Problem
In mission environments, raw data alone is not enough. Teams need to know what record was observed, who processed it, what changed later, and whether a conclusion can be defended under review.
Ratna
Project Stash Vault
Engineering archive shaped for long-horizon work, not short-term portfolio churn.
Vault 01 / Aerospace
Back to Aerospace vault
Case file / 2026
Telemetry Attestation Rail
A provenance rail for mission telemetry that signs critical state changes and preserves an auditable path from raw data to reviewable findings.
Public materials are still being curated. The internal case file below is the current source of truth until supporting assets are ready to publish.
PythonFastAPIKafkaClickHouseSolidity
#telemetry#provenance#verification#mission assurance
20-second project scan
What to understand first
A fast scan for recruiters and engineers: ownership, technical depth, proof status, and current outcome in one place.
Category
Aerospace
Status
Research Track
Proof ready
00
Stack surface
5 tools
My role
Provenance model design, ingestion pipeline architecture, and workflow definition for anomaly review and downstream verification.
PythonFastAPIKafkaClickHouseSolidity
Technical highlights
01
Built the system around immutable telemetry checkpoints so later anomaly verdicts always refer back to a stable source record.
02
Separated high-volume telemetry storage from lightweight attestations to keep the verification path efficient and portable.
03
Shaped the pipeline around publication, verification, and review workflows instead of treating signatures as a standalone feature.
04
Reserved interfaces for anomaly scoring and triage automation without binding the provenance model to any single ML approach.
Impact
Clarified a practical path from telemetry ingestion to defensible engineering review.
Architecture overview
Problem, solution, and system shape
The project framed as a system: the problem, the solution boundary, and the architecture choices that make the implementation credible.
Solution
Telemetry Attestation Rail focuses on the handoff between flight data, anomaly detection, and accountable engineering review. The system packages mission checkpoints, signs them through an ingestion pipeline, and produces a lightweight verification record that downstream operators or insurers can inspect without pulling the entire telemetry archive into the trust boundary.
Architecture
01
Built the system around immutable telemetry checkpoints so later anomaly verdicts always refer back to a stable source record.
02
Separated high-volume telemetry storage from lightweight attestations to keep the verification path efficient and portable.
03
Designed the ledger-facing layer as a registry of signed facts rather than a storage tier for raw flight data.
Technical highlights
Where the engineering depth shows up
The implementation details a technical reviewer should notice before reading the full case file.
Highlight 01
Built the system around immutable telemetry checkpoints so later anomaly verdicts always refer back to a stable source record.
Highlight 02
Separated high-volume telemetry storage from lightweight attestations to keep the verification path efficient and portable.
Highlight 03
Shaped the pipeline around publication, verification, and review workflows instead of treating signatures as a standalone feature.
Highlight 04
Reserved interfaces for anomaly scoring and triage automation without binding the provenance model to any single ML approach.
Proof surface
Artifacts, references, and public access points
Ready links and planned proof artifacts are shown together so reviewers can distinguish published evidence from reserved case-study slots.
Diagram
PlannedTrust-boundary diagram
Reserved for the data path from raw telemetry ingestion to signed checkpoint publication and downstream verification.
Reserved for future publication once the supporting material is ready.
Trace
PlannedVerification trace capture
Reserved for an annotated example of how a reviewer follows a signed telemetry checkpoint back to source evidence.
Reserved for future publication once the supporting material is ready.
System view
Architecture and implementation
The architectural boundaries and implementation choices that make the system coherent, maintainable, and operationally meaningful.
Architecture
01
Built the system around immutable telemetry checkpoints so later anomaly verdicts always refer back to a stable source record.
02
Separated high-volume telemetry storage from lightweight attestations to keep the verification path efficient and portable.
03
Designed the ledger-facing layer as a registry of signed facts rather than a storage tier for raw flight data.
Implementation Notes
01
Shaped the pipeline around publication, verification, and review workflows instead of treating signatures as a standalone feature.
02
Reserved interfaces for anomaly scoring and triage automation without binding the provenance model to any single ML approach.
03
Focused on preserving reviewability for humans as much as machine-readable traceability.
Metrics and outcomes
What is proven so far
Honest status, proof readiness, and results. Qualitative markers are used where exact production metrics are not available yet.
Status
Research Track
Current maturity of the project record.
Proof
Diagram planned
Reserved for the data path from raw telemetry ingestion to signed checkpoint publication and downstream verification.
Architecture
3 notes
Documented architecture decisions and boundaries.
Outcomes
01
Clarified a practical path from telemetry ingestion to defensible engineering review.
02
Positioned provenance as infrastructure for aerospace accountability rather than a decorative blockchain layer.
Future Work
01
Add reviewer workbenches that link signed checkpoints to anomaly investigations and closure notes.
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View ProjectView Repo
Internal case file is live; public repo is not linked yet.