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Scalable Data Streaming with Amazon Kinesis Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis.
This practical guide takes a hands-on approach to implementation and associated methodologies to have you up and running with all that Amazon Kinesis has to offer. You'll work with use cases and practical examples to be able to ingest, process, analyze, and stream real-time data in no time.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Packt Publishing
2021.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright and Credits
- Contributors
- Table of Contents
- Preface
- Section 1: Introduction to Data Streaming and Amazon Kinesis
- Chapter 1: What Are Data Streams?
- Introducing data streams
- Sources of data
- The value of real-time data in analytics
- Decoupling systems
- Challenges associated with distributed systems
- Transactions per second
- Scaling
- Latency
- Fault tolerance/high availability
- Overview of messaging concepts
- Overview of core messaging components
- Messaging concepts
- Examples of data streaming
- Application log processing
- Internet of Things
- Real-time recommendations
- Video streams
- Summary
- Further reading
- Chapter 2: Messaging and Data Streaming in AWS
- Amazon Kinesis Data Streams (KDS)
- Encryption, authentication, and authorization
- Producing and consuming records
- Data delivery guarantees
- Integration with other AWS services
- Monitoring
- Amazon Kinesis Data Firehose (KDF)
- Encryption, authentication, and authorization
- Monitoring
- Producers
- Delivery destinations
- Transformations
- Amazon Kinesis Data Analytics (KDA)
- Amazon KDA for SQL
- Amazon Kinesis Data Analytics for Apache Flink (KDA Flink)
- Amazon Kinesis Video Streams (KVS)
- Amazon Simple Queue Service (SQS)
- Amazon Simple Notification Service (SNS)
- Amazon SNS integrations with other AWS services
- Encryption at rest
- Amazon MQ for Apache ActiveMQ
- IoT Core
- Device software
- Control services
- Analytics services
- Amazon Managed Streaming for Apache Kafka (MSK)
- Apache Kafka
- Amazon MSK
- Amazon EventBridge
- Service comparison summary
- Summary
- Chapter 3: The SmartCity Bike-Sharing Service
- The mission for sustainable transportation
- SmartCity new mobile features
- SmartCity data pipeline
- SmartCity data lake
- SmartCity operations and analytics dashboard
- SmartCity video
- The AWS Well-Architected Framework
- Summary
- Further reading
- Section 2: Deep Dive into Kinesis
- Chapter 4: Kinesis Data Streams
- Technical requirements
- Discovering Amazon Kinesis Data Streams
- Creating streams and shards
- Creating a stream producer application
- Creating a stream consumer application
- Data pipelines with Amazon Kinesis Data Streams
- Data pipeline design (simple)
- Data pipeline design (intermediate)
- Data pipeline design (full design)
- Designing for scalable and reliable analytics pipelines
- Monitoring and scaling with Amazon Kinesis Data Streams
- X-Ray tracing with Amazon Kinesis Data Streams
- Scaling up with Amazon Kinesis Data Streams
- Securing Amazon Kinesis Data Streams
- Implementing least-privilege access
- Summary
- Further reading
- Chapter 5: Kinesis Firehose
- Technical requirements
- Setting up the AWS account
- Using a local development environment
- Using an AWS Cloud9 development environment
- Code examples
- Discovering Amazon Kinesis Firehose