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
- 1Progress is checkpointed in memory.
- 2Each batch runs in a sandbox with a snapshot.
- 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
- Provisioning
- Processing
- Complete
01Progress is checkpointed in memory.
queued- Ahura Memorymemory.setqueued
status: queued · 0 / 240 keys written
- Ahura VMutilities.run_pythonqueued
status: queued · 0 / 24 sandbox runs
02Each batch runs in a sandbox with a snapshot.
queued- Ahura Workflowsworkflow.definequeued
status: queued · 0 / 36 steps completed
03The workflow retries failed batches automatically.
queued- Ahura Storestore.listqueued
status: queued · 0 / 48 objects stored
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
A fragile script run from someone’s laptop over several days, with no record of where it stopped.
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

