¿Quién es Amazon Web Services?

¿Quién es Amazon Web Services?

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  ~$14B Revenue RunRate (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
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  70 Global CloudFront PoPs
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  Most Robust, Fully-Featured TechnologyInfrastructure 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
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  Big Data Technologies andtechniques for working productively with massive amounts of data at any scale in either batch or real-time.
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  The Cloud WasBuilt for Big Data
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  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
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  AWS Big DataPlatform 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
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  AWS Analytics ServicesBusiness Growth NDA Fastest growing segment in .. 2014 .. 2015 .. 2016
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  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
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  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
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  Example enterprise customersby vertical NDA
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  Semi-structured / UnstructuredData 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
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  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
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  Business Intelligence • Fastand 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
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  Gracias rrrenter@amazon.com