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Autoscaling

Vertical autoscaling for a fleet of postgres instances running in a Kubernetes cluster.

For more on how Neon's Autoscaling works, check out https://neon.tech/docs/introduction/autoscaling.

Development status

Autoscaling is used internally within Neon, and makes some minor assumptions about Neon-specifics.

We do not officially support use of autoscaling externally — in other words, you're welcome to try it out yourself, submit bugs, fork the code, etc., but we make no guarantees about timely responses to issues from running locally.

For help from the community, check out our Discord: https://neon.tech/discord.

Quick access

The deployment files and a vm-builder binary are attached to each release.

Check out Building and running below for local development.

How it works

We want to dynamically change the amount of CPUs and memory of running postgres instances, without breaking TCP connections to postgres.

This relatively easy when there's already spare resources on the physical (Kubernetes) node, but it takes careful coordination to move postgres instances from one node to another when the original node doesn't have the room.

We've tried a bunch of existing tools and settled on the following:

  • Use VM live migration to move running postgres instances between physical nodes
  • QEMU is used as our hypervisor
  • NeonVM orchestrates NeonVM VMs as custom resources in K8s, and is responsible for scaling allocated resources (CPU and memory)
  • A modified K8s scheduler ensures that we don't overcommit resources and triggers migrations when demand is above a pre-configured threshold
  • Each K8s node has an autoscaler-agent pod that triggers scaling decisions and makes resource requests to the K8s scheduler on the VMs' behalf to reserve additional resources for them
  • Each compute node runs the vm-monitor binary, which communicates to the autoscaler-agent so that it can immediately respond to memory pressure by scaling up (among other things).
  • For Neon's postgres instances, we also track cache usage and potentially scale based on the heuristically determined working set size, which dramatically speeds up OLTP workloads.

Networking is preserved across migrations by giving each VM an additional IP address on a bridge network spanning the cluster with a flat topology; the L2 network figures out "by itself" where to send the packets after migration.

For more information, refer to ARCHITECTURE.md.

Building and running

Note

NeonVM and Autoscaling are not expected to work outside Linux x86.

Build NeonVM Linux kernel (it takes time, can be run only once)

make kernel

Build docker images:

make docker-build

Start local cluster with kind or k3d:

make kind-setup # or make k3d-setup

Deploy NeonVM and Autoscaling components

make deploy

Build and load the test VM:

make pg16-disk-test

Start the test VM:

kubectl apply -f vm-deploy.yaml

Running pgbench

Broadly, the run-bench.sh script just exists to be expensive on CPU, so that more vCPU will be allocated to the vm. You can run it with:

scripts/run-bench.sh
# or:
VM_NAME=postgres16-disk-test scripts/run-bench.sh

Running allocate-loop

To test on-demand memory reservation, the allocate-loop binary is built into the test VM, and can be used to slowly increasing memory allocations of arbitrary size. For example:

# After ssh-ing into the VM:
cgexec -g memory:neon-test allocate-loop 256 2280
#^^^^^^^^^^^^^^^^^^^^^^^^^               ^^^ ^^^^
# run it in the neon-test cgroup  ;  use 256 <-> 2280 MiB

Testing

To run e2e tests you need to install dependencies:

You can either download them from their websites or install using Homebrew: brew install kubectl kind k3d kuttl

make kind-setup # or make k3d-setup, if you'd like to use k3d
make kernel
make deploy
make example-vms
make e2e