For a dependable n8n installation, choose a VPS with dedicated or high-quality shared CPU, Ubuntu 24.04 LTS, SSD or NVMe storage, and enough memory for PostgreSQL as well as n8n. A practical production setup uses Docker Compose, PostgreSQL, and Caddy or Nginx terminating HTTPS for webhook traffic. The light-instance figures in n8n documentation are useful for testing, but a real production stack needs more headroom.
The short answer: size for the whole stack
n8n itself is only one process in a self-hosted deployment. The VPS also has to run a database, the operating system, Docker, a reverse proxy, logging, backup jobs, and your workflow executions. Memory is normally the first constraint, particularly when PostgreSQL and large execution payloads share the machine.
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| Use case | CPU | RAM | Storage | Recommended software layout |
|---|---|---|---|---|
| Short-term test or very light personal use | 1–2 vCPU | 1–2 GB | 20 GB SSD | n8n with SQLite can work for experimentation; Docker on Linux is the simplest route |
| Typical production workflows | 2 vCPU, preferably dedicated cores | 4 GB minimum; 8 GB gives useful headroom | 40 GB or more SSD/NVMe | Docker Compose, n8n, PostgreSQL, and Caddy or Nginx |
| Heavy payloads or several simultaneous executions | 4 vCPU | 8 GB | 40 GB or more, increased for binary data and logs | PostgreSQL with monitoring; consider separate workers |
| Queue-mode deployment | Depends on worker count; a four-worker single-server estimate is about 8–12 total cores | More than a single-instance setup; size each worker for its workflows | Include external binary-data storage | Main n8n instance, Redis, and one or more workers |
The test figures come from 2026 vendor guides and are guidance rather than independent benchmarks. n8n documentation describes a single light instance at roughly 320 MB to 2 GB of memory, with database storage of about 512 MB to 4 GB. Those figures do not represent the complete production stack described above.
What n8n actually consumes
Memory is the first number to watch
n8n documentation lists memory requirements of approximately 320 MB to 2 GB for one instance and notes that memory requirements supersede its CPU guidance. The same documentation describes the software itself as using about 180 MiB in its cloud sizing examples. A VPS still needs memory for PostgreSQL, the Node.js runtime, Docker overhead, the reverse proxy, the operating system, and temporary execution data. That is why a plan that appears adequate for n8n alone can start swapping as soon as the database is added.
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One 2026 vendor guide specifically warns that a 2 GB server begins swapping and execution speed falls sharply when PostgreSQL runs beside n8n. Treat 2 GB as a test ceiling, not a comfortable production target.
Payload size changes the answer
Workflow count is less useful than execution shape when sizing a server. A workflow that passes a few JSON fields may use little memory, while one that downloads files, transforms images, parses large spreadsheets, or fans out to many branches can consume much more. The n8n Code node duplicates data for pre-processing and post-processing, so memory use grows with payload size. Leave headroom for the largest simultaneous execution rather than sizing from the average run.
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CPU affects concurrency and latency
CPU matters when several executions run at once, when Code nodes perform expensive transformations, or when workers process many jobs in parallel. Vendor guidance commonly starts production at two vCPU and suggests four vCPU with 8 GB of RAM for heavier loads. Dedicated cores are preferred because noisy neighbors on a shared host can make webhook response time unpredictable. CPU is not a substitute for memory: adding cores to a swapping 2 GB plan will not fix the underlying bottleneck.
Storage is more than the database file
Use at least 40 GB of SSD or NVMe for a normal production installation. That space covers the operating system, Docker images, PostgreSQL data, n8n logs, temporary files, and snapshots. Twenty gigabytes can be workable for a short test, but binary attachments and retained execution data can fill it quickly. Fast SSD storage improves database checkpoints and container restarts; capacity and backup policy matter more than peak benchmark numbers.
Choose the right sizing tier
Testing and learning
A 1 vCPU, 2 GB VPS can run n8n alone with SQLite in a test mode, and a 2 vCPU, 2 GB plan with 20 GB SSD is a common vendor recommendation for light use. Keep this tier for learning, disposable integrations, or a private prototype. Expect to stop workflows before applying upgrades, and do not treat a local SQLite database as a production recovery plan.
Small production installation
For real workflows, use 2 vCPU and 4 GB RAM with at least 40 GB of SSD storage. Prefer dedicated cores, Ubuntu 24.04 LTS, Docker Compose, PostgreSQL, and a reverse proxy providing HTTPS. This tier suits scheduled jobs, modest webhook traffic, and a limited number of concurrent executions when payloads are not unusually large. If the VPS provider offers 8 GB at a reasonable difference, the additional memory is usually more valuable than a small CPU upgrade.
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Heavy single-instance use
Move to 4 vCPU and 8 GB RAM when workflows run in parallel, process large payloads, invoke the Code node extensively, or perform frequent file operations. Measure actual memory and execution latency after deployment. A larger disk may be necessary if you retain execution data or handle binary files locally.
Queue mode and horizontal scale
Queue mode separates a main instance, which receives triggers, from worker instances, which execute jobs. n8n describes this as its most scalable operating mode. It adds Redis and requires the EXECUTIONS_MODE setting, so the VPS must accommodate another service and the workers’ concurrent workload. A 2026 guide estimates that one main instance plus four workers on a single server could require roughly 8–12 total CPU cores; that is an estimate, not an official minimum. Start with fewer workers, observe queue depth and memory, then add capacity deliberately.
What to compare between VPS plans
1. Guaranteed memory and CPU behavior
Compare the RAM printed on the plan, not a provider’s claim that the host has abundant capacity. Ask whether vCPU is dedicated, capped, or burstable, and whether the provider exposes steal time or CPU-credit limits. A stable two-core plan is often preferable to a larger burstable plan that throttles during webhook spikes.
2. SSD or NVMe capacity
Confirm the usable disk size after the provider’s system partition and snapshots. For production, begin at 40 GB and reserve room for PostgreSQL growth, Docker image updates, logs, and temporary files. NVMe can reduce database and container I/O latency, but reliability and backup tooling should outrank a small synthetic I/O advantage.
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Select a region close to the services that call your webhooks and to the users who open the n8n editor. Lower round-trip time improves interactive work and can reduce webhook timeouts. If workflows call services in several continents, choose the location that matters most or split workloads across installations rather than assuming one region is equally close to everything.
4. Public address and DNS
Webhook endpoints require a reachable public IP or a domain that resolves to it. Check whether the plan includes a static IPv4 address, whether inbound ports 80 and 443 can be opened, and how quickly DNS changes propagate. A provider’s automated DNS and reverse-DNS tools can simplify setup but are not substitutes for your own domain control.
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5. Backups and snapshots
Look for scheduled snapshots, off-server backup destinations, retention controls, and documented restore procedures. A snapshot on the same physical host is not a complete disaster-recovery plan. Back up PostgreSQL regularly, preferably nightly for a small installation, and test restoring to a separate VPS before you need it.
6. Operational controls
Useful controls include console access when SSH fails, firewall management, reboot and rescue modes, monitoring alerts, and a clear abuse policy. These features reduce recovery time more than a marginal difference in advertised CPU frequency.
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A practical self-hosting architecture
A compact production layout has one Ubuntu 24.04 LTS VPS running Docker Compose. Containers typically include n8n, PostgreSQL, and Caddy or Nginx. The reverse proxy owns ports 80 and 443, obtains and renews the TLS certificate, and forwards authenticated HTTPS requests to n8n. PostgreSQL stores workflow definitions, credentials metadata, execution records, and settings; it should be on a persistent volume and included in backups.
For queue mode, add Redis and one or more n8n workers. The main instance handles triggers and the editor while workers consume jobs. Queue mode cannot use the local filesystem for binary data; use documented S3-compatible external storage instead. This requirement is easy to miss when moving a single-container installation to workers.
Deployment sequence for a new VPS
1. Provision and secure the host
- Create an Ubuntu 24.04 LTS VPS in the region closest to your webhook sources. Select the production tier appropriate to your workload, and attach a static public IP if available.
- Create a non-root administrative user, install security updates, and use SSH keys rather than password-only login. Restrict the firewall to SSH from trusted addresses plus TCP ports 80 and 443 for the reverse proxy.
- Set the host name and create a DNS record such as
n8n.example.compointing to the VPS address. Wait for the record to resolve before requesting a certificate.
2. Install the container runtime
Install Docker Engine and the Docker Compose plugin from the distribution and Docker repositories appropriate for Ubuntu. Keep the compose project in a dedicated directory, store persistent volumes on the VPS disk, and avoid placing secrets directly in a public repository. Pin image versions deliberately so an update is a change you can roll back, not an accidental deployment.
3. Configure PostgreSQL and n8n
Create a private Compose network for n8n and PostgreSQL. Use a strong database password and a separate n8n encryption key; losing that key can make stored credentials unusable even if the database is restored. Set the n8n public URL to the HTTPS hostname, configure the webhook URL to match it, and mount persistent volumes for PostgreSQL and any data that must survive container replacement.
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Use PostgreSQL for production. SQLite is limited to testing in the vendor guidance because concurrent executions, backups, and growth are harder to manage safely on a production instance. Schedule nightly PostgreSQL backups, encrypt them in transit and at rest, and keep at least one copy outside the VPS.
4. Put TLS in front of the editor and webhooks
Configure Caddy or Nginx to proxy the domain to n8n and obtain a certificate from a trusted certificate authority. Test both the editor and a representative webhook over HTTPS. Make sure the proxy forwards the headers n8n needs to reconstruct the original scheme and host; otherwise webhook URLs or OAuth callbacks can be generated incorrectly.
5. Run a controlled test
- Start the Compose project and confirm that PostgreSQL is healthy before n8n begins normal operation.
- Open the editor through the domain, create a minimal workflow, and run it manually.
- Trigger the same workflow through its production webhook URL and verify the response from an external network.
- Inspect container logs, memory usage, disk usage, and PostgreSQL connectivity while the test runs.
- Take a database backup and perform a test restore to verify that the procedure works.
Queue mode: when and how to scale
What changes architecturally
In regular mode, one n8n process receives triggers and performs executions. Queue mode assigns trigger and coordination duties to a main instance while workers execute jobs pulled through Redis. This lets you increase execution capacity without exposing every worker directly to the internet.
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Additional requirements
- Run Redis and set
EXECUTIONS_MODE=queuefor the n8n deployment. - Provide a worker process for each execution slot you intend to run concurrently, then budget CPU and RAM for the workflow types those workers will process.
- Use S3-compatible external storage for binary data; local filesystem storage is not supported for binary data in queue mode.
- Monitor Redis health, queue depth, worker restarts, memory pressure, and failed executions.
Scaling without guesswork
Do not treat the 8–12-core estimate for four workers as a guaranteed requirement. It is a planning figure from a vendor guide, while n8n has not published an official minimum CPU or memory specification for queue-mode workers. Start with a main instance and one worker, record execution duration and peak memory, and add workers only when queue depth or latency demonstrates a need. Large Code-node payloads may require more RAM per worker rather than simply more workers.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Interpreting n8n’s official sizing figures
n8n’s documented single-instance range of 320 MB to 2 GB and its cloud examples—Starter at 320 MiB with 10 millicores burstable CPU, Pro-1 at 640 MiB with 20 millicores, Pro-2 at 1,280 MiB with 80 millicores, and Enterprise at 4,096 MiB with 80 millicores—describe managed service allocations, not a self-hosted VPS bill of materials. The documentation also lists approximately 512 MB to 4 GB for database storage and describes CPU as 10 CPU cycles scaling as needed. Use these values to understand the software’s baseline, then add capacity for the rest of your stack and your workload.
Common failure modes and fixes
The VPS is swapping
Check memory and swap activity during concurrent executions. If PostgreSQL and n8n share a 2 GB plan, move to at least 4 GB before tuning application settings. Reduce unnecessary execution-data retention, limit concurrency where appropriate, and investigate oversized Code-node payloads. Swap can prevent an immediate crash but does not restore predictable latency.
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Webhooks time out or arrive intermittently
Verify DNS, the public IP, firewall rules, and ports 80 and 443. Confirm that the reverse proxy certificate is valid and that it forwards the original host and scheme. If the host is CPU-throttled or overloaded, measure response time during the same period rather than assuming the remote service is at fault.
Disk usage grows unexpectedly
Inspect PostgreSQL growth, retained execution data, Docker images, logs, and binary files. Add alerts before the disk is full, prune obsolete images during a maintenance window, and move queue-mode binary data to external object storage. Never delete a database volume as a cleanup shortcut.
Queue workers fail after migration
Check that every worker can reach Redis and PostgreSQL, that all processes use the same encryption key and n8n configuration, and that binary data is configured for external storage. A worker that still expects local files can appear healthy while individual executions fail.
Backups exist but cannot be restored
Perform a trial restore on an isolated VPS, confirm that credentials decrypt with the preserved encryption key, and document the DNS and certificate steps needed to bring the service online. A backup policy without a restore test is only an assumption.
A decision framework for selecting your plan
- Classify the workload. Choose test, small production, heavy single-instance, or queue mode based on concurrency and payload size rather than workflow count alone.
- Set the memory floor. Reserve 2 GB only for experiments; use 4 GB as the practical production starting point and 8 GB when payloads or concurrency are substantial.
- Check CPU quality. Prefer stable dedicated or non-throttled vCPU, then increase from two to four cores when execution latency or parallelism requires it.
- Reserve disk and backups. Start at 40 GB SSD/NVMe, calculate growth from binary data and retention, and confirm off-server backups.
- Validate networking. Ensure a public static address, usable DNS, open HTTPS, and a region appropriate for webhook callers.
- Plan the next step. Confirm that the provider allows resizing, snapshots, and attaching extra storage so an upgrade does not require an emergency migration.
Bottom line for most self-hosters
Pick a VPS that can run the complete stack, not merely the n8n process. A two-vCPU, 4 GB production baseline with 40 GB or more SSD, Ubuntu 24.04 LTS, Docker Compose, PostgreSQL, and an HTTPS reverse proxy is the sensible starting point for ordinary workflows. Keep 1–2 GB plans for testing, move to 8 GB and four vCPU for heavy payloads or concurrency, and introduce Redis plus workers only when measured queueing justifies the added architecture.
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