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Introducing Amazon RDS for PostgreSQL (DAT210) | AWS re:Invent 2013
 

Introducing Amazon RDS for PostgreSQL (DAT210) | AWS re:Invent 2013

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AWS customers have been asking us for Amazon RDS for PostgreSQL, and we’re excited to announce its immediate availability. Learn how you can offload the management of your PostgreSQL database ...

AWS customers have been asking us for Amazon RDS for PostgreSQL, and we’re excited to announce its immediate availability. Learn how you can offload the management of your PostgreSQL database instances to Amazon RDS using automated backups and point-in-time recovery, Multi-AZ deployments for high availability, and provisioned IOPS for fast and predictable performance. Also learn how to take advantage of familiar PostgreSQL features such as PostGIS with Amazon RDS for PostgreSQL.

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    Introducing Amazon RDS for PostgreSQL (DAT210) | AWS re:Invent 2013 Introducing Amazon RDS for PostgreSQL (DAT210) | AWS re:Invent 2013 Presentation Transcript

    • DAT210 – Introducing Amazon RDS for PostgreSQL Srikanth Deshpande - Senior Product Manager, AWS Nick Hertl – Software Development Manager, AWS Gabe Arnett – Senior Director, Moody’s Analytics November 14, 2013 © 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
    • Amazon Relational Database Service RDS is a managed relational database service that is simple to deploy, easy to scale, reliable, and cost-effective Choice of Database Engines Managed Service Easy to Scale and Operate High Performance High Availability Amazon Relational Database Service (RDS)
    • Backups and Disaster Recovery
    • Push-Button Scaling
    • Multi-AZ Deployments
    • Security Internet VPC IAM
    • DB Parameter Groups Filter=“connection” {DBInstanceClassMemory/12582880}
    • Amazon RDS for PostgreSQL • Database version: PostgreSQL 9.3.1 • Includes valuable Amazon RDS functionality – – – – – – Fast deployment Backups and point-in-time recovery Snapshots and restore Compute and storage scaling Multi-AZ Provisioned IOPS 8
    • Launching a Postgres DB Instance
    • Select Production Use (or not)
    • Instance Details
    • Additional Configuration
    • Management Options
    • Running Instance
    • Connecting
    • Permissions superuser role (Postgres) rds_superuser role (RDS provided) Load and use extensions View and kill sessions Create tablespace Assign replication role …
    • Extensions • PostGIS available • rds.extensions parameter: – – – – – – – – – – btree_gin btree_gist chkpass citext cube dblink dict_int dict_xsyn earthdistance fuzzystrmatch – – – – – – – – – – hstore intagg intarray isn ltree pgcrypto pgrowlocks pg_trgm plperl plpgsql – – – – – – – – – pltcl postgis postgis_tiger_geocoder postgis_topology sslinfo tablefunc tsearch2 unaccent uuid-ossp
    • High Performance 16,500+ Read and 8,500+ Write = 25,000+ IOPS
    • Getting Started • Launch an instance from AWS Management Console • Configure network • Load extensions • Export from existing database using pg_dump • Import to RDS using pg_restore
    • RDS PostgreSQL Gabe Arnett, Senior Director, Moody’s Analytics November 14, 2013 © 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
    • • Moody’s Analytics offers unique tools and best practices for measuring and managing risk through expertise and experience in credit analysis, economic research, and financial risk management. • Product offerings include leading-edge software, advisory services, and credit and economic research. • A subsidiary of Moody's Corporation (NYSE: MCO), which reported revenue of $2.7 billion in 2012, employs approximately 7,200 people worldwide and maintains a presence in 29 countries.
    • Legacy Platform Calculation Engine
    • Job 1 (4x daily) 1x monthly 1x daily Source 1 4x daily App Server 1 Source 2 4x daily Sybase 1 1x daily Routine 1 EDF Front End Db’s (11 servers) excl EJV 1x daily Source 3 Routine 2 Sybase 2 Pasta, anyone? Data Transfer App Routine 3 Source 4 1x daily Legacy App Db Routine 4 Oracle Source 5 Source 6 Job 2 (4x daily) Job 3 (1x daily) Source 7 Sybase 3 App Server 2 Ftp server MS SQL Server Source 8 Job 4 (1x daily) App Server 3 Vendor Data Engine / Calculator Standalone C++ App DataPortal
    • Overhaul
    • Summer Fun External Data Sources Write Master (AZ 1) ETL Cluster WAL Read Replica 1 (Warm Standby AZ 2) Cascading Replication Calculation Engine (reads from RR2 and writes results to WM) Read Replica 2 (AZ 1) Amazon Simple Storage Service
    • Pros • We learned a tremendous amount and could probably write a solid blog post or whitepaper • No cost other than infrastructure • Support/maintenance tasks now very reasonable and can be done with existing resources without incurring additional costs
    • Cons • Lots of time spent finding the write configurations, trial and error, testing and more testing • I have to convince really talented Java, Python, and .NET developers that they have to be PostgreSQL system admins • We are an enterprise, and as such I have to have an enterprise level of support
    • RDS PostgreSQL External Data Sources Write Master (Multi-AZ) ETL Cluster Snapshot Copy future Warm Standby Region 2 Calculation Engine (Reads from RR2 and writes results to WM) Read Replica Amazon Simple Storage
    • RDS PostgreSQL External Data Sources Write Master (Multi-AZ) ETL Cluster Snapshot Copy future Warm Standby Region 2 Calculation Engine (Reads from RR and writes results to WM) Read Replica Amazon Simple Storage
    • Why Amazon RDS PostgreSQL? • Achieve the same performance as existing setup on Amazon EC2, if not better, in a matter of minutes • We get built-in backup/recovery/replication/fault tolerance/multi-AZ • More robust operational support built in, and my developers can get back to the business of development
    • Up and Running Self-Managed(hours) RDS PostgreSQL(minutes) • • • • • • • • • Launch Amazon EC2 w/EBS Mount and Raid0 Amazon EBS Install PostgreSQL Move data and logs Edit .conf files Create users Load/Use DB Create snapshot, and then… • • • • Add/Edit CIDR/IP block to security group (pg_hba.conf) Edit DB parameter group to apply configuration settings (postgresql.conf) Launch RDS instance Load/Use DB Sit back and monitor or let Amazon CloudWatch do it for us…
    • Backup/Retention • Single-click backup policy upon creation • No schedule to implement or forget • Snapshots are easy to find – All easily found in the AWS Management Console and searchable • One-click restore to point in time = AWESOME!!!
    • Monitoring • Amazon CloudWatch metrics alongside instance details – A challenge to find and consolidate all the EBS volumes + EC2 instances • Logs are in the console – Not fun to dig through the logs, assuming we actually had that kind of time • Event subscriptions for faults – Extra pro-active protection
    • Scale and Redundancy • At launch, RDS PostgreSQL is multi-AZ enabled with a click – We had to spin up a second instance and then configure WAL and hope and pray – Bit of configuration and tuning to get the correct performance for this without impacting write performance and ensuring near real-time reads – Lossless factor is a risk if the write master fails
    • Next • Additional legacy data platforms • Extending PostgreSQL – Developing key/value store for near real-time data ingestion – Integrating with Solr – Front end datamart • Redshift for BI use cases
    • Please give us your feedback on this presentation DAT210 As a thank you, we will select prize winners daily for completed surveys!