Coder powers secure, scalable development across key industries — automotive, finance, government, and technology — enabling faster builds, tighter compliance, and seamless AI adoption in enterprise-grade cloud environments.
The 3,000 users architecture targets large-scale enterprises, possibly with
on-premises network and cloud deployments.
The recommendations on this page apply to deployments with up to the following limits. If your needs
exceed any of these limits, consider increasing deployment resources or moving to the next-higher
architectural tier.
Users
Concurrent Running Workspaces
Concurrent Builds
3000
1800
180
Observability: Deploy monitoring solutions to gather Prometheus metrics and
visualize them with Grafana to gain detailed insights into infrastructure and
application behavior. This allows operators to respond quickly to incidents and
continuously improve the reliability and performance of the platform.
Hardware recommendations
Coderd
vCPU
Memory
Replicas
4
12 GB
4
Notes:
"General purpose" virtual machines, such as N4-series in GCP or M8-series in AWS work well.
If deploying on Kubernetes:
Set CPU request and limit to 4000m
Set Memory request and limit to 12Gi
Coderd does not typically benefit from high performance disks like SSDs (unless you are co-locating provisioners).
Coderd instances should be deployed in the same region as the database.
Workspace Proxies
If you choose to deploy workspaces in multiple geographic regions, provision
Workspace Proxies in each region.
vCPU
Memory
Replicas
4
12 GB
4
Notes:
"General purpose" virtual machines, such as N4-series in GCP or M8-series in AWS work well.
If deploying on Kubernetes:
Set CPU request and limit to 4000m
Set Memory request and limit to 12Gi
Workspace Proxies do not typically benefit from high performance disks like SSDs.
Provisioners
vCPU
Memory
Replicas
1
1 GB
180
Notes:
"General purpose" virtual machines, such as N4-series in GCP or M8-series in AWS work well.
If deploying on Kubernetes:
Set CPU request and limit to 1000m
Set Memory request and limit to 1Gi
If deploying on virtual machines, stack up to 30 provisioners per machine with a commensurate amount of memory and CPU.
Provisioners benefit from high performance disks like SSDs.
If deploying workspaces to multiple clouds or multiple Kubernetes clusters, divide the provisioner replicas among the
clouds or clusters according to expected usage.
Database
vCPU
Memory
Replicas
32
120 GB
1
Notes:
"General purpose" virtual machines, such as the M8-series in AWS work well.
Deploy in the same region as coderd
Workspaces
The following resource requirements are for the Coder Workspace Agent, which runs alongside your end users work, and as
such should be interpreted as the bare minimum requirements for a Coder workspace. Size your workspaces to fit the use
case your users will be undertaking. If in doubt, chose sizes based on the development environments your users are
migrating from onto Coder.
vCPU
Memory
0.1
128 MB
Footnotes for AWS instance types
For production deployments, we recommend using non-burstable instance types,
such as m5 or c5, instead of burstable instances, such as t3.
Burstable instances can experience significant performance degradation once
CPU credits are exhausted, leading to poor user experience under sustained load.