managed objects/nodes, reconciliation frequency, scheduled jobs, API activity and worker concurrency Time the job and identify CPU, storage or external-service waits before replacing hardware.
Imports, processing and simultaneous users.Requisitos de hardware de Goose: RAM, CPU, almacenamiento, plano de control y cargas de trabajo administradas
Planifica la memoria RAM, la CPU, el almacenamiento persistente y las dependencias de los servicios de Goose, con dimensionamiento de ZimaOS según la carga de trabajo, copias de seguridad y opciones de hardware prácticas.
Goose hardware requirements at a glance
Goose provides automation & configuration functionality. Use its upstream deployment instructions to identify the supported runtime and service topology. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
- RAM
- No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Size the full stack during the busy operation described below.
- CPU
- No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Measure CPU use during realistic activity.
- Storage
- Persist declarative configuration, credentials, controller state, workflow history and recoverable management state.
- Required services
- Follow the supported upstream runtime and complete Goose deployment topology for the selected release. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
- Main sizing variable
- managed objects/nodes, reconciliation frequency, scheduled jobs, API activity and worker concurrency
- Practical Zima starting point
- Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
From official requirements to the right setup
Plan the complete Goose workload before selecting a server.
-
Official requirements
Choose the exact edition, stable release and supported container/runtime. Follow the supported upstream runtime and complete Goose deployment topology for the selected release. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
-
Confirm your needs
Test a representative busy operation: managed objects/nodes, reconciliation frequency, scheduled jobs, API activity and worker concurrency Record peak resident memory, CPU, disk latency and completion time, including other containers.
-
Leave room to grow
Place active state on reliable persistent storage. Persist declarative configuration, credentials, controller state, workflow history and recoverable management state. Budget working space for an upgrade or import and test recovery before relying on the deployment.
-
Run it on ZimaOS
Follow the supported upstream runtime, operating system and complete service topology for the selected release. On ZimaOS, consider Custom Install only when a maintained compatible amd64 image and every required host capability have been verified. Otherwise use a separately supported Linux environment; this guide does not certify an unverified container deployment. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
Check every playback client
- Exact edition and stable release
- Supported upstream runtime and architecture
- All required companion services
- Realistic peak activity
- Persistent data and file ownership
- Free host ports and reachable URLs
- Working space and backup retention
- Successful database/file restore
Official minimum requirements
Reviewed November 11, 2026 against the linked upstream deployment documentation. Numerical values retain their stated minimum, recommendation or example scope; select release-compatible instructions before installation.
Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. Numerical examples above retain their stated deployment scope; co-hosted services and independent backups need additional capacity.
| Requirement | Official minimum | What this supports |
|---|---|---|
| RAM guidance | No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Size the full stack during the busy operation described below. | Official guidance keeps its original test, recommendation or example scope. |
| CPU guidance | No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Measure CPU use during realistic activity. | Core counts do not predict a fixed user, device or document capacity. |
| Storage planning | Persist declarative configuration, credentials, controller state, workflow history and recoverable management state. | Installation space is separate from retained content, working files and backups. |
| Service topology | Follow the supported upstream runtime and complete Goose deployment topology for the selected release. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. | Include every stateful companion service in the host budget. |
| Persistent state | Persist declarative configuration, credentials, controller state, workflow history and recoverable management state. | An image rebuild or container replacement is not a backup. |
| Deployment boundary | Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. | Check the linked project instructions for the selected edition and release. |
When to upgrade your hardware
Use observed Goose workload pressure to decide when an upgrade is warranted.
Busy operations exceed the available window
The complete stack runs short of memory
Persistent data approaches available capacity
Inspect the application and each required service for OOM events, sustained swap or growing queues. Reduce unnecessary concurrency before adding capacity.
Shared hosts and background work.Persist declarative configuration, credentials, controller state, workflow history and recoverable management state. Track primary state and backup retention separately.
Long-lived installations and growing collections.Plan hardware growth with confidence
Address storage, memory, compute and deployment limits separately.
Use suitable active storage
Put latency-sensitive application/database state on durable local SSD storage and keep recoverable copies.
SATA or PCIe SSD according to measured data growth.Add memory for the complete stack
Choose a higher-RAM host when peak application and companion-service usage leaves inadequate OS headroom.
ZimaBoard 2 832 or ZimaBoard 2 1664 according to the measured constraint.Separate capacity from compute
A multi-drive system helps when retained content and backup storage are the problem; it is not automatically a faster application.
ZimaCube 2 when a broader multi-drive workload justifies it.Fix the observed bottleneck
Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
Check service configuration, I/O and network behavior before selecting a stronger CPU.Can it run on ZimaOS?
Follow the supported upstream runtime, operating system and complete service topology for the selected release. On ZimaOS, consider Custom Install only when a maintained compatible amd64 image and every required host capability have been verified. Otherwise use a separately supported Linux environment; this guide does not certify an unverified container deployment.
Verify the supported upstream deployment
Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. Follow the supported upstream runtime, operating system and complete service topology for the selected release. On ZimaOS, consider Custom Install only when a maintained compatible amd64 image and every required host capability have been verified. Otherwise use a separately supported Linux environment; this guide does not certify an unverified container deployment.
Review upstream deployment guidance ↗Use the official Goose deployment instructions
Keep the selected stable release, persistent paths and companion services aligned with upstream documentation.
Review Goose official installation ↗Check workload-specific deployment details
Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
Review Goose deployment details ↗Which Zima hardware fits Goose?
Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements.
Which workload best matches your Goose deployment?
Conditional lab or supporting storage use only
Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
- Supporting hardware onlyZimaBoard 2 832
These are practical workload recommendations, not official app requirements, compatibility certification, measured capacity limits or performance guarantees. Include all co-hosted services and independent backups.
| Zima hardware | Best for | Example workload | Core configuration | Recommended boundary | Next step |
|---|---|---|---|---|---|
| ZimaBoard 2 832 | Conditional lab or supporting-service role | managed objects/nodes, reconciliation frequency, scheduled jobs, API activity and worker concurrency |
|
Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. | Get Now |
| ZimaBoard 2 1664 | Conditional lab or supporting-service role | Follow the supported upstream runtime and complete Goose deployment topology for the selected release. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. |
|
Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. | Get Now |
What the Press Says
Highlights from trusted reviewers worldwide.
“ZimaCube 2: Not just another NAS, tested with 25TB storage, local AI agents, 4K transcoding, and real homelab workflows.”Read full review
“The ZimaBoard 2 is a compact x86 server board that can be turned into a mini NAS, home server, media box, or self-hosting hub.”Read full review
“ZimaCube 2: A modern, high-performance NAS with plenty of room to grow—built for users who want more than basic storage.”Read full review
“Coverage focused on ZimaCube 2's open hardware foundation, no monthly fee, and self-hosting flexibility.”Read full review
Loved by the Community
Stories and reviews from people who build with Zima every day.
★★★★★
Zima Blade Little yet Powerful
Maybe I am not digital natives but I live with PCs since 12 years old in 1984 when IBM PC clone come to my home. Many years have passed and many operating system I've tried. For me Zima blade and CasaOS was a quantum leap for home PC enthusiast and server lab machine to make me stay curious and relevant for this era.
★★★★★
Very good!!
I use ZimaCube Pro as 5th Proxmox cluster node. It runs several VMs and containers, including a VM with GPU passthrough to run a self-hosted LLM. A specific LXC container runs a Samba server for NAS capabilities using four of six RAID 6 SATA HDDs with ZFS.
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Great innovation for mini server!
It is very useful and makes a powerful mini server for many purposes, including university and college students in engineering and electronics. Thank you so much for making this server.
★★★★★
Avaliação ZimaBoard 2
Construí um servidor de uso pessoal. O desempenho está muito bom e funciona perfeitamente onde quer que eu esteja. A surpresa é não dependermos de grandes estruturas para termos nosso próprio servidor de dados. Como iniciante, estou gostando bastante do ZimaOS, pois ele é simples e eficiente.
Frequently asked questions
Answers to Goose RAM, CPU, storage, Docker, database and ZimaOS sizing questions.
How much RAM should I plan for Goose?
No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Size the full stack during the busy operation described below. Include ZimaOS, the application and its companion services rather than reserving the entire machine for one container.
What drives the CPU requirement?
No fixed numerical whole-host figure is inferred here; follow the selected release and deployment requirements. Measure CPU use during realistic activity. The workload to test is: managed objects/nodes, reconciliation frequency, scheduled jobs, API activity and worker concurrency
Which data must survive a container update?
Persist declarative configuration, credentials, controller state, workflow history and recoverable management state. Preserve a consistent database/file set and verify that your recovery procedure restores a working application.
What other services belong in the budget?
Follow the supported upstream runtime and complete Goose deployment topology for the selected release. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
Does this workload need a dedicated GPU?
Accelerator needs depend on the selected inference, synthesis, browser or media backend. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
Can I deploy it on ZimaOS?
Follow the supported upstream runtime, operating system and complete service topology for the selected release. On ZimaOS, consider Custom Install only when a maintained compatible amd64 image and every required host capability have been verified. Otherwise use a separately supported Linux environment; this guide does not certify an unverified container deployment. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
What should I check before upgrading hardware?
Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute. Measure the same representative operation before and after a configuration or hardware change.
Which Zima device is a practical starting point?
Conditional lab, data-storage or supporting-service hardware only; a complete production deployment requires a separately verified host meeting the upstream requirements. Agent/control tooling may call remote model APIs or a separately hosted inference backend. Tool execution permissions, concurrent sessions and model/runtime requirements must be checked independently; an interface does not include model-sized compute.
What sources informed this Goose hardware guide?
This guide was reviewed against the linked project deployment documentation on November 11, 2026. Zima device choices are editorial workload guidance, separate from upstream requirements and measured performance.
