High-Availability comes with some impact on your architecture choices, in particular when applied to RDBMS such as Postgres. One such impact is the idea of a failover. When implementing database HA, it is usually expected that both the service and the data are maintained available in the face of operational faults. The most common way to implement resilience includes automated (or manual) failover, where a new primary is elected among a list of standby nodes.
In other words, as soon as Postgres High-Availability is implemented, the roles of your Postgres nodes are dynamic. The fact that a given node is a primary or a standby at any given point in time ceases to be relevant to understanding your architecture. In fact, the only thing that’s now given about the role of a node is that it will change. Otherwise you don’t have failover capability, and then, you probably don’t have HA in the first place, right?
In this article we are going to try and understand what having dynamic roles for Postgres nodes in a HA system means.
Table of Contents
Postgres HA setup: nodes and roles
Postgres instances default to being independent primary nodes. When
provisionning a standby node a specific setup is required, that depends on
Postgres version. Starting with Postgres 12 a
standby.signal file is
required, and before that it used to be the
Some of the Postgres configuration file settings only apply to the recovery
mechanisms that are used either when doing PITR or when running a standby
node. Those settings used to be managed in their own configuration file, and
from Postgres 12 onwards those settings can be set in the main
So with recent versions of Postgres, the exact same
postgresql.conf can be
shipped to all the nodes. The presence of the
standby.conf file determines
if a node is asked to start as a primary node or as a standby node.
Reversing that choice is not easy with Postgres. In most cases
is necessary, and that in turn requires that the instance was shutdown
With that we can see that in Postgres core itself the idea that an instance role should be dynamic is not well ingrained in the software. That’s the first reason why a failover management software is needed.
Roles are dynamic
When implementing Postgres HA, the only reason why standby nodes are provisioned and deployed is so that they may be elected as a primary if needed. So by definition, the role of a specific node is dynamic. A node could be a server, a VM, a pod, a container, or maybe even something else.
At the initial provisioning stage, one node must be selected as the current
primary, and that’s where we run
pg_ctl initdb. Other nodes in the same
cluster — or formation, as the cluster name is overloaded in the
Postgres glossary already — are going to be standby nodes and initialised
Then if the current primary node fails or becomes unavailable for a long
enough time to trigger a topology change, one of the standby nodes should be
promoted to be the new primary. It is possible to use
pg_ctl promote to
implement this step, and the Postgres setup must also be edited so that a
further restart down the line allows the node to restart as a primary still.
Also the other standby nodes must be reconfigured to use the new primary as
their upstream replication source. Editing the
primary_conninfo setting in
Postgres requires a restart until Postgres 12 included, and can be changed
with a reload starting with Postgres 13.
When the former primary node gets back to being available — maybe that was
just a spurious reboot after all, or a maintenance operation that didn’t go
by the book, as it happens sometimes — well then it may re-join the
formation as a standby to the current primary. For that to happen it’s
necessary to use
pg_rewind, and in some cases even this tool will fail to
re-join. In that case it might be necessary to resort to using
pg_basebackup or another means (such as restoring a backup) to fetch a
full copy of PGDATA all over again.
When all of those options are implemented correctly in some automation layer, then we have Postgres nodes with actual dynamic roles, rather than just the architectural concept that roles should be dynamic.
To get started with a failover automation that implements the notion of dynamic roles, I recommend playing with pg_auto_failover. Disclaimer: I am the main developer of this tool, so that I know it well enough to trust it with failover orchestration in production.
Now here is a short list of points that may seem obvious to veterans of HA system design, or to those of you with memories of production outages. It might be still good to go over some of the basics to help readers new to HA planning getting started.
As outlined before, the only reason why we provision and maintain standby nodes in an HA system is for those nodes to take over the primary role when the current primary node is not available. Not only will that situation happen, but also we are deploying standby nodes as a way to plan for our production to tolerate such a fault.
After all High Availability is mostly just a fancy way to say Fault Tolerance, and in many cases it boils down to Business Continuity.
So if the standby nodes are being provisioned with the single purpose of taking over the primary role, then the nodes must be as close as possible in specifications to the current primary. Each one of the HA standby nodes is expected to become a primary node sometime, so it must have the capacity to handle whatever workload the current primary is handling.
It means in particular that you want the standby nodes to have the following properties identical to the primary:
- CPU power (number of sockets, cores, speed of each of them, bus speed, etc)
- RAM specifications, bus speed, access latency, amount of RAM
- Disk space available for the data set
- Network bandwith and latency to the application nodes
- Same configuration (kernel, file systems, Postgres tuning, etc)
- Same security rules (firewall, Postgres HBA, etc)
- And probably more elements should be added to this list to make it comprehensive.
We can stress out the Postgres HBA file in that list. Connection privileges must be opened in the same way for the application to be able to connect to the new primary when a failover has happened, of course, and also the other standby that you may have must be able to connect to the new primary too.
When listed here in an article that focuses on High Availability roles and their dynamic nature, I certainly hope all of this sounds obvious. Well, as obvious as it sounds, the most recent on-call situation I was involved in where things went wrong because the newly elected primary was not comparable to the former primary node, and then the application workload was slowed down a lot… was last week.
So while I agree that it sounds as obvious as preventing File System is Full on your database instances and their WAL subsystem, well, we still have to talk about it apparently.
Long term maintenance of production systems
Production systems are sometimes referred to as “legacy systems”, and they tend to require some maintenance and even hardware upgrades after a while. Nowadays, the “hardware upgrade” might be as easy as an automated deploy of a new fleet of newer spec nodes (VMs, pods, containers, what have you).
Still, when upgrading the capabitilies of the system, then we have to deal with an heterogeous set of nodes. What then? How do we respect the previous constraints about every node in the HA system being able to provide with the same capacity, to handle the same load?
When using pg_auto_failover to for implementing your Postgres HA systems, simply make sure that any node that has a non-zero candidate priority is capable of running your actual production workload.
When upgrading your nodes to more powerful and capable systems, simply adjust the candidate priority of the older nodes to zero when the new nodes are ready, so that pg_auto_failover will refrain from putting the lesser capable systems in production as primary nodes.
And also remember that you can use pg_autoctl perform promotion to smoothly switch over to a new primary when it’s ready to take over. Then it is also possible to use pg_autoctl drop node on the previous generation of nodes to implement their end-of-life cycle.
Because proper standby nodes are as expensive as the current primary node, a negociation might arise where those nodes somehow need to pull their own weight. Being available when the current primary isn’t anymore doesn’t cut it.
The cost of the standby nodes should be compared to the cost of an interruption of the current primary for the business, possibly for a long time while it’s being rebuilt from pieces — hardware, new VMs that need provisioning from restoring backups, etc. A common alternative consists of comparing the price of operating the standby nodes with the fact that most of their processing capabilities are unused.
As a result, some of the production load might be distributed to the almost idle standby nodes. In the case when a single standby is part of the production system, and when some of the workload is routed to it, such as batches and reporting queries and other analytics or at least read-only SQL traffic, it looks like a good use of expensive resources.
Now, when the current primary becomes faulty, then the secondary is elected and promoted as expected… and now as a single node it must be capable of handling both the primary workload and also the reporting read-only standby traffic.
In many cases that won’t fly. If your application have an easy way to turn off the read-only traffic for a while, the duration when all you have left is a single Postgres node, then it might still be a good trade-off. It’s not often that I see that kind of sophistication in the wild though.
The approach I generally see is where monitoring and observability is used to somehow “ensure” that a single node would be able to take on the entire workload. Well okay then… but why handling the load-balancing complexities in that case?
Finally, when using pg_auto_failover to manage your Postgres nodes, setting the candidate priority of some of the standby nodes while still allowing them to participate in the replication quorum might be a good trade-off. The nodes can now participate in the data safety of your HA system while never being elected as the new primary. See our sample architecture with three standby nodes, one async documentation for more details.
Application side HA and Connection Pooling
Another aspect of Postgres HA and failovers that needs to be part of this article is the client-side aspect of HA. For an application to benefit from server-side fault tolerance, it must be ready to lose its connections to the current primary (when this one fails) and reconnect to the new primary (when that one is ready).
The Postgres technology is named “Hot Standby” because at promotion time the current connections and read-only traffic is allowed to continue. That’s a very nice feature which in this context means that the application may connect early to the newly elected primary without causing too much trouble.
Then, in order to avoid the whole connection lost thing, in some cases an external connection pooler can be used. Those pieces of infrastructure can usually be reloaded online with the new primary node as the connection target.
There is a catch though: an SQL connection (or session really) is stateful. SQL provides session level objects and features such as prepared statements, temporary tables, cursors, or LISTEN/NOTIFY. So if you’re using any of the session level SQL features then reconnecting to the new primary node can not be made transparently. The application is going to expect some kind of state from its SQL connection, and will not find it again.
I didn’t provide an exhaustive list of the session level SQL features here. pgbouncer features documentation page maintains one if you need to read it.
So the idea that for Postgres HA the roles are dynamic must find its way up to your application code.
Disaster Recovery Setup
Finally, implementing Postgres High Availability requires implementing availability of the data whatever happens. This is achieved via the notion of an “archive”, which is documented as a concept in Postgres itself.
While it is possible to implement archiving using the provided Postgres hooks and some scripting around, please consider using one of the proven robust implementations for archiving. The classic projects that people keep saying some good things about even after running them in production for a while are WAL-G, its predecessor WAL-E, then pgbackrest, and then barman.
Using those projects it is possible to implement a Postgres archive either on a local storage facility — maybe using the Open Source solution min.io and its Cloud Storage compatible API — or on a Cloud Storage of your choice.
When browsing the docs and prototyping your Disaster Recovery Setup, make sure to understand what happens during and after a failover. In my experience, the Open Source products I listed above to implement DR entirely miss the point; at least in the docs. Again, the only thing that is known for sure about the current primary node is that down the road, the primary role is going to be assigned to another node in the system.
Make sure your DR setup knows about this. They’re not good at documenting the steps that need to be implemented, if any, when this happens. That’s unfortunate, and I wish this would change. If you’re reading this and contribute to any of the DR systems I listed, can you think about how to cover the point that any node that participates in some HA system must have a dynamic role?
Automated Failover and HA tooling
While it is possible to implement HA yourself from scratch, the planning for a full failover with minimal (and controlled) data loss and fast enough service failover is ridden with traps that are not easy to foresee, so it’s advised to use a software that’s known to have taken care of the proper steps for you.
As the main author and contributor to pg_auto_failover, that’s the software I trust and recommend.
The notion that roles are dynamic is a strong focus of the whole design of pg_auto_failover. In particular the current primary is not assumed, it’s an information that is maintained through the life time of a formation — that’s pg_auto_failover glossary for what some people may be used to name a cluster.
Remember that the entire application stack must be designed for the node roles to be dynamic in nature if you need some kind of Fault Tolerance.