Hosted PostgreSQL

Mike Fowler (mike.fowler@claranet.uk)
Hosted PostgreSQL

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Senior Site Reliability Engineer in the Public Cloud
Practice of claranet
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Background in Software Engineering, Systems
Engineering, System & Database Administration
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Contributed to several open source projects (YAWL,
PostgreSQL & Terraform)
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Been using PostgreSQL since 7.4
About Me

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Hosted PostgreSQL
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Overview of public cloud hosting options
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Database migration strategies
Overview

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Your database somewhere else
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A managed service
– Some providers offer full DBA support
– Cloud providers give only the infrastructure
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Typically provisioned through an API or GUI
– i.e. a self-service environment
What is hosted PostgreSQL?

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Reduces adoption costs
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Installation & configuration is already done
– Generally sane defaults, some tuning often required
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Needn’t worry about physical servers
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Opex instead of Capex
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Most routine DBA tasks are done for you
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Easier to grow
Benefits of Hosted PostgreSQL

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Less control
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Latency
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Some features are disabled
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Migrating existing databases is hard
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Potential for vendor lock-in
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Resource limits
Drawbacks of Hosted PostgreSQL

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We’ll look only at Public Cloud offerings
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Current major offerings
– Amazon Relation Database Service (RDS)
– Heroku
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Future major offerings
– Amazon Aurora
– Google Cloud SQL
– Microsoft Azure
Hosting Options

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PostgreSQL 9.3.12 – 9.6.2 supported
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Numerous instance types
– Costs range from $0.018 to $4.97 per hour
– Select from 1 vCPU up to 32 vCPUs, all 64-bit
– Memory ranges from 1GB to 244GB
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Flexible storage options
– Choose between SSD or Provisioned IOPS
– Up to 6TB with up to 30,000 IOPS
Amazon RDS

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High availability multi-availability zone option
– Synchronous replica
– Automatic failover (~2 minutes)
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Up to 5 read-only replicas (asynchronous replication)
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Configurable automatic backups with PITR
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Monthly uptime percentage of 99.95 per instance
– Allows for approximately 22 minutes downtime
Amazon RDS

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Supports PostgreSQL 9.3, 9.5, 9.6 & 9.6
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Simpler pricing based on choice of tier ($0-8.5k pcm)
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Tier dictates resource limits
– Maximum number of rows (Hobby only)
– Cache size (1GB - 240GB)
– Storage limit (64GB - 1TB)
– Connection limit (120 - 500)
– Rollback (4 days – 1 week)
Heroku

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Fork & Follow
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Some of your data may end up in the US
– Logs (can be blocked at creation time)
– Snapshots & Dataclips
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Not possible to replicate out
– No permission for Bucardo, Londiste & Slony
– Remote slave is prohibited
– Only way is dump & restore
Heroku

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Currently in open preview
– Largely free to use but no SLA
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Compatible with PostgreSQL 9.6
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Up to 2x throughput of conventional PostgreSQL
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Up to 16 read replicas with sub-10ms replica lag
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Auto-growing filesystem up to 64TB
– Filesystem is shared between 3 availability zones
Amazon Aurora

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Currently in Beta (no SLA)
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Only supports PostgreSQL 9.6
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Only available in Iowa, no replication support
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Posed to be a serious rival to RDS
– Billing per minute
– Automatic scaling of filesystem
– Similar variety of instance types
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Minimal extensions but includes PostGIS
Google Cloud SQL

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Currently in preview (no SLA)
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Supports PostgreSQL 9.5 & 9.6
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Replication is seamless
– Automated failover
– PITR
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Selectable compute units
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Supports some extensions including PostGIS
Microsoft Azure

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Dump & Restore
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Replication failover
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PITR + Logical decoding
Migration Strategies

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Simplest strategy
– Perceived as low risk for data loss
– Less “moving parts”
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Just a pg_dump & pg_restore
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Downtime is function of database size
Dump & Restore

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Move historic data ahead of time
– Opportunity to clear out unused data
– Consider introducing partitions
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Consider moving the dump closer to the target
– e.g. Upload to EC2 instance in the same region as
the RDS instance and run pg_restore from there
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Over provision resources
– Gives higher throughput during data load
– Downscale once operational
Strategies to Minimise Downtime

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No one supports external masters!
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Trigger based replication failover
– Slony, Londiste & Bucardo
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Can be used on most any version of PostgreSQL
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Some restrictions apply
– DDL is not supported
– Rows must be uniquely identifiable
Replication Failover

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Presents some risk to production environment
– Initial overhead of replicating each table
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Gradually add tables to the configuration to
spread the load
– Per-transaction overhead
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Write latency to remote slave
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Heavy write workload could lead to high
replication lag
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This also works to replicate out of RDS but not Heroku
Replication Failover

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Most involved approach, least downtime
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Combines point-in-time recovery with the changes
captured by logical decoding to create a replica
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Need to be running at least PostgreSQL 9.4 with WAL
level logical and have WAL archiving configured
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DDL not supported, still need unique rows
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Recommend barman for managing WAL
http://www.pgbarman.org/
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Recommend decoder_raw as logical decoding plugin
github.com/michaelpq/pg_plugins/tree/master/decoder_raw
PITR & Logical decoding

1. Create a logical replication slot
SELECT * FROM
pg_create_logical_replication_slot
('logical_slot', 'decoder_raw');
2. Note the transaction ID (catalog_xmin)
SELECT catalog_xmin FROM
pg_replication_slots WHERE slot_name =
‘logical_slot’;

3. Perform a barman backup
$ barman backup master
4. Perform a barman PITR
$ barman recover –target-xid
(catalog_xmin - 1) master latest
5. Start database and verify correct recovery

5. Perform pg_dump on the readonly barman node
6. Restore to public cloud
7. Read output of logical decoding and write to cloud

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Hosted PostgreSQL gives you high performance
PostgreSQL without the hassle of hardware,
maintenance and configuration
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Opex instead of Capex
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Consider the limitations of your intended platform
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There are multiple options for migration
Summary

Hosted PostgreSQL

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