The ALCOA+ Field Guide for Platform Engineers

Table of Contents

The auditor asked a simple question: “How do you know this file was not modified after upload?” The team had versioning off, a shared transfer credential, and a fourteen-second silence that felt much longer.

Most ALCOA+ writing is aimed at quality and regulatory people. This post is the engineering translation—a control mapping you can hand to a teammate before the next audit or design review. It assumes you already went live with a hybrid lab-to-cloud path. This is not legal or regulatory advice; validate the mapping with your quality team.

The one-table version

PrinciplePlain meaningPrimary AWS controls
AttributableYou can say who/what touched data and whenCloudTrail (management + data events), one IAM identity per agent
LegibleReadable by humans and systems for the retention periodOpen/structured formats, schema registry, format migration plan
ContemporaneousRecorded at the time of the action, not reconstructedSource-side timestamps, NTP discipline, ingest-time vs event-time kept distinct
OriginalThe first capture is preserved, including copiesS3 versioning, Object Lock on raw, source checksums
AccurateData is what it claims to beChecksum verification gates, quarantine on mismatch
CompleteNothing missing, including contextManifests, completion markers, metadata sidecars
ConsistentSame facts everywhere, in orderCorrelation ids (run_id), idempotent consumers, ordered state transitions
EnduringSurvives time, failure, and platform changeCross-region replication, KMS, documented retention, restore drills
AvailableRetrievable on demand by the right peopleLifecycle tiering without deletion, access model, retrieval SLOs

Attributable: identity all the way down

  • CloudTrail data events for S3 are on for the data buckets—management events alone do not show object-level access.
  • Every agent, validator, and consumer has its own role (separate identities by job)—“shared upload user” fails attribution by construction.
  • Log lines carry run_id, instrument_id, agent_id—an auditor should not need to infer identity from an IP address.
  • Break-glass use is time-bound, alarmed, and reviewed.

Original + Accurate: immutability with proof

  • S3 versioning is on everywhere; a mistaken overwrite is a new version, not data loss.
  • raw/ prefix has Object Lock (governance mode is usually enough; compliance mode is a one-way door—decide deliberately).
  • Source checksums are computed at capture, stored in metadata and sidecar, and verified before any marker is written (the transfer checklist).
  • Checksum mismatch routes to quarantine with a reason, never a silent overwrite.

Contemporaneous + Consistent: timestamps and correlation

  • Agent hosts sync time (NTP); clock skew is a documented risk, and event-time is recorded separately from ingest-time.
  • One run_id from instrument through validation to consumer—the correlation discipline is also a data-integrity control.
  • Consumers are idempotent on run_id, so a redelivery cannot create two conflicting “truths.”

Complete + Enduring + Available: the retention shape

  • A run is complete only with a manifest or marker—“the folder looked full” is not completeness.
  • Retention for raw/, validated/, quarantine/ is written down, enforced by lifecycle policy, and matches what quality promised the auditor.
  • Cross-region replication or an equivalent endurance story exists for the data that matters.
  • Tiering to colder storage never means deletion; retrieval paths are exercised on a calendar, not assumed.

Audit-day evidence pack

What to be able to produce in an hour, not a week:

  1. For any run_id: who/what wrote each object (CloudTrail), checksum chain, marker time.
  2. The retention policy as enforced (lifecycle + Object Lock config), not as described.
  3. Access history for a named principal over a period.
  4. Proof of a restore or replay performed under control.

If you only do one thing: turn on CloudTrail data events + S3 versioning + Object Lock on raw today—those three cheap defaults are the difference between answering audit questions from evidence and answering them from memory.

Next in this series: choosing between a poller, DataSync, and S3 Events for instrument ingestion.

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