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Quick Definition (30–60 words)

Rekor is an open-source transparency log that records metadata about signed software artifacts to make supply chain actions auditable. Analogy: Rekor is like a public ledger for signing receipts. Formal: Rekor provides an append-only, cryptographically verifiable ledger for storing and indexing signing attestations and related metadata.

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What is Rekor?

Rekor is a transparency log component, typically part of the Sigstore ecosystem, that persistently records metadata about signatures, attestations, and other provenance artifacts for software. It is an append-only store designed to enable verifiable, auditable evidence that a signing event or attestation occurred and was recorded.

What it is NOT:

• Rekor is not the signing tool itself; it does not create cryptographic signatures.
• Rekor is not a full provenance database with arbitrary queries; it focuses on storing and indexing entries.
• Rekor is not an enforcement engine; it provides evidence that other systems can use to enforce policies.

Key properties and constraints:

• Append-only transparency log model with cryptographic integrity proofs.
• Entries are indexed by artifact hash, signature, and other selectors for lookup.
• Designed to be public or multi-tenant; visibility and retention depend on deployment.
• Not a replacement for artifact registries or secret stores.
• Performance and storage scale depend on deployment architecture and retention policies.

Where Rekor fits in modern cloud/SRE workflows:

• CI/CD: record signing events as part of pipeline completion.
• Release governance: provide verifiable evidence for release artifacts.
• Incident response: audit who signed what and when to trace provenance.
• Policy enforcement: allow gate checks to verify records before deployment.
• Supply chain security: a component in attestation-based supply chains.

Diagram description (text-only):

• Developer or CI creates a signed artifact.
• Signing tool issues signature and attestation.
• Client submits signature and metadata to Rekor server.
• Rekor appends entry to immutable log and yields a log index and proof.
• Consumers query Rekor to verify that an artifact’s signing event exists and is unchanged.
• Auditors or monitors watch Rekor for suspicious entries and generate alerts.

Rekor in one sentence

Rekor is an append-only transparency log that stores verifiable records of software signing and attestation metadata to support auditable software supply chain workflows.

Rekor vs related terms (TABLE REQUIRED)

ID	Term	How it differs from Rekor	Common confusion
T1	Sigstore	Rekor is one component; Sigstore is the broader project	People call Rekor and Sigstore interchangeably
T2	Notary	Notary focuses on attestations; Rekor stores log entries	Both used for provenance but different architectures
T3	Transparency log	Rekor implements this idea; not every log is Rekor	Term used generically and specifically
T4	Certificate Authority	CA issues certs; Rekor records metadata not issue certs	Some think Rekor validates certs
T5	Artifact registry	Registry stores artifacts; Rekor stores signing metadata	Confused because both relate to releases
T6	Key management	KMS stores keys; Rekor stores publications about signatures	Rekor does not manage private keys
T7	Supply chain policy engine	Policy engine enforces; Rekor provides evidence	Users expect Rekor to block deployments
T8	Transparency monitor	Rekor is the log; monitors watch Rekor	People assume Rekor sends alerts automatically

Row Details (only if any cell says “See details below”)

• None

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Why does Rekor matter?

Business impact:

• Trust and brand protection: Verifiable signing records reduce the risk of undetected tampering, helping preserve customer trust.
• Regulatory and compliance: Provides traceable evidence for audits and compliance frameworks that require immutable records.
• Reduced legal and financial risk: Faster root-cause and attribution can limit breach scope and cost.

Engineering impact:

• Incident reduction: With reliable provenance, unsafe or illegitimate artifacts are less likely to be promoted to production.
• Faster incident response: Teams can quickly determine who signed what and when, accelerating mitigation and rollback.
• Improved velocity: Automating attestation recording reduces manual approvals and friction while preserving auditability.

SRE framing:

• SLIs/SLOs: Rekor availability and query latency become measurable SLIs for teams that rely on it for gating deployments.
• Error budgets: If verification depends on Rekor, Rekor outages should be part of error budget calculations.
• Toil: Proper automation for submission and verification reduces manual recordkeeping toil.
• On-call: On-call runbooks should include Rekor verification and troubleshooting steps.

What breaks in production — realistic examples:

1. CI pipeline signs release but fails to push to Rekor, leaving artifacts unverifiable and blocked by gating.
2. Rekor instance becomes read-only or unavailable, causing deployment stalls where verification is mandatory.
3. Malicious actor reuses an old signature against a newer artifact if clients only check signature presence, not artifact hash.
4. Log poisoning attempts against a self-hosted Rekor by submitting malformed entries to exploit indexing logic.
5. Retention policy purges older entries unexpectedly, breaking audits and postmortem analysis.

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Where is Rekor used? (TABLE REQUIRED)

ID	Layer/Area	How Rekor appears	Typical telemetry	Common tools
L1	CI/CD	Signed artifact submission step	Submission success rate and latency	CI system, signing client
L2	Release gating	Verification step before deploy	Verification pass/fail counts	Gate checks, policy engine
L3	Kubernetes	Admission controller checks records	Admission accept/reject rates	Admission controllers, OPA
L4	Serverless	Pre-deploy attestation validation	Deployment block counts	Managed PaaS deploy hooks
L5	Artifact storage	Cross-reference metadata	Lookup latency and index hits	Registries, storage
L6	Incident response	Audit log for investigations	Query frequency and patterns	SIEM, forensic tools
L7	Observability	Monitors index growth and anomalies	Alerts on failed writes	Monitoring stacks
L8	Security ops	Detection of anomalous entries	Alerts on suspicious submitters	SOAR, SIEM
L9	Compliance	Evidence bundling for audits	Archive completeness	Archive tools

Row Details (only if needed)

• None

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When should you use Rekor?

When it’s necessary:

• You require immutable audit trails for signing events.
• Your deployment pipeline demands verifiable attestations before production promotion.
• Regulatory or contractual obligations mandate tamper-evident logs.

When it’s optional:

• Small projects without formal release controls may not need Rekor initially.
• Early-stage prototypes where rapid iteration outweighs formal auditability.

When NOT to use / overuse it:

• Do not record highly sensitive secrets or PII in Rekor entries.
• Avoid using Rekor as a general-purpose datastore for arbitrary metadata.
• Don’t expect Rekor to replace runtime enforcement; it’s evidence, not a policy engine.

Decision checklist:

• If you require verifiable signing evidence and audits -> use Rekor.
• If you have lightweight internal releases with low compliance needs -> optional.
• If you need real-time blocking and enforcement without auditability -> pair Rekor with enforcement tools or use alternatives.

Maturity ladder:

• Beginner: Use hosted or community Rekor, integrate with CI to submit signatures.
• Intermediate: Run dedicated Rekor instances, add automated verification in deployment gates, monitor SLIs.
• Advanced: Multi-region Rekor clusters, retention policies, alerting for anomalies, integration with security orchestration and policy engines.

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How does Rekor work?

Components and workflow:

• Rekor Server: Accepts entries and appends them to the log.
• Underlying storage: Backing store for log entries (filesystem, object storage, database depending on implementation).
• Transparency Log Structure: Merkle-tree or similar structure to provide cryptographic inclusion and consistency proofs.
• API/Client: CLI or SDKs to submit entries and query by artifact hash or signature.
• Indexer: Extracts searchable fields from submissions for efficient queries.

Data flow and lifecycle:

1. Signing tool creates signature and attestation metadata.
2. Client packages metadata and artifact identifier and posts to Rekor API.
3. Rekor validates submission format and appends entry.
4. Rekor returns a log index, UUID, and inclusion proof.
5. Consumers query Rekor by artifact hash, signature, or UUID to verify presence.
6. Over time, retention and archival policies may prune or export entries.

Edge cases and failure modes:

• Partial submission: Client submits but network failure prevents confirmation; deduplication is important.
• Indexer lag: Newly appended entries may not be immediately queryable if indexing is asynchronous.
• Storage corruption: Underlying storage corruption can break inclusion proofs or availability.
• Compromised client keys: Authorized clients could flood Rekor with malicious entries; monitoring required.

Typical architecture patterns for Rekor

1. Hosted Rekor (SaaS or community endpoint) – Use when you want minimal ops. – Good for smaller teams or rapid adoption.
2. Single-node self-hosted Rekor behind load balancer – Use for predictable load and internal control. – Requires backup and monitoring.
3. HA Rekor cluster with object storage – Use for production-critical, high-availability needs. – Requires distributed storage and consensus.
4. Rekor with local cache and proxy – Use to reduce latency in high-query environments. – Proxy caches recent entries for faster verification.
5. Rekor + policy engine + admission controller – Use to enforce deployment gates based on Rekor entries. – Tight integration with OPA/Gatekeeper or Kubernetes admission webhooks.

Failure modes & mitigation (TABLE REQUIRED)

ID	Failure mode	Symptom	Likely cause	Mitigation	Observability signal
F1	Write failures	Submission errors	Storage full or API error	Backpressure and retries	Error rate spike
F2	Index lag	Queries miss recent entries	Async indexer backlog	Monitor index lag and scale indexer	Index lag metric
F3	Corrupted proofs	Verification fails	Storage corruption	Restore from backup and reindex	Proof verification failures
F4	High latency	Slow verification calls	Resource exhaustion	Autoscale or optimize DB	Request latency increase
F5	Unauthorized writes	Suspicious entries	Compromised client	Revoke keys and audit	Unusual submitter patterns
F6	Retention purge	Missing historical entries	Aggressive retention	Adjust retention and archive	Audit and archive alerts

Row Details (only if needed)

• None

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Key Concepts, Keywords & Terminology for Rekor

Glossary (40+ terms). Each entry: Term — 1–2 line definition — why it matters — common pitfall

1. Rekor — Transparency log for signatures and attestations — Stores verifiable records — Not a signer.
2. Transparency log — Append-only ledger for public auditing — Provides tamper evidence — Confused with general logs.
3. Attestation — Metadata claiming facts about an artifact — Enables richer provenance — Can contain sensitive data.
4. Signature — Cryptographic proof of origin — Core input to Rekor entries — Signature reuse risk.
5. Inclusion proof — Cryptographic proof that entry is in the log — Verifies integrity — Misinterpreting proof validity period.
6. Consistency proof — Shows log growth without tampering — Ensures immutability — Requires correct reference trees.
7. Merkle tree — Data structure for proofs — Efficient verification — Implementation complexity.
8. UUID — Unique entry identifier in Rekor — Used to fetch entries — Not a secure key by itself.
9. Indexer — Extracts searchable fields from entries — Enables fast lookup — Can lag behind writes.
10. API client — Tool to submit/query Rekor — Automation point — Misconfigured clients cause failures.
11. Log root — Cryptographic root of the log state — Basis for audits — Must be preserved for verification.
12. Transparency monitor — Watches logs for changes — Alerts on anomalies — False positives if noisy.
13. Keyless signing — Short-lived ephemeral signing model — Reduces key management burden — Requires external trust.
14. Public key certificate — Links identity to key — Used in verification — Certificate revocation issues.
15. Certificate Authority — Issues certs for signing keys — Adds trust anchors — Not provided by Rekor.
16. Artifact hash — Identifies binary content — Primary lookup key — Hash collisions are theoretical risk.
17. Non-repudiation — Difficulty to deny a signature — Increases accountability — Depends on broader identity controls.
18. Supply chain attack — Compromise of build or release flows — Rekor aids detection — Not a full defense.
19. CI/CD integration — Automated submit step in pipelines — Essential for reliable provenance — Pipeline failures stop recordings.
20. Admission control — Gate in runtime platforms that verifies entries — Enforces policies — Can block healthy deploys if Rekor is down.
21. Provenance — Collection of evidence about artifact origin — Critical for audits — Requires consistent instrumentation.
22. Immutable log — Cannot be altered without detection — Core security property — Needs secure storage.
23. Replay attack — Resubmitting old valid signature for new artifact — Verify artifact hashes to prevent.
24. Replay protection — Strategies to avoid replay — Bind signature to artifact content — Often overlooked.
25. Gossip protocol — Mechanism for syncing logs across nodes — Not always used — May be present in distributed setups.
26. Replica — Copy of Rekor store — Improves availability — Requires consistent synchronization.
27. Root rotation — Changing log root for security — Needs re-signing and coordination — Mishandled rotation breaks verification.
28. Retention policy — How long entries are kept — Balances storage and audit needs — Over-aggressive pruning harms audits.
29. Archival — Exporting old records for long-term retention — Satisfies compliance — Must preserve integrity proofs.
30. Availability SLA — Expected uptime for Rekor service — Important for gating pipelines — Must be measured.
31. Latency SLA — Expected response time — Affects deployment velocity — Critical for synchronous checks.
32. Quorum — Threshold for distributed decisions — Relevant in HA setups — Config complexity risk.
33. Encryption at rest — Protects stored entries — Reduces data exposure — Not a substitute for access control.
34. Authentication — Client identity verification for submissions — Prevents unauthorized writes — Misconfigured auth equals exposure.
35. Authorization — Fine-grained submission permissions — Limits who can create entries — Often underused.
36. Audit trail — Chronological record of events — Critical for investigations — Needs completeness.
37. Forensics — Investigation using Rekor records — Speed improves containment — Requires queryability.
38. SIEM integration — Feed Rekor events to security systems — Enables correlation — Requires mapping of events.
39. DDoS protection — Protect Rekor API from overload — Prevents outages — Requires network controls.
40. Healthcheck endpoint — Enables monitoring of Rekor status — Used by orchestration systems — Should reflect readiness.
41. Dead-letter queue — Holds failed submissions for later retry — Prevents data loss — Needs operational process.
42. Throttling — Rate-limiting clients to protect service — Ensures stability — Can disrupt bursty pipelines.
43. Replica divergence — Difference between replicas — Causes validation mismatch — Requires reconciliation.
44. Client SDK — Language bindings to interact with Rekor — Simplifies integration — SDK bugs can cause failures.
45. Chain of custody — Record of artifact movement — Helps legal defensibility — Requires consistent logging.

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How to Measure Rekor (Metrics, SLIs, SLOs) (TABLE REQUIRED)

ID	Metric/SLI	What it tells you	How to measure	Starting target	Gotchas
M1	Write success rate	Reliability of submissions	Successful writes / total writes	99.9% daily	Includes client retries
M2	Write latency	Time to append entry	P95 request latency	<= 500ms	Indexing may add extra delay
M3	Query success rate	Readability of records	Successful queries / total queries	99.9% daily	Caches may mask issues
M4	Query latency	Time to verify evidence	P95 query latency	<= 200ms	Network affects this
M5	Index lag	Time between write and searchable	Time difference metric	< 10s	Varies with index load
M6	Proof verification rate	Valid proofs returned	Valid proofs / total proof checks	100%	Corrupted storage breaks this
M7	Error rate	API errors vs total	5xx and 4xx counts	<0.1%	Client misconfig inflates 4xx
M8	Storage usage	Growth of log data	Bytes stored over time	Trend-based	Retention affects value
M9	Retention compliance	Entries archived vs expected	Archived count / expected	100%	Long-term archival verification needed
M10	Unauthorized write attempts	Security incidents	Auth fails count	0 tolerated	High false positives possible

Row Details (only if needed)

• None

Best tools to measure Rekor

Provide 5–10 tools each with the exact structure below.

Tool — Prometheus

• What it measures for Rekor: Metrics like request latency, success rates, error counts.
• Best-fit environment: Kubernetes, on-prem, cloud VMs.
• Setup outline:
• Export Rekor metrics via Prometheus exporter or endpoints.
• Configure Prometheus scrape jobs for Rekor endpoints.
• Define recording rules for SLI calculation.
• Create alerts for error rate and latency SLO breaches.
• Retain metrics for SLO burn-rate analysis.
• Strengths:
• Cloud-native and widely used.
• Powerful query and alerting rules.
• Limitations:
• Requires instrumentation or exporter.
• Long-term storage needs extra components.

Tool — Grafana

• What it measures for Rekor: Visualizes Prometheus or other metric stores.
• Best-fit environment: Teams using Prometheus or other TSDBs.
• Setup outline:
• Connect to Prometheus or backend.
• Build dashboards for write/read latency and success.
• Share dashboards with stakeholders.
• Strengths:
• Flexible visualization.
• Dashboard templating.
• Limitations:
• Not a metric store itself.
• Alerting config distributed across systems.

Tool — Loki / ELK

• What it measures for Rekor: Application logs, submission traces, errors.
• Best-fit environment: Centralized logging environments.
• Setup outline:
• Ingest Rekor server logs.
• Parse structured log fields for request IDs and UUIDs.
• Create alerts on error patterns.
• Strengths:
• Powerful log search and correlation.
• Limitations:
• Storage costs for high-volume logs.

Tool — OpenTelemetry

• What it measures for Rekor: Distributed traces and spans for Rekor API calls.
• Best-fit environment: Instrumented microservices and CI systems.
• Setup outline:
• Instrument Rekor server with OTEL SDK.
• Export traces to chosen backend.
• Use traces to identify slow paths.
• Strengths:
• End-to-end tracing.
• Limitations:
• Instrumentation effort required.

Tool — SIEM (Varies)

• What it measures for Rekor: Security events from failed auth and suspicious writes.
• Best-fit environment: Security operations centers.
• Setup outline:
• Forward Rekor security logs to SIEM.
• Create correlation rules for anomalous activity.
• Strengths:
• Central security view.
• Limitations:
• Licensing and integration overhead.

Tool — Synthetic monitors (HTTP checks)

• What it measures for Rekor: Availability and basic latency from multiple regions.
• Best-fit environment: Global deployments or critical services.
• Setup outline:
• Create periodic write/read synthetic checks.
• Monitor SLA from consumer perspective.
• Strengths:
• Consumer-centric availability measurement.
• Limitations:
• Synthetic checks may not exercise indexing paths.

Recommended dashboards & alerts for Rekor

Executive dashboard:

• Panels:
• Overall write success rate: shows reliability for business stakeholders.
• Query success rate and trend: demonstrates availability to leadership.
• Storage growth trend and retention compliance: shows capacity planning needs.
• Recent security incidents: counts of unauthorized attempts.
• Why: High-level indicators for risk and capacity.

On-call dashboard:

• Panels:
• Live error rate and request latency per endpoint.
• Index lag metric and queue lengths.
• Recent failed submissions with error codes.
• Replica synchronization status and storage usage.
• Why: Rapid troubleshooting and root cause identification.

Debug dashboard:

• Panels:
• Per-request traces for slow operations.
• Recent submission UUIDs and status.
• Indexer backlog and recent indexing errors.
• Proof verification failure logs and stack traces.
• Why: Deep-dive for engineers during incidents.

Alerting guidance:

• Page vs ticket:
• Page for service-wide outages affecting production gating or SLO breach (high severity).
• Ticket for degraded performance that does not block deployments (medium severity).
• Burn-rate guidance:
• Use burn-rate calculations on write success SLI; page if burn rate exceeds 3x for 10 minutes.
• Noise reduction tactics:
• Dedupe alerts by correlated root causes and group by service/region.
• Suppress non-actionable transient spikes using short alerting windows combined with thresholds.

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Implementation Guide (Step-by-step)

1) Prerequisites – Identify use cases and stakeholders. – Choose hosted vs self-hosted Rekor. – Ensure CI/CD tooling supports Rekor client or SDK. – Define retention and access policies.

2) Instrumentation plan – Instrument CI to submit to Rekor on canonical artifact builds. – Ensure signing step produces provenance metadata and artifact hash. – Add retries and idempotency to submission logic.

3) Data collection – Capture artifact identifiers, signature, signer identity, timestamp, and attestation payloads. – Ensure logs include submission UUIDs and request IDs. – Route security events to SIEM.

4) SLO design – Define availability SLOs for write and read paths. – Set latency SLOs for synchronous verification calls.

5) Dashboards – Create executive, on-call, and debug dashboards. – Add long-term storage and retention panels.

6) Alerts & routing – Implement alerts for write failure rate, index lag, and proof verification failures. – Route severe incidents to on-call, medium issues to queues.

7) Runbooks & automation – Create runbooks for common failures: indexer restart, storage cleanup, certificate rotation. – Automate key rotation, backups, and archival.

8) Validation (load/chaos/game days) – Run synthetic writes and reads from regional locations. – Run chaos tests on indexer and storage to validate failover. – Perform game days to test incident workflows and postmortems.

9) Continuous improvement – Review incident trends monthly. – Refine retention and archival based on audit needs. – Automate remediation for common failures.

Checklists:

Pre-production checklist:

• Rekor endpoint reachable from CI.
• CI pipeline submits sample entry and verifies proof.
• Metrics and logs integrated with monitoring.
• Backup and snapshot processes configured.

Production readiness checklist:

• SLA and SLO defined and agreed by stakeholders.
• Alert routing and on-call rotation defined.
• Access control and authentication configured.
• Retention and archival policies implemented.

Incident checklist specific to Rekor:

• Verify service health and storage capacity.
• Check recent submission UUIDs and errors.
• Inspect indexer backlog and logs.
• Rollback or bypass gating policies if safe.
• Capture evidence and notify security if suspicious writes detected.

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Use Cases of Rekor

Provide 8–12 use cases.

1. CI/CD signature recording – Context: Automated builds with signed artifacts. – Problem: Lack of auditable signing evidence. – Why Rekor helps: Records and proves signing events. – What to measure: Write success rate and verification latency. – Typical tools: CI platform, Rekor client, Prometheus.

2. Release gating in Kubernetes – Context: Controlled production deployments. – Problem: Unsigned or unverifiable images promoted accidentally. – Why Rekor helps: Admission controllers verify Rekor entries before deploy. – What to measure: Admission reject rate and Rekor availability. – Typical tools: OPA/Gatekeeper, Kubernetes admission webhook.

3. Forensic audit after incident – Context: Investigation of compromised release pipeline. – Problem: Need to prove what was signed and when. – Why Rekor helps: Immutable evidence for postmortem. – What to measure: Query success and completeness of logs. – Typical tools: SIEM, Rekor query APIs.

4. Supply chain attestation – Context: Multi-step build and sign process across teams. – Problem: Missing chain of custody for artifacts. – Why Rekor helps: Stores attestations from each pipeline stage. – What to measure: Attestation completeness and timing. – Typical tools: Attestation generators, Rekor.

5. Compliance reporting – Context: Audit requirements for signed releases. – Problem: Manual collection of signing records for audits. – Why Rekor helps: Centralized, tamper-evident audit repository. – What to measure: Archive completeness and integrity. – Typical tools: Archive system, Rekor exports.

6. Keyless signing workflows – Context: Reduce long-lived key exposure. – Problem: Managing private keys across CI runners. – Why Rekor helps: Works with short-lived certificates and records events. – What to measure: Frequency of key rotations and submission success. – Typical tools: Sigstore signing clients, Rekor.

7. Centralized observability for signings – Context: Monitor signing activity across org. – Problem: No centralized view of signing patterns. – Why Rekor helps: Single source of truth for signing events. – What to measure: Submission rates, anomalies. – Typical tools: Prometheus, Grafana, Rekor.

8. Chaotic environment verification – Context: Multi-region deployments with forked CI. – Problem: Diverging artifacts and signatures across regions. – Why Rekor helps: Provides authoritative record to reconcile differences. – What to measure: Consistency across regions and replica health. – Typical tools: Multi-region Rekor setups, replica health checks.

9. Third-party vendor artifact verification – Context: Consuming third-party components. – Problem: Need proof vendor signed what they delivered. – Why Rekor helps: Vendors publish signatures in transparency logs. – What to measure: Verified vendor entries and validity. – Typical tools: Rekor query, SIEM.

10. Automation audit and governance – Context: Automation creates and approves releases. – Problem: Hard to prove who authorized what. – Why Rekor helps: Logs automated attestations with identity context. – What to measure: Attestation provenance and frequency. – Typical tools: CI/CD, Rekor, identity provider logs.

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Scenario Examples (Realistic, End-to-End)

Scenario #1 — Kubernetes admission gate for signed images

Context: Production Kubernetes clusters must only accept images with recorded attestations.
Goal: Block deployment of images unless Rekor contains a valid signature for that image digest.
Why Rekor matters here: Provides verifiable proof that image signing happened and was recorded.
Architecture / workflow: CI builds image -> signs -> submits signature to Rekor -> image pushed to registry -> Kubernetes admission webhook queries Rekor during pod creation.
Step-by-step implementation:

1. Integrate Rekor submission in CI after successful build and signing.
2. Configure admission controller to query Rekor by image digest.
3. Valid webhook enforces policy allowing only verified images.
4. Monitor admission rejects and Rekor availability metrics. What to measure: Admission accept/reject rate, Rekor query latency, write success rate.
   Tools to use and why: CI, Rekor client, OPA/Gatekeeper, Prometheus/Grafana.
   Common pitfalls: Index lag causing recent signatures to be not found; webhook misconfiguration.
   Validation: Run canary deployments and synthetic sign-and-deploy tests.
   Outcome: Deployments blocked if no verifiable evidence, improving supply chain guarantees.

Scenario #2 — Serverless function deploy with attestation check

Context: Managed PaaS for serverless functions requires proof that runtime bundles were signed.
Goal: Ensure only signed bundles are promoted to production.
Why Rekor matters here: Offers centralized verifiable records for signing events spanning many teams.
Architecture / workflow: Build system signs function bundle -> submits entry to Rekor -> PaaS deployment hook verifies Rekor entry before activation.
Step-by-step implementation: Integrate sign-and-submit in buildpack, add pre-deploy hook to call Rekor, configure failure handling to rollback.
What to measure: Pre-deploy verification success, Rekor availability from PaaS region.
Tools to use and why: CI, Rekor client, PaaS deployment hooks, synthetic monitors.
Common pitfalls: Network restrictions blocking Rekor API calls from PaaS region.
Validation: Test from staging and production networks and run game days.
Outcome: Reduced risk of runtime execution of unsigned bundles.

Scenario #3 — Incident response and postmortem reconstruction

Context: A production compromise requires identifying when a bad artifact was introduced.
Goal: Use Rekor records to build timeline of signing and promotions.
Why Rekor matters here: Immutable records provide forensic evidence for attribution and scope.
Architecture / workflow: Query Rekor by artifact hashes and signer IDs; correlate with CI and registry logs.
Step-by-step implementation: Export Rekor entries, correlate timestamps with deployment logs, gather inclusion proofs for legal records.
What to measure: Completeness of records and query success.
Tools to use and why: Rekor API, SIEM, forensic tools, backup archives.
Common pitfalls: Retention policy purged needed entries.
Validation: Periodic audit that reconstructs known historical events.
Outcome: Faster root cause and defensible audit trail.

Scenario #4 — Cost vs performance trade-off for Rekor archiving

Context: Log growth increases storage costs in a regulated organization.
Goal: Reduce cost while preserving auditability.
Why Rekor matters here: Needs balance between long retention and cost-effective storage.
Architecture / workflow: Active Rekor instance keeps recent entries; older entries archived to cold storage with preserved proofs.
Step-by-step implementation: Define retention window, implement archival job to export and cryptographically seal archived batches, update verification process to consult archives as needed.
What to measure: Storage cost trends, archive retrieval latency, archive completeness.
Tools to use and why: Object storage lifecycle policies, Rekor export tooling, retrieval API.
Common pitfalls: Archive format lacks proofs or is not verifiable.
Validation: Restore several archived entries and verify inclusion proofs.
Outcome: Lower operational cost while maintaining compliance.

Scenario #5 — Multi-region Rekor replica synchronization

Context: Global organization needs local Rekor replicas to reduce latency.
Goal: Provide local reads with eventual consistency.
Why Rekor matters here: Allows faster verification while keeping a global authoritative log.
Architecture / workflow: Primary Rekor writes replicate to regional replicas with consistency checks.
Step-by-step implementation: Deploy regional replicas, configure replication pipeline, monitor divergence, provide fallback to primary for writes.
What to measure: Replica lag, divergence count, failover success.
Tools to use and why: Message bus for replication, monitoring stack, Rekor replication config.
Common pitfalls: Divergence causing verification mismatches.
Validation: Periodic reconciliation and proof verification across regions.
Outcome: Improved verification latency with operational complexity managed.

Scenario #6 — Vendor-signed package verification before ingest

Context: Security team consumes third-party packages into internal catalog.
Goal: Allow only vendor-signed packages with Rekor evidence.
Why Rekor matters here: Centralized verification of vendor claims reduces supply chain risk.
Architecture / workflow: Vendor publishes signature in Rekor -> ingestion pipeline verifies Rekor entry before cataloging.
Step-by-step implementation: Configure ingestion to query Rekor by package hash and vendor identity, reject if absent.
What to measure: Rejection rates, Rekor query latency.
Tools to use and why: Ingestion pipeline, Rekor API, artifact scanning tools.
Common pitfalls: Different vendor practices and absent Rekor submissions.
Validation: Pilot with few vendors and expand policy.
Outcome: Better control over third-party artifacts.

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Common Mistakes, Anti-patterns, and Troubleshooting

List of 20 common mistakes with Symptom -> Root cause -> Fix.

1. Symptom: Recent signature not found in Rekor -> Root cause: Indexer lag or async indexing -> Fix: Monitor and scale indexer; add retries with backoff.
2. Symptom: CI jobs blocked waiting for Rekor -> Root cause: Synchronous verification with Rekor outage -> Fix: Add fallback retry logic or degrade to allow non-blocking operation with audit fallback.
3. Symptom: High write error rate -> Root cause: Storage full or database errors -> Fix: Increase storage and implement alerting for capacity.
4. Symptom: Proof verification fails -> Root cause: Storage corruption or misconfigured proof calculation -> Fix: Restore from backup and reindex; verify root.
5. Symptom: Unauthorized entries appear -> Root cause: Compromised submission credentials -> Fix: Revoke keys, rotate credentials, audit submissions.
6. Symptom: Admission controller rejects valid images -> Root cause: Using signature presence only without verifying artifact hash -> Fix: Verify artifact digest against signature.
7. Symptom: Excessive alert noise -> Root cause: Alerts trigger on transient spikes -> Fix: Tune alert windows and group similar alerts.
8. Symptom: Missing historical records -> Root cause: Aggressive retention and no archival -> Fix: Implement archival and adjust retention to compliance needs.
9. Symptom: Slow query times -> Root cause: Unindexed queries or overloaded DB -> Fix: Optimize indexes and scale query infrastructure.
10. Symptom: Replica mismatch -> Root cause: Replication failures or partial writes -> Fix: Reconcile replicas and repair pipeline.
11. Symptom: Secrets accidentally logged into Rekor -> Root cause: Unvalidated attestation content -> Fix: Sanitize attestation inputs and audit submissions.
12. Symptom: CI rate limits triggered -> Root cause: High-frequency submissions without batching -> Fix: Batch entries or throttle with backoff.
13. Symptom: Hard-to-debug failures -> Root cause: Insufficient correlation IDs in logs -> Fix: Add request IDs and trace propagation.
14. Symptom: Audit shows missing context -> Root cause: Incomplete submission metadata -> Fix: Standardize metadata fields in CI.
15. Symptom: DDoS causing Rekor outage -> Root cause: No rate limiting or WAF -> Fix: Implement network protections and throttling.
16. Symptom: Rekor root rotation breaks verification -> Root cause: Poor rotation coordination -> Fix: Plan rotations with re-signing and client updates.
17. Symptom: High storage cost -> Root cause: No lifecycle or archive policy -> Fix: Implement tiered storage and archival processes.
18. Symptom: False security alerts -> Root cause: Improperly tuned anomaly detection -> Fix: Improve baselining and whitelists.
19. Symptom: Deployment slowdown -> Root cause: Blocking verification for non-critical paths -> Fix: Use async verification for low-risk flows.
20. Symptom: Poor observability -> Root cause: Missing Prometheus metrics and traces -> Fix: Instrument Rekor and ingestion points for full observability.

Observability pitfalls (at least 5 included above):

• Missing request IDs -> correlating events is hard.
• Only monitoring writes, not index lag -> recent entries appear missing.
• No synthetic checks -> unaware of region-specific failures.
• Logs not parsed into SIEM -> security incidents missed.
• No retention monitoring -> compliance gaps emerge.

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Best Practices & Operating Model

Ownership and on-call:

• Designate a team that owns the Rekor service, including backups and SLA.
• On-call rotation should include a Rekor responder with runbook access.

Runbooks vs playbooks:

• Runbook: Step-by-step technical remediation for known failures.
• Playbook: Scenario-based guidance for complex incidents needing multiple teams.

Safe deployments:

• Canary deployments with verification against Rekor to validate sign-and-record steps.
• Automatic rollback when verification fails in production gates.

Toil reduction and automation:

• Automate submission in CI and verification in deploy pipelines.
• Automate backups, archival, and key rotations.

Security basics:

• Use strong authentication for clients submitting entries.
• Limit who can submit entries via authorization controls.
• Avoid storing secrets within attestation payloads.

Weekly/monthly routines:

• Weekly: Review failed submissions and index lag trends.
• Monthly: Verify archival integrity and run synthetic tests.
• Quarterly: Simulate root rotation and disaster recovery drills.

What to review in postmortems related to Rekor:

• Was Rekor submission successful before the incident?
• Were any entries missing due to retention or purge?
• Indexer and replica behaviors during the incident.
• Any unauthorized or suspicious submissions during the period.

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Tooling & Integration Map for Rekor (TABLE REQUIRED)

ID	Category	What it does	Key integrations	Notes
I1	CI/CD	Automates submit of signatures	CI systems and build tools	Instrument CI for idempotent submissions
I2	Signing client	Creates signatures and attestations	Rekor API and KMS	Can be keyless or key-backed
I3	Admission controller	Enforces Rekor checks at runtime	Kubernetes, OPA	Use for gating deployments
I4	Monitoring	Collects metrics and alerts	Prometheus/Grafana	Tracks SLIs and SLOs
I5	Logging	Centralizes Rekor logs	Loki/ELK, SIEM	For forensic and security use
I6	SIEM	Security event correlation	SIEM systems	Feed suspicious submit events
I7	Archive storage	Long-term retention and export	Object storage and archives	Preserve cryptographic proofs
I8	Policy engine	Translates Rekor findings into actions	OPA/Gatekeeper	Use for automated enforcement
I9	Tracing	Distributed traces for Rekor calls	OpenTelemetry backends	Diagnose latency and errors
I10	Replica sync	Replicates log across regions	Message bus and object storage	Ensure eventual consistency

Row Details (only if needed)

• None

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Frequently Asked Questions (FAQs)

What is Rekor’s primary purpose?

Rekor provides an immutable, verifiable record of signing and attestation metadata to support software supply chain verification.

Is Rekor a signing tool?

No, Rekor stores metadata about signatures but does not perform cryptographic signing itself.

Can Rekor be self-hosted?

Yes, Rekor can be deployed self-hosted for organizational control; deployment details vary based on scale.

Does Rekor replace an artifact registry?

No, Rekor complements registries by storing signing metadata, not artifact binaries.

How do you verify an entry in Rekor?

By querying for an entry ID or artifact hash and validating the inclusion and consistency proofs returned.

Is Rekor secure against tampering?

Rekor’s append-only and proof mechanisms provide tamper-evidence; security depends on deployment integrity and storage protections.

Should Rekor be synchronous in deployment gates?

Depends; synchronous checks provide stronger safety but can introduce availability risk. Use fallbacks or async checks when needed.

What do I store in Rekor entries?

Store signatures, attestations, artifact hashes, timestamps, and signer identity. Avoid secrets or PII.

How long should Rekor keep entries?

Varies / depends on compliance and audit needs; consider archival for long-term retention.

How does Rekor handle scale?

Scale depends on underlying storage, indexer capacity, and deployment architecture; monitor SLOs and autoscale where possible.

Can Rekor support multi-region reads?

Yes with replication; ensure consistent synchronization and reconciliation processes.

What happens if Rekor is down?

Verification steps may fail; implement graceful degradation, retries, or cached proofs for resilience.

How to detect unauthorized Rekor writes?

Monitor failed auth attempts, abnormal submitter patterns, and enable SIEM correlation for anomalies.

Is Rekor suitable for small projects?

It can be, but evaluate cost and operational overhead; hosted solutions might be a practical starting point.

How to prove entry integrity long-term?

Archive entries with preserved inclusion proofs and verify periodically.

How do you test Rekor in CI?

Submit sample entries and verify inclusion proofs in automated pipeline tests.

How does Rekor affect deployment velocity?

If implemented correctly, it can increase velocity by automating attestations; poorly designed gating can slow deployments.

Who should own Rekor within an org?

Security or platform engineering commonly owns Rekor, with defined SLAs and on-call responsibilities.

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Conclusion

Rekor is a critical transparency log building block for verifiable software supply chains. It provides immutable records for signatures and attestations, enabling stronger security posture, faster incident response, and compliance evidence. Successful adoption requires thoughtful integration into CI/CD, monitoring and SLOs, archive policies, and operational readiness.

Next 7 days plan:

• Day 1: Identify use cases and decide hosted vs self-hosted Rekor.
• Day 2: Integrate Rekor submit step into a single CI pipeline and validate.
• Day 3: Instrument Rekor with Prometheus metrics and basic dashboards.
• Day 4: Implement a simple verification gate in a non-critical deployment path.
• Day 5: Run synthetic write/read checks and create alert rules.
• Day 6: Define retention and archival policy and test exporting an entry.
• Day 7: Run a short game day simulating indexer lag and rehearse runbook steps.

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Appendix — Rekor Keyword Cluster (SEO)

• Primary keywords
• Rekor transparency log
• Rekor guide
• Rekor tutorial
• Rekor supply chain
• Rekor usage
• Rekor deployment
• Rekor integration
• Rekor best practices
• Rekor metrics

• Rekor SLO

• Secondary keywords

• Rekor versus Sigstore
• Rekor transparency proofs
• Rekor architecture
• Rekor indexer
• Rekor retention
• Rekor monitoring
• Rekor admission controller
• Rekor CI integration
• Rekor archival

• Rekor security

• Long-tail questions

• What is Rekor used for in CI CD
• How to verify Rekor entry proofs
• How does Rekor compare to Notary
• How to set up Rekor in Kubernetes
• How to monitor Rekor index lag
• How to archive Rekor entries for compliance
• How to integrate Rekor with OPA Gatekeeper
• How to handle Rekor downtime in pipelines
• How to detect unauthorized Rekor writes

• How to measure Rekor SLOs

• Related terminology

• transparency log
• attestation storage
• inclusion proof
• consistency proof
• merkle tree proof
• artifact hash verification
• keyless signing
• provenance attestation
• admission control policy
• supply chain security
• CI signing client
• Rekor indexer lag
• Rekor write latency
• Rekor query latency
• Rekor retention policy
• Rekor archive verify
• Rekor synthetic checks
• Rekor runbook
• Rekor postmortem
• Rekor SLI metrics
• Rekor SLA planning
• Rekor replica sync
• Rekor root rotation
• Rekor proof validation
• Rekor SIEM integration
• Rekor forensic evidence
• Rekor deployment gate
• Rekor supply chain audit
• Rekor observability
• Rekor trace instrumentation
• Rekor Prometheus metrics
• Rekor Grafana dashboards
• Rekor admission webhook
• Rekor policy enforcement
• Rekor authentication
• Rekor authorization
• Rekor scalability
• Rekor high availability
• Rekor backup strategy
• Rekor cost optimization

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