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All use cases

Software engineering

Long-running migration agent

Work through a large codebase change over days, resumably.

  • Memory
  • VM
  • Workflows
  • Store

The scenario

An agent migrates hundreds of files over several days and must survive restarts without losing its place.

How it works

  1. 1Progress is checkpointed in memory.
  2. 2Each batch runs in a sandbox with a snapshot.
  3. 3The workflow retries failed batches automatically.

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

01Progress is checkpointed in memory.

queued
  • Ahura Memoryqueued

    status: queued · 0 / 240 keys written

  • Ahura VMqueued

    status: queued · 0 / 24 sandbox runs

02Each batch runs in a sandbox with a snapshot.

queued
  • Ahura Workflowsqueued

    status: queued · 0 / 36 steps completed

03The workflow retries failed batches automatically.

queued
  • Ahura Storequeued

    status: queued · 0 / 48 objects stored

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

Services in this partition

  • Memory

    0 calls · 0.00 ACU

  • VM

    0 calls · 0.00 ACU

  • Workflows

    0 calls · 0.00 ACU

  • Store

    0 calls · 0.00 ACU

Spend by service

Event log

  • Waiting to start.

Why Ahura OS

Why this is better on Ahura OS

Large migrations fail on interruption, not difficulty. A script that dies on day three forgets where it was. On Ahura OS progress is checkpointed in memory, each batch runs in a sandbox with a snapshot, and a workflow retries failed batches on its own. A restart costs minutes, a bad batch can be rolled back from its snapshot, and the run history shows precisely what changed. Compute is billed only while batches run, so a week-long job is not a week of idle servers.

What each capability replaces

  • Ahura MemoryInstead of provisioning and securing a cache or database, agents get fast key/value state with expiry already scoped to their partition.
  • 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 StoreInstead of managing buckets, permissions and lifecycle rules, objects follow the partition: they freeze, thaw and expire with it.

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

A fragile script run from someone’s laptop over several days, with no record of where it stopped.

Cheaper with Ahura OSCompute is billed only while batches run, and failed batches are retried instead of re-run from scratch.
Faster with Ahura OSCheckpoints let work resume exactly where it stopped, so a restart costs minutes, not days.
Less risk with Ahura OSSnapshots and a full run history give you a safe way back if a batch goes wrong.

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