Software engineering
Automated code review
Review every change, run the tests, and report.
- Streams
- Workflows
- VM
- AI
The scenario
On each change, an agent checks out the code in a sandbox, runs the tests, and posts a review.
How it works
- 1An event announces a new change.
- 2A workflow runs checks in a sandbox.
- 3The review is stored and the author is notified.
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
01An event announces a new change.
queued- Ahura Streamsstreams.publishqueued
status: queued · 0 / 300 events routed
- Ahura Workflowsworkflow.definequeued
status: queued · 0 / 36 steps completed
02A workflow runs checks in a sandbox.
queued- Ahura VMutilities.run_pythonqueued
status: queued · 0 / 24 sandbox runs
03The review is stored and the author is notified.
queued- Ahura AIai.extractqueued
status: queued · 0 / 150 model calls
Services in this partition
Streams
0 calls · 0.00 ACU
Workflows
0 calls · 0.00 ACU
VM
0 calls · 0.00 ACU
AI
0 calls · 0.00 ACU
Spend by service
Event log
- Waiting to start.
Why Ahura OS
Why this is better on Ahura OS
Always-on CI servers cost money in quiet weeks and bottleneck in busy ones, and shared runners accumulate state nobody audits. On Ahura OS a change event starts a workflow, checks run in disposable sandboxes in parallel and the review is stored with its history. Untrusted code never touches a long-lived machine. You pay per review, results arrive when the change does, and every review is reproducible from its recorded inputs.
What each capability replaces
- Ahura StreamsInstead of a message broker to run, agents, workflows and your own systems react to events through managed routing.
- Ahura WorkflowsInstead of writing retry, timeout and approval plumbing, you declare the steps and the platform guarantees the behaviour and the history.
- Ahura VMInstead of fleets of machines to patch, every run gets its own disposable sandbox, billed only while it executes.
- Ahura AIInstead of a model gateway and several vendor contracts, one priced call reaches several models and chooses a cheap one when it can.
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 CI server that is always on, shared runners with leaked state, and reviewers waiting for results.
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