Esta sesión está enfocada en mostrar cómo las empresas pueden optimizar sus recursos a través de las soluciones basadas en la nube, poniendo foco en la diferenciación, la innovación y reducción de riesgos en la infraestructura. Por Ricardo Rentería de Amazon

2. ~$14B Revenue Run Rate
(trailing 12 months , as of Q4 2016)
47% YoY Growth
( Q4 2015 v s Q4 2016)
AWS is the fastest enterprise IT vendor to
reach a $10 billion run-rate

5. 70 Global
CloudFront PoPs

7. Most Robust, Fully-Featured
Technology Infrastructure Platform
HYBRID ARCHITECTURE
Data Backups
Integrated App
Deployments
Direct
Connect
Identity
Federation
Integrated Resource
Management
Integrated
Networking
VMware
Integration
MARKETPLACE
Business
Apps
Databases
DevOps
Tools
NetworkingSecurity Storage
Business
Intelligence
INFRASTRUCTURE
Availability
Zones
Points of
Presence
Regions
CORE SERVICES
Compute
VMs, Auto-scaling, Load
Balancing, Containers, Cloud
functions
Storage
Object, Blocks, File,
Archivals,
Import/Export
Databases
Relational, NoSQL,
Caching, Migration
CDN
Networking
VPC, DX,
DNS
Access Control
Identity
Management
Key Management
& Storage
Monitoring
& Logs
SECURITY & COMPLIANCE
Resource &
Usage Auditing
Configuration
Compliance
Web application
firewall
Assessment and
reporting
TECHNICAL & BUSINESS SUPPORT
Support
Professional
Services
Account
Management
Partner
Ecosystem
Solutions
Architects
Training &
Certification
Security &
Billing Reports
Optimization
Guidance
ENTERPRISE APPS
Backup
Corporate
Email
Sharing &
Collaboration
Virtual
Desktops
IoT
Rules
Engine
Registry
Device
Shadows
Device
Gateway
Device
SDKs
DEVELOPMENT & OPERATIONSMOBILE SERVICESAPP SERVICESANALYTICS
Data
Warehousing
Hadoop/
Spark
Streaming Data
Collection
Machine
Learning
Elastic
Search
Push
Notifications
Identity
Sync
Resource
Templates
One-click App
Deployment
Triggers
Containers
DevOps Resource
Management
Application Lifecycle
Management
API
Gateway
Transcoding
Queuing &
Notifications
Email
Workflow
Search
Streaming Data
Analysis
Business
Intelligence
Mobile
Analytics
Single Integrated
Console
Mobile App
Testing
Data
Pipelines
Petabyte-Scale
Data Migration
Database
Migration
Schema
Conversion
Application
Migration
MIGRATION

8. Big Data
Technologies and techniques for
working productively with massive
amounts of data at any scale in
either batch or real-time.

9. The Cloud Was Built for Big Data

10. The AWS Approach
• Flexible - Use the best tool for the job
• Data structure, latency, throughput, access patterns
• Low Cost - Big data ≠ big cost
• Scalable – Data should be immutable (append-only)
• Batch/speed/serving layer
• Minimize Admin Overhead - Leverage AWS managed services
• No or very low admin
• Be Agile – Fail fast, test more, optimize Big Data at a lower cost

11. AWS Big Data Platform
EMR EC2
Glacier
S3
Import Export
Kinesis
Direct Connect
Machine LearningRedshift
DynamoDB
AWS Database
Migration Service
Collect Orchestrate Store Analyze
AWS Lambda
AWS IoT
AWS Data Pipeline
Amazon Kinesis
Analytics
Amazon
SNS
AWS Snowball
Amazon
SWF
AmazonAthena
Amazon
QuickSight
Amazon AuroraAWS Glue

12. AWS Analytics Services Business Growth NDA
Fastest growing segment in
.. 2014
.. 2015
.. 2016

13. Kinesis: Stream Processing
• Real-time stream processing
• High throughput; elastic
• Highly available; data replicated across multiple
Availability Zones with configurable retention
• S3, Redshift, DynamoDB Integrations
• Kinesis Streams for custom streaming applications;
Kinesis Firehose for easy integration with Amazon S3
and Redshift; Kinesis Analytics for streaming SQL
“Real-Time Analytics workloads is becoming
mainstream”
Amazon
Kinesis

14. Structured Data Processing
• Petabyte-scale relational, MPP, data warehousing
• Fully managed with SSD and HDD platforms
• Built-in end to end security, including customer-
managed keys
• Fault tolerant. Automatically recovers from disk and
node failures
• Data automatically backed up to Amazon S3 with
cross region backup capability for global disaster
recovery
• Over 140 new features added since launch
• $1,000/TB/Year; start at $0.25/hour. Provision in minutes;
scale from 160GB to 2PB of compressed data with just
a few clicks
Amazon Redshift

15. Example enterprise customers by vertical NDA

16. Semi-structured / Unstructured Data Processing
• Hadoop, Hive, Presto, Spark, Tez, Impala etc.
• Release 5.3.1: Hadoop 2.7.3, Hive 2.1.1, Spark 2.1.0, Zeppelin, Presto, HBase
1.2.3 and HBase on S3, Phoenix, Tez, Flink.
• New applications added within 30 days of their open source release; most
current distribution in the segment
• Fully managed, autoscaling clusters with support for on-demand and
spot pricing
• Support for HDFS and S3 filesystems enabling separated compute
and storage; multiple clusters can run against the same data in S3
• HIPAA-eligible. Support for end-to-end encryption, IAM/VPC, S3
client-side encryption with customer managed keys and AWS KMS
Amazon EMR

17. Internal only – do not distribute
Serverless Query Processing
• Serverless query service for querying data in S3 using standard SQL,
with no infrastructure to manage
• No data loading required; query directly from Amazon S3
• Use standard ANSI SQL queries with support for joins, JSON, and
window functions
• Support for multiple data formats include text, CSV, TSV, JSON, Avro,
ORC, Parquet
• Pay per query only when you’re running queries based on data
scanned. If you compress your data, you pay less and your queries
run faster
Amazon
Athena

18. Business Intelligence
• Fast and cloud-powered
• Easy to use, no infrastructure to manage
• Scales to 100s of thousands of users
• Quick calculations with SPICE
• 1/10th the cost of legacy BI software
Amazon
QuickSight

19. Gracias
rrrenter@amazon.com