AWS Tools
SAM is public available ;p
- https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-getting-started.html
- deploy example: https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-getting-started-hello-world.html
AWS all services overview
Need to refresh about all AWS services
- so many new ones being launched recent times
- too many overlapping and confusing services among AWS product line
- https://docs.aws.amazon.com/whitepapers/latest/aws-overview/amazon-web-services-cloud-platform.html
Only listing some services I’m not so familiar personally.
Most probably will update this post again in future.
Analytics
AWS Data Pipeline
https://docs.aws.amazon.com/data-pipeline/index.html
Interesting components:
1 . Task Runners: basically slave node daemon, similar to Spark worker ExecutorRunner
2 . Activitiy: a collection of most common pipeline operations, and more of moving data around as of 2020-Apr
- => can be extended in future releases
- currently pretty limited usability
- I’m expecting more of pipeline or job management for this service
Kinesis
Amazon Kinesis: streaming data
Amazon Kinesis Data Firehose: load streaming data into data stores and analytics tools
Amazon Kinesis Data Analytics: analyze streaming data
Amazon Kinesis Data Streams: manages the infrastructure, storage, networking, and configuration
Amazon Kinesis Video Streams: stream video data
Amazon Managed Streaming for Kafka (MSK)
Kafka wrapper
AWS Lake Formation
set up a secure data lake in days
further extension is possible, for data source and metadata management
Amazon CloudFront
content delivery network (CDN) service
AWS Single Sign-On
SSO access to multiple AWS accounts and business applications
https://www.youtube.com/watch?v=FbNkDjX5efE&feature=youtu.be
AWS Cloud9
IDE in browser
AWS Chatbot
@Xin: how about call it integration service for Slack and Amazon Chime
Another lol story: add-a-wrapper-and-launch-a-service
ML
AWS Chatbot vs Amazon Lex vs Polly vs Rekognition vs Transcribe vs Elastic Inference vs Textract vs Personalize
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AWS Chatbot: a pre-built interactive agent
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Lex: deep learning capabilities of automatic speech recognition
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Amazon Polly: turns text into lifelike speech
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Amazon Transcribe: automatic speech recognition (ASR) service
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Amazon Rekognition: image analysis
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Amazon Elastic Inference: low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances
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Amazon Textract: extracts text and data from scanned documents
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Amazon Personalize: individualized recommendations for customers
Sagemaker
SageMaker Autopilot: auto model tuning and selection, and deploy best model
https://aws.amazon.com/sagemaker/autopilot/
SageMaker Experiments + Trial visualization chart + Debugger: compare model trials in studio
- Experiments https://docs.aws.amazon.com/sagemaker/latest/dg/experiments-mnist.html#experiments-mnist-compare-trials
- Debugger blog https://aws.amazon.com/blogs/aws/amazon-sagemaker-debugger-debug-your-machine-learning-models/
SageMaker Studio to include all above Sagemaker features
Pretty powerful IMHO.
- SageMaker Studio tutorial: https://docs.aws.amazon.com/sagemaker/latest/dg/gs-studio-end-to-end.html
- SageMaker Studio notebook example: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/aws_sagemaker_studio/getting_started/xgboost_customer_churn_studio.ipynb
- Experiment => select components and add to chart, can configure scatter or time-series chart
- Debugger => only on training job
- Model monitor => https://docs.aws.amazon.com/sagemaker/latest/dg/gs-studio-end-to-end.html#studio-tour-monitor
SageMaker Neo: Train models once, run anywhere with up to 2x performance improvement
https://aws.amazon.com/sagemaker/neo/
WorkMail vs Simple Email Service
Amazon WorkMail: a business e-mail service and not intended to be used for bulk e-mail services
Amazon Simple Email Service: for bulk e-mail services