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ngit-grasp/docs/explanation/monitoring.md
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DanConwayDev fd7c6bb851 refactor(auth): make current maintainer authority explicit
The v3.0.1 authorization fix is intentionally small. Follow it with a separate structural pass so the implementation and documentation express the present-tense maintainer model directly instead of leaving the security behavior hidden behind owner-oriented names and repeated raw-tag interpretation.

Parse indexed roles once into a current-only snapshot of active maintainers, active lead targets, and announcement-author activity. Preserve detailed lead-resolution failures internally while policy callers continue to fail closed, distinguish selected authorization coordinates from physical owner views, and name broad announcement admission as discovery rather than authority.

Keep history relevant only while deriving current activity and retain active leads only for selected-coordinate resolution. Preserve the v3.0 public API through compatibility projections and deprecated aliases; this commit is not intended to change the authorization outcome established by 650cfb57.

Refresh architecture, inline authorization, storage, sync, and audit documentation. Correct the audit fixture description that claimed a listed maintainer authorized with no reciprocal announcement even though its setup already published one.

Validated with cargo test --lib (903 tests), cargo test --test state_authorization (53 tests), cargo test -p grasp-audit --lib (54 passed, 5 ignored), cargo test --test push_authorization (56 tests), and cargo clippy --tests -- -D warnings.
2026-08-29 21:20:49 +00:00

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Monitoring

ngit-grasp exposes Prometheus metrics at /metrics for monitoring WebSocket connections, Git operations, Nostr events, and system health.

Architecture

flowchart TB
    subgraph ngit-grasp
        HTTP[HTTP Service]
        WS[WebSocket Handler]
        GIT[Git Handlers]
        RELAY[Nostr Relay]
        
        subgraph Metrics Module
            REG[Prometheus Registry]
            CT[ConnectionTracker]
            MC[Metric Counters]
        end
        
        ME[/metrics endpoint]
    end
    
    subgraph External
        PROM[Prometheus Server]
        GRAF[Grafana]
        ADMIN[Admin Browser]
    end
    
    HTTP --> ME
    WS --> CT
    WS --> MC
    GIT --> MC
    RELAY --> MC
    
    CT --> REG
    MC --> REG
    REG --> ME
    
    PROM -->|scrape /metrics| ME
    GRAF -->|query| PROM
    ADMIN -->|view dashboards| GRAF

Configuration

Option CLI Flag Environment Variable Default Description
Metrics enabled --metrics-enabled NGIT_METRICS_ENABLED true Enable /metrics endpoint
Abuse threshold --abuse-threshold NGIT_ABUSE_THRESHOLD 10 Max connections per IP before flagging
Top N repos --top-n-repos NGIT_TOP_N_REPOS 10 Number of top bandwidth repos to track

Logging severity policy

Operational logging classifies records by who can act on them:

  • error identifies an internal, persistence, or process failure that may require an operator response.
  • warn identifies a degraded application path, bounded retry, or cooldown that affects service behavior but remains recoverable.
  • info records application lifecycle, aggregate batch outcomes, and durable state transitions.
  • debug carries individual client, peer, event, filter, and capability negotiation details. Invalid or unsupported remote input is expected on a public relay and is not operator-actionable by itself.

For a bare NGIT_LOG_LEVEL, dependencies remain at warn while the selected level applies to ngit-grasp. Use an explicit tracing filter expression when a dependency needs temporary diagnostics.

Privacy Model

IP addresses are never exposed in Prometheus metrics. The connection tracker maintains per-IP counts internally only for abuse detection:

Data Exposed in Metrics?
Total connections ✅ Yes
Unique IP count ✅ Yes
Flagged abuser count ✅ Yes
Actual IP addresses ❌ No (internal only)
IP + abuse flag ⚠️ Logs only (when flagged)

When an IP exceeds the abuse threshold, a warning is logged but the IP is never exposed via Prometheus.

Deployment

See Prometheus Setup Guide for NixOS configuration and Grafana dashboard provisioning.

Deletion Lifecycle Metrics

The deletion/recovery operational paths expose these additional metrics:

Metric Type Labels Description
ngit_blacklist_deletions_total Counter phase, result Startup blacklist parity deletion attempts/success/failure
ngit_holding_cleanup_runs_total Counter - Number of holding cleanup passes run
ngit_holding_cleanup_deleted_total Counter type Total deleted objects by cleanup (metadata, payload, archive_file)
ngit_holding_cleanup_last_run_deleted Gauge type Deleted object counts for most recent cleanup pass
ngit_deletion_request_cleanup_runs_total Counter - Number of deletion-request cleanup passes run
ngit_deletion_request_cleanup_removed_total Counter type Deletion-request payloads and lifecycle metadata removed (main, tombstone, metadata)
ngit_deletion_request_cleanup_outcomes_total Counter outcome Deletion-request cleanup failures and stale/concurrent skips (failure, stale_or_concurrent_skip)
ngit_recovery_total Counter result Recovery attempts and outcomes (attempted, succeeded, failed, partial)
ngit_manual_ejections_total Counter - Number of operator manual ejection operations
ngit_manual_ejection_deleted_total Counter type Objects removed by manual ejection (metadata, payload, archive_file)

Future: Load-Based Sync Scheduling (GRASP-02)

The metrics infrastructure enables future load-based scheduling for GRASP-02 sync jobs:

flowchart TD
    SYNC[Sync Manager] --> CHECK{Check Load}
    CHECK --> MET[Query Metrics]
    MET --> CONN{Connections > N?}
    CONN -->|Yes| DELAY[Delay 5 min]
    CONN -->|No| RUN[Run Sync Job]
    DELAY --> CHECK

Future: Loki for Detailed Logging

For detailed per-repository investigation at scale, consider adding Loki (log aggregation):

  • Structured logging with tracing crate already in place
  • Loki queries enable ad-hoc deep dives (e.g., find all transfers > 10MB)
  • Pairs with Prometheus for long-term trends

Sync Metrics (GRASP-02)

When GRASP-02 proactive sync is implemented, the following metrics will be added to track relay synchronization health. These metrics use in-memory tracking with Prometheus for operator visibility (no database persistence needed for <100 relays).

Sync Metrics Overview

Metric Type Labels Description
ngit_sync_relay_connected Gauge relay Connection status (0=disconnected, 1=connecting, 2=syncing, 3=connected, 4=connected_historic_sync_failures)
ngit_sync_connection_attempts_total Counter relay, result Connection attempt outcomes
ngit_sync_relay_status Gauge relay Health status (1=healthy, 2=disconnected, 3=degraded, 4=dead, 5=rate_limited, 6=policy_limited)
ngit_sync_policy_refusals_total Counter relay, category Subscription policy refusals using bounded categories; raw reasons remain in logs
ngit_sync_relay_failures Gauge relay Current consecutive failure count
ngit_sync_events_synced_total Counter - Events synced (newly saved events only)
ngit_sync_hydration_events_total Counter relay, phase, outcome Remote hydration requests, deliveries, and bounded persistence/admission outcomes; phase is stream or recovery
ngit_sync_relays_tracked_total Gauge - Total relays discovered
ngit_sync_relays_connected_total Gauge - Currently connected relay count
ngit_sync_relays_dead_total Gauge - Relays marked as dead

Connection Status Values

The ngit_sync_relay_connected metric tracks the connection lifecycle:

  • 0 = Disconnected - Not currently connected
  • 1 = Connecting - Connection attempt in progress
  • 2 = Syncing - Connected, historic sync in progress
  • 3 = Connected - Connected, historic sync complete, live sync active
  • 4 = ConnectedHistoricSyncFailures - Connected, historic sync had failures, live sync active, partial data

This allows operators to distinguish between "connected but still catching up" (Syncing) vs "fully synced and live" (Connected) vs "historic sync failures - missing historic data" (ConnectedHistoricSyncFailures).

Relay Health States

The ngit_sync_relay_status metric tracks relay health:

  • 1 = Healthy - Connected and stable
  • 2 = Disconnected - Not connected, but no issues detected
  • 3 = Degraded - Connection problems or unstable after recovery
  • 4 = Dead - 24h+ of continuous failures
  • 5 = RateLimited - Rate limit cooldown active (65s)

After a too many queries response, Activated adaptive query-start pacing reports the learned per-connection interval. It begins at 600 ms and doubles only when a distinct later episode proves that pace too fast. Queued starts unwind during the existing 65-second cooldown before paced recovery; reconnecting clears that reactive lesson. Independent proactive pacing still spaces background historic and dependency starts at one per second; persistent live subscriptions bypass the background gate. Falling back to paced REQs for the query-limited connection session means NIP-77 remains skipped until reconnect because SDK-managed NEG-MSG traffic cannot be passed individually through the learned gate.

Example Grafana Queries

# Relay connection status overview - count by status
sum by (relay) (ngit_sync_relay_connected == 0)  # Disconnected
sum by (relay) (ngit_sync_relay_connected == 1)  # Connecting
sum by (relay) (ngit_sync_relay_connected == 2)  # Syncing
sum by (relay) (ngit_sync_relay_connected == 3)  # Connected
sum by (relay) (ngit_sync_relay_connected == 4)  # ConnectedHistoricSyncFailures

# Relays still syncing (not yet fully caught up)
count(ngit_sync_relay_connected == 2)

# Relays with historic sync failures (missing historic data)
count(ngit_sync_relay_connected == 4)

# Connection success rate over last hour
sum(rate(ngit_sync_connection_attempts_total{result="success"}[1h]))
/ sum(rate(ngit_sync_connection_attempts_total[1h]))

# Event sync rate (newly saved events)
rate(ngit_sync_events_synced_total[5m])

# Exact-ID responses that a source did not deliver
sum by (relay) (rate(ngit_sync_hydration_events_total{phase="recovery",outcome="not_delivered"}[15m]))

# Delivered events that were not made servable
sum by (relay, outcome) (
  rate(ngit_sync_hydration_events_total{outcome=~"purgatory|rejected_.*|persistence_error"}[15m])
)

# Relays with high failure counts (potential issues)
topk(10, ngit_sync_relay_failures)

# Relay health overview - count by health state
sum(ngit_sync_relay_status == 1)  # Healthy
sum(ngit_sync_relay_status == 2)  # Disconnected
sum(ngit_sync_relay_status == 3)  # Degraded
sum(ngit_sync_relay_status == 4)  # Dead
sum(ngit_sync_relay_status == 5)  # RateLimited

Example Alerts

# Alert if relay stuck in dead state for > 1 day
- alert: SyncRelayDead
  expr: ngit_sync_relay_status == 4  # Dead state
  for: 1d
  labels:
    severity: warning
  annotations:
    summary: "Sync relay {{ $labels.relay }} is dead (24h+ failures)"

# Alert if relay stuck in syncing state for > 1 hour
- alert: SyncRelaySlow
  expr: ngit_sync_relay_connected == 2  # Syncing state
  for: 1h
  labels:
    severity: info
  annotations:
    summary: "Sync relay {{ $labels.relay }} taking >1h to complete historic sync"

# Alert if too many relays are degraded
- alert: SyncManyDegraded
  expr: sum(ngit_sync_relay_status == 3) > 5  # Degraded state
  for: 15m
  labels:
    severity: warning
  annotations:
    summary: "{{ $value }} relays in degraded state"

Design Rationale

In-memory health tracking with Prometheus visibility was chosen over database persistence because:

  1. Scale: <100 relays means per-relay labels have acceptable cardinality
  2. Simplicity: No database schema, migrations, or cleanup needed
  3. Operator visibility: Prometheus + Grafana provide better dashboards than custom queries
  4. Restart behavior: Conservative initial backoff (5s + jitter) avoids thundering herd on restart
  5. Historical data: Prometheus retains health history; in-memory state only needs current status

See GRASP-02 Proactive Sync for full architecture details.

Rejected Events Index Metrics

The rejected events index tracks rejected repository announcements and state events to prevent wasteful re-fetching during negentropy sync and enable race condition resolution.

Rejected Events Metrics

All metrics are parameterized by event_type label with values "announcement" or "state":

Metric Type Labels Description
ngit_rejected_hot_cache_current Gauge event_type Current number of entries in hot cache
ngit_rejected_cold_index_current Gauge event_type Current number of entries in cold index
ngit_rejected_hot_cache_hits Counter event_type Events retrieved by the explicit invalidation API
ngit_rejected_hot_cache_misses Counter event_type Explicit invalidations whose full event had already expired
ngit_rejected_hot_cache_expired Counter event_type Entries cleaned up from hot cache (2 min expiry)
ngit_rejected_cold_index_expired Counter event_type Entries cleaned up from cold index (7 day expiry)
ngit_rejected_invalidated Counter event_type Entries removed by the explicit invalidation API

The invitation dependency-recovery path is deliberately non-destructive and does not increment the hit, miss, or invalidation counters above. It retains cold IDs until processing succeeds. Operators can observe exact-ID attempts in structured logs containing Fetched purgatory dependencies by exact event ID; the current and expiry gauges still cover entries used by both paths.

Example Grafana Queries

# Explicit invalidation API hot-cache efficiency
rate(ngit_rejected_hot_cache_hits_total[5m])
/ (rate(ngit_rejected_hot_cache_hits_total[5m]) + rate(ngit_rejected_hot_cache_misses_total[5m]))

# Current rejected events by type
ngit_rejected_hot_cache_current{event_type="announcement"}
ngit_rejected_hot_cache_current{event_type="state"}
ngit_rejected_cold_index_current{event_type="announcement"}
ngit_rejected_cold_index_current{event_type="state"}

# Explicit invalidation activity
rate(ngit_rejected_invalidated_total[5m])

# Explicit invalidation cache hit ratio over time
sum(rate(ngit_rejected_hot_cache_hits_total[5m]))
/ sum(rate(ngit_rejected_hot_cache_hits_total[5m]) + rate(ngit_rejected_hot_cache_misses_total[5m]))

Example Alerts

# Alert if cold index growing too large
- alert: RejectedEventsColdIndexSize
  expr: ngit_rejected_cold_index_current > 10000
  for: 1h
  labels:
    severity: info
  annotations:
    summary: "Rejected events cold index has {{ $value }} entries"
    description: "Consider investigating why many events are being rejected"

Two-Tier Architecture

Hot Cache (2 minutes):

  • Stores full event objects
  • Enables immediate re-processing when dependencies arrive
  • Cleaned up every 60 seconds
  • Memory: ~200 KB typical, ~20 MB worst case

Cold Index (7 days):

  • Stores metadata only (event ID, pubkey, identifier, reason)
  • Prevents re-downloading during negentropy sync
  • Supplies exact IDs when dependency-resolvable full events have left the hot cache
  • Cleaned up daily
  • Memory: ~1 MB typical

Use Cases

Race Condition Resolution: When a maintainer announcement arrives before the owner announcement:

  1. Maintainer event rejected → hot cache + cold index
  2. Reciprocal owner announcement enters purgatory → retain the cold ID until recovery succeeds
  3. If still in hot cache → immediate policy re-processing
  4. If expired from hot cache → exact-ID requests run in parallel across the maintainer-discovery relay dependencies
  5. Empty or failed requests keep the ID for a throttled retry
  6. Successful processing removes the event from both tiers

Negentropy Sync Efficiency: During sync, cold index IDs are excluded from "missing events" calculation, preventing wasteful re-download of events that will be rejected again.

See GRASP-02: Integration with Rejected Events Index for the recovery flow.