AWS & ASP.NET

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https://dotnetcodr.com/amazon-cloud/

Amazon cloud

Big Data overall architecture

• Architecture of a Big Data messaging and aggregation system using Amazon Web Services part 1
• Architecture of a Big Data messaging and aggregation system using Amazon Web Services part 2
• Architecture of a Big Data messaging and aggregation system using Amazon Web Services part 3
• Architecture of a Big Data messaging and aggregation system using Amazon Web Services part 4
• Architecture of a Big Data messaging and aggregation system using Amazon Web Services part 5

Amazon Big Data components and code

The message handler: Kinesis

• Big Data: using Amazon Kinesis with the AWS.NET API Part 1: introduction
• Using Amazon Kinesis with the AWS.NET API Part 2: stream, NET SDK and domain setup
• Big Data: using Amazon Kinesis with the AWS.NET API Part 3: sending to the stream
• Big Data: using Amazon Kinesis with the AWS.NET API Part 4: reading from the stream
• Using Amazon Kinesis with the AWS.NET API Part 5: validation
• Using Amazon Kinesis with the AWS.NET API Part 6: storage

The raw data storage: S3

• Using Amazon S3 with the AWS.NET API Part 1: introduction
• Using Amazon S3 with the AWS.NET API Part 2: code basics
• Using Amazon S3 with the AWS.NET API Part 3: code basics cont’d
• Using Amazon S3 with the AWS.NET API Part 4: working with folders in code
• Using Amazon S3 with the AWS.NET API Part 5: S3 in Big Data
• Using Amazon S3 with the AWS.NET API Part 6: S3 in Big Data II

Data storage alternative: DynamoDb

• Using Amazon DynamoDb with the AWS.NET API Part 1: introduction
• Using Amazon DynamoDb with the AWS.NET API Part 2: code beginnings
• Using Amazon DynamoDb with the AWS.NET API Part 3: table operations
• Using Amazon DynamoDb with the AWS .NET API Part 4: record insertion
• Using Amazon DynamoDb with the AWS .NET API Part 5: updating and deleting records
• Using Amazon DynamoDb with the AWS .NET API Part 6: queries
• Using Amazon DynamoDb with the AWS .NET API Part 7: its place in Big Data

Data mining and analysis tool: Elastic MapReduce

• Using Amazon Elastic MapReduce with the AWS.NET API Part 1: introduction
• Using Amazon Elastic MapReduce with the AWS.NET API Part 2: the cluster startup GUI
• Using Amazon Elastic MapReduce with the AWS.NET API Part 3: starting and logging into a cluster
• Using Amazon Elastic MapReduce with the AWS.NET API Part 4: Hive basics with Hadoop
• Using Amazon Elastic MapReduce with the AWS .NET API Part 5: cluster-related code
• Using Amazon Elastic MapReduce with the AWS .NET API Part 6: Hive with Amazon S3 and DynamoDb
• Using Amazon Elastic MapReduce with the AWS .NET API Part 7: indirect Hive with .NET
• Using Amazon Elastic MapReduce with the AWS .NET API Part 8: connection to our Big Data demo

Data mining and analysis tool: RedShift

• Using Amazon RedShift with the AWS .NET API Part 1: introduction
• Using Amazon RedShift with the AWS .NET API Part 2: MPP definition and first cluster
• Using Amazon RedShift with the AWS .NET API Part 3: connecting to the master node
• Using Amazon RedShift with the AWS .NET API Part 4: code beginnings
• Using Amazon RedShift with the AWS .NET API Part 5: connecting to master node using ODBC
• Using Amazon RedShift with the AWS .NET API Part 6: Postgresql to master node using ODBC
• Using Amazon RedShift with the AWS .NET API Part 7: data warehousing and the star schema
• Using Amazon RedShift with the AWS .NET API Part 8: data warehousing and the star schema 2
• Using Amazon RedShift with the AWS .NET API Part 9: data warehousing and the star schema 3
• Using Amazon RedShift with the AWS .NET API Part 10: RedShift in Big Data

AWS Big Data summary

• Big Data series: a summary of Amazon Big Data tools we have discussed

Amazon CodePipeline

• Introduction to Amazon Code Pipeline with Java part 1: basics of CI/CD
• Introduction to Amazon Code Pipeline with Java part 2: setup
• Introduction to Amazon Code Pipeline with Java part 3: adding custom job runners
• Introduction to Amazon Code Pipeline with Java part 4: comparison with TeamCity and Jenkins
• Introduction to Amazon Code Pipeline with Java part 5: architecture key terms
• Introduction to Amazon Code Pipeline with Java part 6: third party action overview
• Introduction to Amazon Code Pipeline with Java part 7: the third party action user signup process
• Introduction to Amazon Code Pipeline with Java part 8: the job agent communication process
• Introduction to Amazon Code Pipeline with Java part 9: the job agent continuation token
• Introduction to Amazon Code Pipeline with Java part 10: the client web pages
• Introduction to Amazon Code Pipeline with Java part 11: starting with the job agent
• Introduction to Amazon Code Pipeline with Java part 12: the job agent entry point in code
• Introduction to Amazon Code Pipeline with Java part 13: the client token lookup service
• Introduction to Amazon Code Pipeline with Java part 14: the loadtest executor service
• Introduction to Amazon Code Pipeline with Java part 15: the job processor interface and related objects

Geo-spatial services

• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 1: introduction and goals
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 2: MaxMind source files
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 3: IPv4 range strategy
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 4: lng/lat range strategy
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 5: creating the IPv4 source file for DynamoDb
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 6: uploading IPv4 range to DynamoDb
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 7: querying the IPv4 range table
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 8: creating the lng/lat coordinates source file for DynamoDb
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 9: uploading the co-ordinate range to DynamoDb
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 10: querying the coordinate range table
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 11: uploading the geolocation range to DynamoDb
• Using Amazon DynamoDb for IP and co-ordinate based geo-location services part 12: querying the geolocation range to DynamoDb

AMIs

• How to manage Amazon Machine Images with the .NET Amazon SDK Part 1: starting an image instance
• How to manage Amazon Machine Images with the .NET Amazon SDK Part 2: monitoring and terminating AMI instances, managing Security Groups

Data Pipeline

• An example of using ShellCommandActivity on Amazon Data Pipeline

Elastic Beanstalk

• Creating an Amazon Beanstalk wrapper around a Kinesis application in Java

AWS & ASP.NET

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原文地址：http://www.cnblogs.com/haoliansheng/p/5719767.html