary](#integration---summary)
+
+## Section Introduction
+
+- When we start deploying multiple applications, they will inevitably need to communicate with one another
+- There are two patterns of application communication
+  1. Synchronous communications (application to application)
+  2. Asynchronous / Event based (application to queue to application)
+- Synchronous between applications can be problematic if there are sudden spikes of traffic
+- What if you need to suddenly encode 1000 videos but usually it’s 10?
+- In that case, it’s better to **decouple** your applications:
+  - using SQS: queue model
+  - using SNS: pub/sub model
+  - using Kinesis: real-time data streaming model (out of scope for the exam)
+- These services can scale independently from our application!
+
+## Amazon SQS - Simple Queue Service
+
+- Oldest AWS offering (over 10 years old)
+- Fully managed service (~serverless), use to decouple applications
+- Scales from 1 message per second to 10,000s per second
+- Default retention of messages: 4 days, maximum of 14 days
+- No limit to how many messages can be in the queue
+- Messages are deleted after they’re read by consumers
+- Low latency (<10 ms on publish and receive)
+- Consumers share the work to read messages & scale horizontally
+
+## Amazon Kinesis
+
+- **Kinesis = real-time big data streaming**
+- Managed service to collect, process, and analyze real-time streaming data at any scale
+- Too detailed for the Cloud Practitioner exam but good to know:
+  - Kinesis Data Streams: low latency streaming to ingest data at scale from hundreds of thousands of sources
+  - Kinesis Data Firehose: load streams into S3, Redshift, ElasticSearch, etc…
+  - Kinesis Data Analytics: perform real-time analytics on streams using SQL
+  - Kinesis Video Streams: monitor real-time video streams for analytics or ML
+
+## Amazon SNS
+
+- What if you want to send one message to many receivers?
+- 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.
+- The “event publishers” only sends message to one SNS topic
+- As many “event subscribers” as we want to listen to the SNS topic notifications
+- Each subscriber to the topic will get all the messages
+- Up to 12,500,000 subscriptions per topic, 100,000 topics limit
+
+## Amazon MQ
+
+- SQS, SNS are “cloud-native” services, and they’re using proprietary protocols from AWS.
+- Traditional applications running from on-premise may use open protocols such as: MQTT, AMQP, STOMP, Openwire, WSS
+- When migrating to the cloud, instead of re-engineering the application to use SQS and SNS, we can use Amazon MQ
+- Amazon MQ = managed Apache ActiveMQ
+- Amazon MQ doesn’t “scale” as much as SQS / SNS
+- Amazon MQ runs on a dedicated machine (not serverless)
+- Amazon MQ has both queue feature (~SQS) and topic features (~SNS)
+
+## Integration - Summary
+
+- SQS:
+  - Queue service in AWS
+  - Multiple Producers, messages are kept up to 14 days
+  - Multiple Consumers share the read and delete messages when done
+  - Used to decouple applications in AWS
+- SNS:
+  - Notification service in AWS
+  - Subscribers: Email, Lambda, SQS, HTTP, Mobile…
+  - Multiple Subscribers, send all messages to all of them
+  - No message retention
+- Kinesis: real-time data streaming, persistence and analysis
+- Amazon MQ: managed Apache MQ in the cloud (MQTT, AMQP.. protocols)