Platform · Insight

KERNSTACK Analytics

Analytics on KERNSTACK is a declared project resource — resources.analytics_projects with a name, retention in days, and a named write key — that collects product behaviour into the same stack as the product itself. Events stop emigrating to a third-party analytics SaaS whose export terms become the ceiling on every future question.

Product Analytics

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Why teams replace assembled cloud services with KERNSTACK Analytics

Teams otherwise run a third-party analytics SaaS and discover its data model, its retention, and its export limits at the exact moment a serious question arrives. On KERNSTACK the analytics project is declared beside the tables it complements, in the same zone, under the same balance.

What an analytics project is

A small declaration with long consequences: name the project, set retention_days so event volume has a priced horizon, and name the write key the product uses to send events. Client and server code write behaviour events; the product’s tables hold the transactional truth beside them, so “what did users do” and “what did the system do” can finally be asked in one place.

Why colocation compounds

Experiments, recommendation logs, and funnel questions all want behaviour joined to product records by the same user keys. When analytics lives with the product, that join is ordinary project data work; when it lives at a SaaS, it is an export pipeline with a quarterly sync and a prayer. Retention being a declared field also ends the silent accumulation of forever-events nobody priced.

Retention is explicit: the event horizon is a number in the plan review, not a vendor tier discovered later
Write keys are named stack objects; rotation is a declaration
Behaviour data inherits the project’s zone and subject-erasure discipline

SDKs & Language Integration

Every KERNSTACK environment vendors typed SDK packages into .kernstack/ so both engineers and coding agents in Agent Sandboxes can call Analytics without external credentials:

Go SDK: github.com/coding-berlin/kernstack-sdk-go/sdk_analytics
Node.js SDK: kernstack-sdk
Python SDK: kernstack_sdk
PHP SDK: Kernstack\Analytics

Implementation guides for Analytics

React + Analytics →

Analytics in the Project Graph

Declarestack.jsonanalytics

RunAnalyticsinfrastructure

MeterOne credit balanceEU zone

stack.json — analytics configuration plan · deploy

{
  "resources": {
    "analytics_projects": [{ "name": "product", "retention_days": 400, "write_key_name": "web" }],
    "tables": [{ "name": "users", "key_name": "user_id", "key_type": "S", "indexes": [] }]
  }
}

Metering · compute, storage, or network 1 Shared Balance

Usage draws from the same credit balance as compute (0.01 credits/GiB-s), storage (0.04 credits/GB-hour), and egress (9.00 credits/GiB).

Replaces: Amazon Kinesis · no native equivalent · no direct equivalent

FAQ

Frequently asked questions

Does this replace our product analytics tool?

For event collection and product questions, it is designed to. If your team depends on a specific analytics vendor’s polished exploration UI, keep it for that and let the project remain the source of truth it exports from — the data stops being hostage either way.

How is retention controlled?

retention_days on the analytics project declaration. Event history beyond the horizon is removed on schedule, which makes analytics storage a visible, chosen cost at 0.04 credits per GB-hour.

Can analytics events join product data?

Yes — that is the architectural point. Events written with user and entity keys can be analysed beside the tables holding those users and entities, inside one project and one zone.

Connected in the Project Graph

Related capabilities, architectures, and comparisons

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