As PostgreSQL has made way into business critical applications, many customers who are using Oracle RAC for high availability and load balancing have asked for similar functionality for using PostgreSQL. In this Hangout session we would discuss architecture and alternatives, based on real life experience, for achieving high availability and load balancing functionality when you deploy PostgreSQL. We will also present some of the key tools and how to deploy them for effectiveness of this architecture.

1. Building Scalable And
Highly Available
Postgres Cluster
Postgres based High Availability Setup with Load Balancing
and no Single Point of Failure

2. A typical Cluster Setup
• Load Balancing between two or more nodes
• High Availability- If one of the nodes goes down the other
node Takes over the load
• The failover does not involve any configuration changes in
application

3. PostgreSQL – Worlds Most Advanced Open Source
Database
• Built on top of the same Relational Database Fundamentals that
is basis of all Modern day relational databases e.g. Oracle, DB2,
SQL Server
• Has advanced Streaming Replication features
• Point-in-Time Recovery capabilities
• Multi Version Concurrency control (conceptually similar Oracle’s
undo tablespace concept)
• ANSI-SQL Support
• noSQL datatypes support e.g. JSON, hstore, JSONB

4. Architectural Overview of PostgreSQL

5. PostgreSQL – Postgres Plus Users

6. High Availability Options in Postgres
• OS level (shared-disk) Clustering – e.g. Red Hat Cluster Suite
• A drawback is only one of the nodes is active at a time
• Streaming Replication
• A drawback is that failovers/node promotion is not automated
• The replica can take up read load but the logic to distribute the
read queries has to be built into application
• Next few slides will show some popular architectures we
have seen and limitations which one ideally faces

7. PostgreSQL Streaming Replication
• WAL (transaction log) based Replication
• Replication can be synchronous or
asynchronous
• Shared nothing architecture
• No network or locking issues for global
shared cache
• No disk contention since each instance
has its own disk
• Can be setup without Archiving of WAL
files
• No disk level mirroring needed
• Standby can accept read queries

8. Load Balancing with pgpool
• Read query is automatically load
balanced
• pgpool can detect failover and start
sending Read/write to surviving
node
• Node promotion is not automated,
unless pgpool is used for performing
failovers and specific settings of
pgpool are set properly
• No proper safe guarding against
split brain situation
• pgpool becomes a single point of
failure

9. Automated Failover with EDB Failover Manager
• Automated Failover and Virtual IP
movement makes it easier with 0
configuration changes required at
application end
• Handles the split brain situation
with witness node
• More than 2 nodes can be added
• No load-balancing of read queries

10. • Failover can be managed by open
source components – e.g. Pacemaker
and Corosync
• Replication always happens using the
Virtual IP which will shift over to the
2nd node upon promotion
• There is a separate Virtual IP used for
application access
• It is suggested to use 3 different LAN –
for pacemaker, replication and
application access
• No Load balancing of read queries
Alternative Open Source Architecture

11. EDB Failover Manager + pgpool Cluster
• EDB Failover Manager manages the
failover
• pgpool is used for load balancing
• pgpool can be installed on the same
machine as failover manager
witness node
• Still does not solve the problem of
pgpool being a Single Point of
Failure

12. EDB Failover Manager with pgpool HA
• EDB Failover Manager manages the failover of
database
• pgpool has it own HA which only manages failure
of pgpool
• pgpool also manages a virtual IP which can shift to
2nd pgpool node if there is a failover
• No split brain at pgpool level as at a time only one
node will have virtual IP and hence only one node
will accept connection
• Remember that pgpool is not deciding on DB
failover
• To reduce number of servers, each DB node can
host a pgpool
• but still pgpool will only take care of pgpool failovers
• This means Primary DB and active pgpool can be on two
different servers
• This architecture can be further scaled to work
with more underlying replica/standby DB nodes

13. 3 Node Cluster
• Each of the Servers will have
• Postgres Database Instance
• EDB fm agent
• pgpool
• One the instance is master an replicates to
other two
• EDB fm agents will take care of failover of
databases
• Each of the pgpool is talking with each other via
watchdog
• If pgpool on Primary server goes down the
pgpool on the 2nd server will take over and it
can talk to Master (without changing the role of
Master DB), and 2 standby
• Cons
• A little Complicated to setup (and comprehend)
• Primary DB server has more processes running
and hence one may have performance concerns
• Pros
• Scalable and more nodes can be added

14. Consideration of Application Clusters
• Today most of the applications have their own clusters for
both High Availability as well as Load Balancing
• 2 or 3 node JBOSS setup which is talking to a single
Database is very common
• Or a DB Cluster (the DB level Cluster is abstracted from
Application Layer)
• With this setup it makes more sense to have a pgpool server
installed on the application server itself so that each
Application server has its own pgpool

15. pgppol with Application Cluster
• Pros-
• More nodes can be easily
added for both HA as well
as Failover Manager
• Cons-
• One issue in this
architecture is service
level failure of pgpool is
not taken care of

16. • Failover is managed by Linux-HA
components – Pacemaker and
Corosync
• Replication always happens using the
Virtual IP which will shift over to the
2nd node upon promotion
• pgpool is used for load balancing
• pgpool be installed on a stand-alone
server or on application server or can
be setup as pgpool-HA
• Cluster with more than 2 nodes can
be setup using pacemaker and
corosync
Alternative Open Source Architecture

17. Benefits of Postgres Cluster
• More stand-by servers can be added and pgpool can be
configured for load balancing across more nodes in runtime
• More stand-by being added can also be added to
synchronous standby list making sure data redundancy is
being maintained on at least one servers
• Standby servers being added can also be added to EDB FM
cluster without bringing down the cluster/switching roles
• Works in tandem with Virtualization and Provisioning on the
fly

18. Ashnik’s Approach
• To build enterprise class solutions
• Provide an alternative to clustering features which has
created a lock-in for Enterprise Customers
• Consulting services to help customers build architectures
tailored for organization specific requirements
• Consulting and implementation services helping customers
migrate their databases to Postgres without compromising
on Availability and Recoverability of the setup