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All use cases

Science & optimisation

Parameter sweeps

Fan out thousands of simulation runs and gather results.

  • VM
  • Workflows
  • NoSQL
  • Utilities

The scenario

An agent runs a model across a large grid of parameters and summarises the outcome.

How it works

  1. 1A workflow launches runs in parallel sandboxes.
  2. 2Each result is written to a collection.
  3. 3A utility aggregates the final table.

An illustrative scenario, not a customer story.

Interactive simulation

Simulate this case study

Watch the partition come up, each step run, and usage build as it goes. Simulated: volumes, timings and prices are illustrative.

Partition

—

Status

not created

Elapsed

00:00

Overall0%
  1. Provisioning
  2. Processing
  3. Complete

01A workflow launches runs in parallel sandboxes.

queued
  • Ahura VMqueued

    status: queued · 0 / 24 sandbox runs

  • Ahura Workflowsqueued

    status: queued · 0 / 36 steps completed

02Each result is written to a collection.

queued
  • Ahura NoSQLqueued

    status: queued · 0 / 600 records written

03A utility aggregates the final table.

queued
  • Ahura Utilitiesqueued

    status: queued · 0 / 120 documents processed

Not createdus-eastRetention hold
Run time
00:00
0 calls
Size
2.3MB
0.00 ACU used

Services in this partition

  • VM

    0 calls · 0.00 ACU

  • Workflows

    0 calls · 0.00 ACU

  • NoSQL

    0 calls · 0.00 ACU

  • Utilities

    0 calls · 0.00 ACU

Spend by service

Event log

  • Waiting to start.

Why Ahura OS

Why this is better on Ahura OS

A parameter sweep is thousands of small jobs, and reserving a cluster for it means paying for the idle hours either side. On Ahura OS a workflow fans runs out across parallel sandboxes billed by the millisecond, each result lands in a collection and a function assembles the table. Nothing is reserved and nothing idles. Each run is isolated, and results are retained only as long as you choose.

What each capability replaces

  • Ahura VMInstead of fleets of machines to patch, every run gets its own disposable sandbox, billed only while it executes.
  • Ahura WorkflowsInstead of writing retry, timeout and approval plumbing, you declare the steps and the platform guarantees the behaviour and the history.
  • Ahura NoSQLInstead of designing tables and maintaining indexes, you write documents and query them. Indexes are looked after for you.
  • Ahura UtilitiesInstead of a function platform to host, common helpers are ready to call and billed per invocation.

And on every use case

  • One endpoint, not a stack

    Memory, storage, compute, inference, identity and messaging share one connection, one identity and one bill. The integration work you would normally own disappears.

  • Isolation by construction

    Every agent’s world is a partition. Separation is how the platform is built, not a convention teams must remember to follow.

  • Cost follows use

    Pay per call and per millisecond. Idle agents freeze to archive pricing. There is no capacity to reserve and nothing running unseen.

  • Retention and deletion built in

    Lifetimes, expiry, freezing and destruction are platform features, so your data policy is enforced rather than aspirational.

  • Safe autonomy

    Spending limits, protected signing keys, approval steps and signed actions let agents work unattended without being unaccountable.

  • Ready for audit

    Designed against SOC 2 and ISO 27001 controls, with every call metered, recorded and attributable.

Compared

The old way of doing things

Today

Reserving a cluster for the week, or queueing for shared compute, then tearing it down by hand.

Cheaper with Ahura OSThousands of short runs billed by the millisecond. Nothing reserved, nothing idle.
Faster with Ahura OSRuns fan out in parallel and the results table assembles itself.
Less risk with Ahura OSEach run is isolated, and the results are retained only as long as you decide.

Data retention is built in

Everything this scenario stores lives in one isolated partition with a lifetime you set. Expired data deletes itself, a paused project freezes to low-cost archive, and a finished one can be destroyed completely. Security and compliance