What's New & What's Next from AWS?

Post on 21-Jan-2018

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Transcript of What's New & What's Next from AWS?

What’s New & What’s Next

@IanMmmm

Ian Massingham, Worldwide Lead, AWS Evangelism

M i l l i o n s O f A c t i v e C u s t o m e r s P e r M o n t h

Largest Number Of Star tup Customers

Largest Number Of Enterprise Customers

Where Are We In The Cloud’s Evolution?

In 2014

New normal In 2015

Control over your own destiny

Today

Harder, Faster, Better, Stronger

Compute VMs, Auto-scaling, Load Balancing, Containers, Virtual Private Servers, Batch Computing, Cloud

Storage Object, Blocks, File, Archivals, Import/Export, Exabyte-scale data

CDN

Databases Relational, NoSQL, Caching, Migration, PostgreSQL

Networking

CORE

Integrated Networking

Rules Engine

Device Shadows

Device SDKs

Device Gateway

Registry

Local Compute

Custom ModelTraining & Hosting

Conversational Chatbots

Virtual Desktops

App Streaming

Schema Conversion

Image & Scene Recognition

Sharing & Collaboration

Exabyte-ScaleData Migration

Text to Speech

Corporate Email Application Migration

Database Migration

Regions

Availability Zones

Points of Presence

Data Warehousing

Business Intelligence

Elasticsearch

Hadoop/Spark

Data Pipelines

Streaming Data Collection

ETLStreaming Data Analysis

Interactive SQL Queries

Queuing & Notifications

Workflow

Email

Transcoding

Deep Learning (Apache MXNet, TensorFlow, & others)

Server MigrationCommunications

Business Apps Business Intelligence DevOps Tools Security Networking StorageDatabases

API Gateway

Single Integrated Console

Identity

Sync

Mobile Analytics

Mobile App Testing

Targeted Push Notifications

One-click App Deployment

DevOps Resource Management

Application Lifecycle Management

Containers

Triggers

Resource Templates

Build & Test

Analyze & Debug

Identity Management

Key Management & Storage

Monitoring & Logs

Configuration Compliance

Web Application Firewall

Assessment& Reporting

Resource & Usage Auditing

Access Control

Account Grouping

DDOSProtection

Support ProfessionalServices

Optimization Guidance

PartnerEcosystem

Training & Certification

Solutions ManagementAccount Management

Security & Billing Reports

Personalized Dashboard

TECHNICAL & BUSINESS SUPPORT

MARKETPLACE

Monitoring

Manage Resources

Data Integration

Integrated Identity & Access

Integrated Resource & Deployment Management

Integrated Devices & Edge Systems

Resource Templates

Configuration Tracking

Server Management

Service Catalogue

Search

HYBRIDANALYTICS MOBILE SERVICESDEV/OPS IoT MACHINE LEARNING ENTERPRISE APPS MIGRATION

APP SERVICES

INFRASTRUCTURE SECURITY & COMPLIANCE MANAGEMENT TOOLSComputeVMs, Auto-scaling, Load Balancing, Containers, Virtual Private Servers, Batch Computing, Cloud Functions, Elastic GPUs, Edge Computing

Storage Object, Blocks, File, Archivals, Import/Export, Exabyte-scale data transfer

CDN

Databases Relational, NoSQL, Caching, Migration, PostgreSQL compatible

Networking VPC, DX, DNS

CORE SERVICES

Facial Recognition & Analysis

Facial Search

Patching

Contact Center

Most Complete Technology Platform

Data Warehousing

Business Intelligence

Elasticsearch

Hadoop/Spark

Data Pipelines

Streaming Data Collection

ETLStreaming Data Analysis

Interactive SQL Queries

ANALYTICS

Hadoop, Spark, Presto, HBase,

Hive, Mahout, Pig, Zeppelin

Amazon EMR

Elasticsearch

Amazon Elasticsearch

Interactive queries

Amazon Athena

Data warehouse

Amazon Redshift

Redshift Spectrum

Business intelligence

Amazon QuickSight

Real-time streaming data

Amazon Kinesis Analytics

Storage and databases

AWS Has Made Petabyte-scale Analytics Accessible To Companies Of All Sizes

No infrastructure or clusters to set up and manage

Results within seconds

Query S3 directly and right away

Pay for just the queries you run

No need to move data to Athena

Amazon AthenaInteractive query service that makes it easy to analyze data in Amazon S3 using standard SQL

Amazon EMRAnalyze large data sets using popular big data processing frameworks

Fully customizable clusters

Code your own applications

Hadoop, Spark, Presto, HBase

Amazon RedshiftAnalyze large data sets using popular big data processing frameworks

Highly structured

Complex queries across very large

databases

Pull together data from different sources

20x faster than ad-hoc query services

Amazon RedshiftAnalyze large data sets using popular big data processing frameworks

Highly structured

Complex queries across very large

databases

Pull together data from different sources

20x faster than ad-hoc query services

Query S3 directly or join data across Redshift and S3

Support for CSV, JSON, ORC, and Parquet data formats

Scale Redshift compute andstorage separately

Amazon Redshift

Redshift Query Engine

Redshift Data

Data Lake

Amazon S3

Redshift SpectrumExtend Redshift Queries To Data In Amazon S3

Extract, Transform, Load: Ubiquitous And Tedious

Tedious, “fiddly” boilerplate code

Understand what data you have and

where

Done repeatedly, reliably, and at

scale

Resource-intensive and

irregular

AVAILABLE NOW

Fully managed Data Catalog and ETL service

AWS Glue

AWS GlueFully managed Data Catalog and ETL service

Discovers and catalogs your

data

Schedules and runs your

ETL jobs

Generates customizable

transformation code

Serverless - provisions and manages your infrastructure

Build your data catalog

Generate & edit transformations

Schedule and run your jobs

Machine Learning Is Undergoing A Renaissance…

The Challenge For Machine Learning: Scale

Data Training Inference At the Edge

Tons of GPUs and CPUs Serverless

Tons of GPUs Elastic capacity Pre-built images

PBs of existing data Aggressive migration

New data created on AWS

IoT and mobile deployment Mobile optimization

IoT device optimization

The Challenge For Machine Learning: Scale

Data Training Inference At the Edge

Machine Learning On AWS Today

SERVICES

PLATFORMS

ENGINES

INFRASTRUCTURE

Amazon ML Spark & EMR

Kinesis Batch ECS

GPU CPU IoT Mobile

Apache MXNet Caffe 2 Theano PyTorch CNTKTensorFlow

Vision Amazon Rekognition

Chat Amazon Lex

Speech Amazon Polly

Machine Learning in the hands of every developer

Early detection ofdiabetic complications

New Pinterest Lens mobile app uses TensorFlow to let

users find pins based on the pictures they take

Real time, per pixel object segmentation

Thousands of Amazon Engineers Focused on Machine Learning

https://reinvent.awsevents.com/

27 November – 1 December Las Vegas, NV

aws.amazon.com/blogs

aws.amazon.com/new

@AWScloud @AWS_UKI

Thank You!

@IanMmmm

Ian Massingham, Worldwide Lead, AWS Evangelism