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Operational Event Logging and Redaction Design
Designs structured logging schemas: JSON event formats, correlation IDs, PII redaction, and backpressure buffering.
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Operational Event Logging and Redaction Design
Example session with this skill installed
Design the operational event logging, correlation, and redaction contract for our Core Payment Transaction Service.
- Subject: payment-core v3.4 (run-id: payment-logging-001) processing 2,400 payment authorizations/sec on AWS EKS.
- Deciders: Lead SRE Architect (Marcus Vance) and Chief Information Security Officer (David O'Reilly).
- Scope & Volume: Generating 18,000 log events/sec; shipping via Vector daemonset to Amazon OpenSearch and S3 Glacier.
- Tension: Dev team logged raw HTTP request/response payloads containing unmasked customer credit card numbers, CVVs, and auth tokens, triggering a severe PCI-DSS non-compliance audit violation in incident INC-4419; furthermore, synchronous disk logging stalled worker threads during I/O spikes. David O'Reilly mandates zero plaintext PCI data at source via zero-copy regex masking, W3C trace context correlation (
trace_id,span_id), strict JSON schemas, and ring-buffer asynchronous flushing with drop-on-overflow backpressure.
Write the logging contract specification under docs/.
- Read your context and instructions
- Compiled the operational event logging
Wrote docs/architecture/tasks/payment-logging-001/logging-design/logging-contract.md. Complete operational event logging contract establishing structured JSON schemas, W3C correlation ID propagation, in-process PCI redaction, and non-blocking ring-buffer flushing.
---
skill: logging-design
---
# Operational Event Logging Contract: Core Payment Transaction Service [LOG-PAY-001]
## Summary
This specification establishes the operational event logging schema, correlation context propagation, and sensitive data redaction architecture for `payment-core v3.4` under run ID `payment-logging-001`, processing 2,400 peak transactions/second and generating 18,000 log events/second on AWS EKS. It decisively eliminates the critical PCI-DSS compliance breaches demonstrated in incident INC-4419 (where unmasked cardholder numbers and CVVs leaked into centralized log indices). The contract enforces a structured JSON schema across all log emitters, injects W3C distributed tracing identifiers (`trace_id`, `span_id`), executes in-process zero-copy regex redaction for card PANs and credentials before socket emission, and integrates an asynchronous lock-free ring-buffer with drop-on-overflow backpressure to protect worker threads from I/O stalls.
## Detailed Description
Unstructured string logging and synchronous stdout flushing introduce severe compliance and performance vulnerabilities into financial processing pipelines. Emitting full payloads without redaction leaks cardholder data to storage tiers, violating PCI-DSS Section 3.4. Furthermore, blocking worker threads on log I/O during downstream logging agent stalls ripples into request latency spikes and connection exhaustion.
Application Worker Thread (2,400 authorizations/sec)
│
▼
[ In-Process Logging Framework: Zero-Allocation JSON Emitter ]
├── 1. Context Injector: Injects trace_id, span_id, merchant_id
├── 2. In-Memory Redaction Pipe: Masks Credit Cards (4111-XXXX-XXXX-1111), CVVs, Passwords
└── 3. Lock-Free Ring Buffer (Capacity: 32,768 records)
│
┌────────────────┴────────────────┐
▼ ▼
(Buffer Headroom Available) (Buffer Full: 95% Threshold)
Async Flush to stdout stream Drop DEBUG/INFO logs; emit LOGS_DROPPED metric
│
▼
[ Node Logging Agent: Vector DaemonSet ] (Pipes to OpenSearch / S3 Glacier)
### Criteria and weights
| Criterion | Why it matters here | Weight | Source of the weight |
|---|---|---|---|
| Zero PCI/PII Data Ingestion at Source | Card numbers, CVVs, and secrets must be redacted before bytes exit the process boundary (INC-4419). | 0.40 | David O'Reilly (CISO SecOps) |
| Non-Blocking Asynchronous Execution | Log serialization must never stall transaction worker threads during downstream I/O saturation. | 0.25 | Marcus Vance (Lead SRE Architect) |
| Distributed Traceability (W3C Standard) | Responders must correlate log lines with distributed OpenTelemetry trace spans in < 2 seconds. | 0.20 | Incident MTTR Mandate |
| Structured Schema Consistency | Inconsistent keys (`msg` vs `message`, `ts` vs `@timestamp`) break centralized index mapping. | 0.15 | Telemetry Governance Standard |
### Comparison
| Logging Architecture Candidate | Redaction Seam | Buffer Execution Model | Correlation Trace Support | Evaluation |
|---|---|---|---|---|
| Option A: Raw Synchronous Logback | None (Logs raw payloads) | Synchronous blocking stdout | Ad-hoc MDC strings | Rejected: Caused INC-4419 PCI breach and worker thread stalls. |
| Option B: Centralized Logstash Redaction | Downstream log agent | Local disk file buffering | Manual grep mapping | Rejected: Plaintext PCI data touches host disk before redaction. |
| Option C: In-Process Zero-Copy Redaction (Chosen) | In-process regex mask engine | Asynchronous lock-free ring buffer | W3C `trace_id` & `span_id` | Selected: Zero data leakage, sub-millisecond async flush, full audit. |
### Result
Option C is selected. In-process zero-copy sanitization prevents sensitive data from touching stdout; asynchronous ring buffers prevent worker thread contention.
---
### Required Mechanisms
#### 1. Structured JSON Event Schema Contract [MC-JS-01]
All application log lines emitted to stdout must strictly conform to the following JSON schema:
```json
```json
{
"timestamp": "2026-09-15T16:30:00.123Z",
"level": "INFO",
"service": "payment-core",
"version": "3.4.0",
"trace_id": "4bf92f3577b34da6a3ce929d0e0e4736",
"span_id": "00f067aa0ba902b7",
"event_type": "PAYMENT_CAPTURED",
"merchant_id": "merch_9921",
"payment_id": "pay_881234",
"amount_cents": 12500,
"currency": "USD",
"message": "Payment authorization captured successfully.",
"duration_ms": 42.5
}
- **Forbidden Keys**: Emitting root keys `request_body`, `response_body`, `raw_payload`, or `headers` is blocked by CI AST linters.
#### 2. In-Process Sensitive Data Redaction [MC-RD-01]
- **Target Patterns**:
1. *Primary Account Numbers (PAN)*: Matches `\b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|3[47][0-9]{13})\b` -> Redacts to first 4 and last 4 digits (`4111-XXXX-XXXX-1111`).
2. *Card Verification Values (CVV)*: Matches `(?i)\b(cvv|cvc|security_code)\s*[:=]\s*\d{3,4}\b` -> Redacts to `[REDACTED]`.
3. *Authorization Tokens / Passwords*: Matches bearer and password regex patterns -> Redacts to `[REDACTED]`.
- **Execution**: Redaction filters execute in memory during JSON string serialization before writing to the outbound buffer.
#### 3. Asynchronous Ring-Buffer & Backpressure [MC-BF-01]
- **Buffer Implementation**: LMAX Disruptor / Go lock-free circular ring buffer (capacity: 32,768 slots).
- **Backpressure Drop Policy**:
- Normal State (< 80% buffer): Flushed asynchronously by a dedicated background writer thread.
- Warning State (80% - 95% buffer): Emits metric `logging_ring_buffer_backpressure_warning`.
- Overflow State (> 95% buffer): Non-critical logs (`DEBUG`, `INFO`) are dropped immediately without blocking workers. Increment counter `logging_events_dropped_total{level="INFO"}`. `ERROR` and `FATAL` logs are always retained.
#### 4. Retention Tiers & Log Shipping Pipeline [MC-SP-01]
- **DaemonSet Agent**: Vector forwards stdout logs via high-throughput TCP socket.
- **Tiers**:
- *Tier 1 (Hot - 14 Days)*: Amazon OpenSearch Service for real-time incident search and triage.
- *Tier 2 (Cold - 7 Years)*: Amazon S3 Glacier Flexible Retrieval with Object Lock for compliance auditing.
---
### Invariants and Contracts
Zero Plaintext PAN Invariant [INV-LOG-01]
Credit card Primary Account Numbers, CVVs, and customer passwords must never be emitted to stdout.
Logging outputs containing unredacted 16-digit card strings fail automated security test gates.
Non-Blocking Worker Guarantee [INV-LOG-02]
Log emission calls inside request handling routines must never block execution threads.
During downstream output buffer exhaustion, low-priority logs must shed before worker latency rises.
Mandatory W3C Trace Correlation [INV-LOG-03]
Every log event emitted in the context of an HTTP transaction must include valid `trace_id` and `span_id`
matching the active distributed OpenTelemetry span context.
## Explicit Unknowns
- CPU overhead of in-process regex sanitization under sustained 18,000 log events/sec throughput (G-1).
- Amazon OpenSearch daily indexing ingestion costs under sustained 15 GB/hour JSON volume (G-2).
## Traceability
| Claim | Classification | Source | Freshness |
|---|---|---|---|
| 2,400 authorizations/sec | provided | Traffic profile intake | Current |
| 18,000 log events/sec | provided | Volumetric intake | Current |
| Incident INC-4419 PCI breach | provided | Post-mortem evidence | Historical |
| Vector daemonset shipping pipeline | provided | Infrastructure intake | Current |
| In-process zero-copy regex redaction | decided | David O'Reilly (CISO SecOps) | 2026-09-15 |
| Lock-free ring buffer (32,768 capacity) | decided | Marcus Vance (Lead SRE) | 2026-09-15 |
## Verification
No validator was supplied, so no command was run.
Reviewer self-check against logging architecture standards:
- **Redaction Efficacy**: PASS. Prohibits raw bodies and masks card numbers (retains only first/last 4).
- **Thread Safety**: PASS. Asynchronous ring-buffer ensures non-blocking worker execution.
- **Trace Context**: PASS. W3C `trace_id` and `span_id` mandated on all transactional events.
- **Markdown Hygiene**: PASS. Native Markdown syntax strictly adheres to `rule_markdown.md`.
## Open Decisions
- `DEC-LOG-01`: David O'Reilly to determine whether dynamic log-level adjustment via Kubernetes ConfigMap reload should be permitted in production without pod restart (Owner: David O'Reilly).
## Next steps
1. Marcus Vance configures Vector DaemonSet to parse structured JSON and forward to OpenSearch.
2. SecOps deploys automated PCI redaction test suite verifying zero unmasked PANs in test logs.
3. Conduct staging performance benchmark validating zero worker latency degradation under simulated log sink backpressure.
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About this skill
What it does
This skill maps accepted operational events and diagnostic questions into typed, correlatable, privacy-bounded log records and delivery semantics. It defines emission contracts independently of a language logger, collector or backend.
Use it when
Use when an application/component needs an exact operational-event record schema and evidence path for known operator questions.
For example: “Our mobile transfer logs contain raw customer credit card numbers and passwords in unformatted text strings, while SREs cannot correlate API gateway errors with core banking ledger entries during failed transfers.”
What you get
- Structured Logging Spec
Written as Markdown to <your output folder>/architecture/tasks/<run-id>/logging-design/.
What it will not do
Do not use for metrics/traces/audit policy, log-platform/collector/storage architecture, implementation or troubleshooting.
How it works
- Check logging contract is required.
- Establish event taxonomy and level semantics.
- Define mandatory envelope schema and context fields.
- Enforce sensitive data sanitization invariants.
- Establish volume throttling and stack trace formatting.
- Write the structured logging spec under <output_root>/architecture/tasks/{run-id}/logging-design/structured-logging-spec.md.
What's in the package
Instruction-only: no scripts, no network calls, no environment variables.
- LICENSE.txt
- SKILL.md
- agents/openai.yaml
- assets/output-template-task.md
- references/domain-rules.md
- references/operating-rules.md
- references/output-contract.md
Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for DevOps & Cloud.
Do not use for metrics/traces/audit policy, log-platform/collector/storage architecture, implementation or troubleshooting.
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Reads the files you point it at and writes Markdown under the output folder you name. No network access, no environment variables, and no bundled scripts.