Persona · CTOs

KERNSTACK for CTOs

CTOs choose KERNSTACK for the properties that survive an audit of the engineering organisation: every system declared in one file, every production change preceded by a readable plan, agent work sandboxed by construction and promoted only through approval, data resident in one European zone on named infrastructure, and a bill that arrives as a single meter a finance partner can interrogate.

stack.json IaC Agent Sandboxes Approval Workflows NoSQL Tables

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Why CTOs outgrow assembled cloud and tool collages

Engineering leaders accountable for residency, review discipline, security posture, and a cloud bill that can be explained to a board.

Governance that is mechanical, not cultural

Policy written in a wiki decays; policy in the platform does not. Deploy gates can require review-approved source, destructive changes refuse without explicit human confirmation, agent branches are confined to their own environments, and secrets never live in the repository. A CTO evaluating KERNSTACK is really evaluating whether their non-negotiables can be platform defaults instead of code-review vigilance.

The honest boundaries of the platform

KERNSTACK is not a hyperscaler replacement: no exotic managed services, no regions on five continents, tables are key-value rather than SQL. The CTO case rests on how much of the estate is ordinary product engineering that currently pays hyperscaler complexity rent — and on agent-era leverage: agents are only safe at scale when the system they change is one declared graph with a human gate.

Residency answer in one sentence: this zone, this operator, every environment
Destructive operations require --confirm-destructive — a named human, every time, logged by the act itself
Cost attribution per project and environment without a tagging programme

stack.json — CTOs Stack plan · deploy

{
  "stack": { "target": "core.default", "min_source_assurance": "review_approved" },
  "resources": {
    "functions": [{ "name": "api" }, { "name": "record-change" }],
    "tables": [{ "name": "audit", "key_name": "record_id", "key_type": "S",
      "sortkey_name": "ts", "sortkey_type": "N", "indexes": [],
      "change_stream": { "function": "record-change" } }]
  }
}

FAQ

Frequently asked questions

What is the lock-in story, honestly?

Your code is ordinary (Go functions; Node/Python/PHP workers), your data exports as JSON and files, and stack.json is a readable declaration of the architecture. Leaving means re-declaring elsewhere — real work, no hostage mechanics, and the declaration itself is the map the next platform team will thank you for.

How is agent risk contained at the platform level?

Agents work on agent/<id> branches with their own environments; deploying outside them prompts for confirmation; production deploys can require review-approved source; destructive plan entries stop for a human flag. The controls are the deploy path itself, not agent instructions.

Can the board-level cost question be answered?

Per project, per environment, in one unit: credits. Compute at 0.01 per GiB-second, storage at 0.04 per GB-hour, egress at 9.00 per GiB — a bill that fits on one slide because it is one meter.

Connected in the Project Graph

Related capabilities, architectures, and comparisons

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