© 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.

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

Amazon Relational Database Service RDS is a managed relational database service that is simple to deploy,

easy to scale, reliable, and cost-effective

Managed Service

Easy to Scale and Operate

Choice of Database Engines

High Availability

High Performance

Amazon Relational Database Service (RDS)

Backups and Disaster Recovery

Push-Button Scaling

Multi-AZ Deployments

Security Internet

IAM

VPC

DB Parameter Groups

{DBInstanceClassMemory/12582880} Filter=“connection”

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

© 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.

RDS PostgreSQL

Gabe Arnett, Senior Director, Moody’s Analytics

November 14, 2013

• 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

DataPortal

Source 2

Sybase 1

Sybase 2

Sybase 3

Oracle

Source 3

Source 7

Source 4

Source 8

Source 5

Source 6

Source 1

Ftp server

Routine 2

Routine 3

excl EJV

Legacy App Db

4x daily

EDF

Data

Transfer

App1x daily

1x daily

4x daily

1x daily

Front End Db’s

(11 servers)

MS SQL Server

Routine 4

Standalone

C++ App

Vendor

Data

Engine /

Calculator

1x monthly

Routine 11x daily

App Server 2

Job 2

(4x daily)

Job 3

(1x daily)

App Server 3

Job 4

(1x daily)

App Server 1

Job 1

(4x daily)

Pasta,

anyone?

Overhaul

Write Master (AZ 1)

Read Replica 1

(Warm Standby AZ 2)

Read Replica 2 (AZ 1)

WAL

Cascading Replication

ETL Cluster

Calculation Engine

(reads from RR2 and writes results to WM)

External Data Sources

Amazon Simple Storage

Service

Summer Fun

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

Write Master (Multi-AZ)

Read Replica

ETL Cluster

Calculation Engine

(Reads from RR2 and writes results to WM)

External Data Sources

Amazon Simple Storage

RDS PostgreSQL

Warm Standby

Region 2

Snapshot Copy

futu

re

Write Master (Multi-AZ)

Read Replica

ETL Cluster

Calculation Engine

(Reads from RR and writes results to WM)

External Data Sources

Amazon Simple Storage

RDS PostgreSQL

Warm Standby

Region 2

Snapshot Copy

futu

re

• 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

Why Amazon RDS PostgreSQL?

Up and Running

Self-Managed(hours)

• 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…

RDS PostgreSQL(minutes)

• 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

As a thank you, we will select prize

winners daily for completed surveys!

DAT210