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Umami’s official installation guidance does not specify a minimum CPU, memory, or traffic capacity, so there is no documented server size—or visits-per-gigabyte formula—to apply to a Vultr VPS. For a small personal installation, Umami’s DigitalOcean guide offers a $5-per-month cloud server as a possible starting point, but that is neither a Vultr price nor a tested capacity benchmark. Choose a modest starting server based on your workload, then use your own app, database, and disk metrics to decide when to scale.
What Umami’s requirements do—and do not—tell you
The current Umami installation documentation specifies software requirements: Node.js 18.18 or newer and PostgreSQL 12.14 or newer. Those versions describe compatible software, not the CPU, RAM, disk space, or traffic a server must support.
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The official material does not give a minimum VPS specification or a benchmark linking server size to visits, page views, or events. It also does not state how much database storage each visit consumes. Any precise “visits per GB of RAM” recommendation would therefore imply evidence that is not available.
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The right starting setup depends partly on how much infrastructure you want to administer. Umami documents these arrangements:
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| Deployment | Where components run | Operational trade-off |
|---|---|---|
| One server | Umami and PostgreSQL share a machine. | The simplest documented self-hosting topology, but both application and database workloads use the same server. |
| Separate application and database | The web server connects to a database on another machine. | Separates the services, but the database must be reachable remotely and becomes an additional component to administer. |
| Hosted application with external database | An app-hosting provider runs Umami; a separate database service stores its data. | Reduces direct server administration for the app, while retaining a dependency on the database. |
There is no documented traffic or resource threshold at which you should move from one arrangement to another. A single server is a reasonable place to begin when simplicity matters; splitting components is an architectural option if monitoring shows a resource bottleneck or if you need separate operational control. The documentation does not establish that one arrangement is universally faster or cheaper.
How to think about a starting Vultr server
Umami’s DigitalOcean guide says personal users can start with a $5-per-month cloud server and scale up as needed. That is a provider-specific example from Umami’s guide—not a Vultr quote, a verified equivalent plan, or proof that a server at that price will handle a particular workload.
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For Vultr, select an available server based on its current specifications and your own constraints; the cited Umami material does not identify a Vultr plan or establish a minimum number of vCPUs, memory, or disk. If you choose a one-server Docker Compose deployment, remember that the machine will host both the Umami application and PostgreSQL. Leave room for the operating system and other services you run there, rather than treating all advertised capacity as available to Umami.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchStart with a small deployment only if you are comfortable observing it and changing the plan when evidence warrants. A provider’s lowest-priced option is a starting hypothesis, not a capacity guarantee. Do not infer expected traffic capacity from the DigitalOcean example or transfer its price to Vultr.
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Install and secure the deployment
Umami’s installation options include source installation, Docker Compose, and a prebuilt Docker image. The supplied Docker Compose setup includes the Umami application and PostgreSQL, making it a straightforward way to place both services on one server. Use a supported PostgreSQL version (12.14 or newer) and Node.js 18.18 or newer where applicable to your chosen installation method.
- Choose the deployment method and topology: for the simplest single-server arrangement, use the Docker Compose setup that runs the app and PostgreSQL together.
- Provision the server and install Umami following its official installation instructions, ensuring the required software versions are met.
- Log in after installation and change the default administrator password immediately.
- Check that the application and database are running, then begin tracking resource use under your actual workload.
What to monitor before changing server size
Because there is no official capacity formula, observe the system that you actually deploy rather than sizing from a generic visit count. For a combined app-and-database server, watch the host’s CPU, memory, and disk use, along with whether the application and database remain responsive during your normal traffic periods.
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- CPU and memory: Look for sustained pressure or resource exhaustion that coincides with slow responses or service problems. A brief spike alone does not establish that the server is undersized.
- Disk and database growth: Track free disk space and database size over time. Umami retains self-hosted data indefinitely unless it is manually deleted, so storage use can accumulate. The documentation provides no per-visit storage estimate.
- Service health: Check whether the app or database is restarting, failing, or becoming unavailable, and correlate those events with resource use before deciding what to change.
Set up backups and decide how you will handle retention before the database becomes important to your reporting. The official retention statement does not prescribe a backup schedule or deletion policy; those are operational choices to make for your own needs.
When to scale up or separate the database
Scale the server when sustained resource pressure or observed service problems point to a capacity constraint, not simply because a particular number of visits has been reached. If the application and PostgreSQL compete for resources on one machine, moving the database to a separate host is one possible change. It adds remote connectivity and another service to secure, monitor, and maintain, and Umami’s documentation does not define a threshold that makes the move necessary.
Make one change at a time where practical, then observe whether it resolves the problem under the same kind of workload. This produces a more useful sizing decision than relying on an unsupported traffic-to-instance estimate.
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