Use Case · Product

Experiment assignment on the Software Lifecycle Cloud

Experiment assignment on KERNSTACK keeps the experiment inside the product’s own data: a table declares the experiment — variants, split, eligibility — a function assigns each subject deterministically from their key, and outcome events land in the same tables as every other product event. The readout is a query over your records: assignments beside conversions, with no experimentation vendor defining what either one means.

Functions (WASM)NoSQL TablesProduct Analytics
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The engineering bottleneck with assembled stacks

Growth leads assign a variant and record the outcome in two different universes: the experiment platform knows who saw what, the product database knows who converted, and joining them is a quarterly data project. Under that friction, teams run experiments whose results arrive after the decision was already made by shipping deadline.

Architecture on the Software Lifecycle Cloud

Assignment is a pure function of the subject key and the experiment’s salt — stable across requests, no coordination needed. The function records the assignment row once and serves the variant; outcome handlers were already writing events, which now simply carry the experiment id the assignment returned. Analysis reads assignments and outcomes from neighbouring tables with the same keys.

Deterministic beats random

Hashing the subject key means the same user gets the same variant on every device and every request without a lookup table of coin flips — and re-running the analysis reproduces the same buckets. When an experiment smells wrong, the assignments can be recomputed from the rule and compared against what was served; that audit is impossible when a vendor’s black box did the flipping.

  • Assignments and outcomes share keys, so the experiment readout is one honest query
  • Variant splits and eligibility are table rows — pausing an experiment is an update, not a ticket
  • No client-side experiment SDK phoning a third party from your product’s critical path

Statistics stay your responsibility

This pattern assigns and records; it does not supply a statistician. Sample sizes, guardrail metrics, and when-to-call-it judgement belong to your team or your analysis tools reading the exported tables. What the platform removes is the plumbing excuse for not knowing who saw what.

FAQ

Frequently asked questions

Deterministically: the variant is a hash of the subject key and the experiment salt. Same subject, same variant, every request and device — and assignments are also stored, so served variants can be audited against the rule.

Over the project’s tables: assignments joined to outcome events by subject key. Bring your notebooks or BI to those exports; the platform’s contribution is that the join exists at all, in one place, from day one.

Yes — updating the experiment row ends new assignments, and the full assignment and outcome record remains for the post-mortem. Early stopping is a data change with an author and a timestamp, not a vendor ticket.

Connected in the Project Graph

Related capabilities, architectures, and comparisons

Category PillarThe Software Lifecycle CloudWhy people and agents build, deploy, and operate on a single vertically integrated stack.Service · ComputeFunctionsGo WebAssembly HTTP handlersService · DataTablesServerless key-value and document tablesService · InsightAnalyticsProduct analytics on the same fabricIndustry SolutionE-commerce Cloud SolutionsE-commerce on KERNSTACK owns the parts of commerce that constitute the business: the catalogue and its search, carts and checkout state, the order lifecycle, raw payment events reconciled into provable order states, and fulfilment workflows with human steps for the exceptions. Cards stay with the payment provider; the data that makes the business worth buying moves onto infrastructure the merchant controls, in Europe.Use Case · AgenciesAgency client deliveryThe studio’s delivery shape is a template stack.json: gateway, functions or workers in the client’s stack languages, tables, buckets, and apps under one target per client, on European infrastructure the studio can name in the pitch. Previews run the same declaration; the client’s approval happens in the bound conversation with a live link. Every client’s meter is separate by construction — the studio sees delivery cost per client without allocation spreadsheets.Use Case · AgentsAgent operations consoleThe raw material already exists in the project: hosted git lists branches including agent/<id>, each agent branch maps to its environment, and every deploy begins as a plan a person approved. The console view arranges that material — branch, environment URL, plan summary, approval state — into the board engineering managers actually ask for, with conversations and board topics carrying the discussion around each run.Use Case · AgentsAI agent backendHosted git carries the repository; agent branches namespace the experiments. The agent edits code and stack.json together, runs kernstack plan --json to verify its own change set, and a reviewer checks the same plan. Environments multiply cheaply because a project is declared, not hand-assembled: the agent-<id> environment runs the branch’s stack for click-through review.

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