For Cloud and GPU Cloud Providers
Standardise Provisioning. Scale the Operations Around It.
Growth exposes every manual step between an order and a running instance. StackHeal standardises provisioning intake, policy and verification, automates the support requests that follow, and gives you one place to watch the whole operation — across hypervisors, regions and accelerator types.
Provisioning request
Requested specification
- vCPU
- 8 (dedicated)
- Memory
- 32 GB
- Storage
- 400 GB NVMe
- Network
- VLAN 418 · private
- Template
- ubuntu-24.04-base
Checks before build
- Quota available in AMS-1
- Template approved for tenant
- Naming and tagging policy
- Owner approval (over 16 GB)
The problem
Where cloud operations get expensive
If several of these describe your week, the gap is process rather than tooling.
Provisioning paths that multiplied
Each region, platform and plan picked up its own slightly different procedure, and nobody can say which steps are mandatory any more.
Support load that grows with the fleet
Quota bumps, resize requests, access questions and capacity issues arrive in proportion to customers, and they all land on engineers.
Accelerator capacity is scarce and expensive
GPU allocation needs approvals and verification that the driver stack actually works — but those checks are usually manual.
Verification left to the customer
The first signal that a build was wrong is often a ticket from the person who ordered it.
The fit
How StackHeal fits a cloud platform
One intake and verification path in front of every platform you operate, with the support workflow behind it automated too.
One provisioning contract
A single request shape, policy set and verification stage in front of Proxmox, vSphere, OpenStack or a public cloud backend.
Accelerator-aware workflows
Validate accelerator inventory, hold high-cost requests for approval, and confirm the driver and runtime stack before hand-off.
Self-service that stays governed
Expose provisioning and lifecycle actions to customers through your portal, bounded by entitlement and quota policy.
Support automation on the same platform
The tickets your platform generates are classified, investigated and resolved by workflows that reach the same infrastructure.
Use cases
Cloud providers commonly automate
The workflows teams in this segment build first, because the handling is already well understood.
Order to running instance
Normalise the order, check entitlement and quota, build from the approved template, enrol in monitoring and backup, verify reachability.
GPU capacity request
Validate availability, require approval above a cost threshold, provision with the correct driver image, confirm the accelerator is visible.
Resize and plan change
Validate the target plan, take a rollback point, apply the change in a window, verify the workload is healthy afterwards.
Quota and limit requests
Check the account's history and policy, apply the increase automatically within bounds, escalate larger asks with the context attached.
Capacity pressure response
Correlate utilisation signals across a cluster and run the approved rebalance or expansion workflow.
Offboarding
Retain the final copy, release resources back to the pool, and update inventory, monitoring and billing in one run.
Products this solution builds on
These are the products most relevant to this segment. All of them share one engine and one run history.
AI Support Automation
Turn incoming support requests into structured, actionable workflows.
Learn moreVM Provisioning
Standardize virtual machine provisioning and infrastructure lifecycle operations.
Learn moreWorkflow Orchestration
Connect systems and automate repetitive operational processes.
Learn moreCloud and GPU Cloud Providers: common questions
Something not covered here? Ask our team.
See StackHeal against your own cloud and gpu cloud providers workflows.
Bring two or three of the request types your team handles most often. We will walk through how each would be built, where the approvals sit, and what the run history records.