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GRASP-02 Proactive Sync: Purgatory Git Data Fetching

Status: ✅ Implemented
Implementation: src/purgatory/sync/
Related:


Overview

When Nostr events arrive before their git data, they enter purgatory waiting to be served. But they don't wait passively—ngit-grasp actively hunts for the missing git data across all git servers assoicated with the repo until it finds what it needs.

How It Works

If the data exists, we'll find it.

The system scours git servers listed in repository announcements and PR events, checking every 2 minutes for 30 minutes. If we find the data, events are released immediately. If not, they expire from purgatory after 30 minutes.

Smart timing based on how events arrive:

  • User-submitted events: Wait 3 minutes before hunting—we expect a git push to follow shortly
  • Sync-received events: Start hunting after just 500ms—batch burst arrivals, then get to work

Playing nicely with other servers:

We respect remote server capacity with:

  • Throttling: Max 5 concurrent requests per domain, 30 requests/minute
  • Backoff: Start at 20 seconds, double each attempt, cap at 2 minutes
  • Round-robin: Fair distribution across repositories waiting for the same domain
  • Fresh start: New events reset retry count—recent updates often mean fresh data

The result: If git data is available anywhere in the clone URL list, we'll find it within minutes. If it's not available within 30 minutes, the events expire cleanly.

Key Features

✅ Proactive hunting - Scours git servers every 2 min (backoff), finds data automatically
✅ Respectful throttling - 5 concurrent + 30/min per domain, plays nice with other implementations
✅ Smart timing - 3min delay for user pushes, 500ms for synced events
✅ 30min expiry - Auto-cleanup of events when data never arrives
✅ Fully testable - Mock-based architecture for reliable unit tests


The Problem: Out-of-Order Arrival

In a distributed system, git data and Nostr events can arrive in any order:

Timeline A: Event arrives first (user push expected)
  t=0s:   State event received → enters purgatory
  t=180s: (3min wait - expecting git push)
  t=30s:  Git push arrives → event released ✅

Timeline B: Git arrives first
  t=0s:  Git push received → data available
  t=30s: State event received → immediately served ✅

Timeline C: Sync scenario (hunt for data)
  t=0s:   State event received from relay X → enters purgatory
  t=0.5s: (500ms delay to batch bursts)
  t=0.5s: Start hunting git servers → check server1, server2, server3...
  t=45s:  Git data found on server2 → event released ✅

Timeline D: Data never arrives
  t=0s:    State event received → enters purgatory
  t=0.5s:  Start hunting → server1 (not found), server2 (timeout), server3 (not found)
  t=20s:   Retry → server1 (not found), server2 (not found), server3 (not found)
  t=60s:   Retry → all servers checked, no data
  ...
  t=1800s: 30 minutes expired → event discarded, purgatory cleaned up 🗑️

Without proactive sync: Events in Timeline C would wait indefinitely (or until manual git push).
With proactive sync: System automatically hunts for data across all known servers, releasing events as soon as the data is found.


Architecture: Two-Path Sync Design

The system uses two independent execution paths that work together:

Path 1: Main Sync Loop (Non-Throttled URLs)

Runs every 1 second, processes identifiers ready for sync:

  1. Find ready identifiers (where !in_progress && next_attempt <= now)
  2. Spawn parallel tasks for each identifier
  3. Each task tries non-throttled URLs until:
    • ✅ All OIDs fetched (complete) → remove from queue
    • ⏸️ Only throttled URLs remain → enqueue with throttled domains, apply backoff
    • ❌ No URLs left (all tried/throttled) → apply backoff, retry later

Key insight: Main loop doesn't wait for throttled domains. It quickly tries available servers, then hands off to domain queues for rate-limited processing.

Path 2: Domain Throttle Queues (Throttled URLs)

Trigger-based (no polling), processes when capacity frees:

  1. Identifier enqueued with throttled domain (from main loop)
  2. When domain has capacity (slot frees or rate limit window passes):
    • Pick next identifier (round-robin for fairness)
    • Try one URL from that domain
    • Mark URL as tried, release slot
  3. Trigger repeats until queue empty or capacity exhausted

Key insight: Each domain independently manages its queue, ensuring we respect rate limits while maximizing throughput.


Data Flow: From Event to Release

graph TB
    A[Event Arrives] --> B{Git Data<br/>Available?}
    B -->|Yes| C[Serve Immediately]
    B -->|No| D[Enter Purgatory]

    D --> E[Enqueue for Sync]
    E --> F{Event Source?}
    F -->|User Submit| G[3min Delay<br/>expect push]
    F -->|Relay Sync| H[500ms Delay<br/>batch burst]

    G --> I[Main Sync Loop<br/>1s interval]
    H --> I

    I --> J{Ready?}
    J -->|Not Yet| I
    J -->|Yes| K[Spawn Sync Task]

    K --> L[Try Non-Throttled URLs]
    L --> M{Got All OIDs?}
    M -->|Yes| N[Process & Release]
    M -->|Partial| O[Enqueue Throttled Domains]
    M -->|None| P[Apply Backoff]

    O --> Q[Domain Queue]
    Q --> R{Has Capacity?}
    R -->|No| Q
    R -->|Yes| S[Try Domain URL]
    S --> T{Got OIDs?}
    T -->|Yes| N
    T -->|No| U[Try Next in Queue]

    P --> I
    N --> V[Event Served]

    style D fill:#fff3cd
    style N fill:#d4edda
    style V fill:#d1ecf1

Retry Strategy: Exponential Backoff with Fresh Start

Backoff Schedule

When sync attempts don't complete (OIDs still needed), backoff increases:

Attempt Delay Formula
1 20s 20s * 2^0
2 40s 20s * 2^1
3 80s 20s * 2^2
4+ 120s (capped) min(20s * 2^n, 120s)

Implementation: src/purgatory/sync/queue.rs:SyncQueueEntry::backoff()

Fresh Start on New Events

Critical feature: When a new event arrives for an identifier already in the sync queue, the attempt_count resets to 0.

Why? New events often mean:

  • A maintainer just updated the repository
  • Fresh git data might be available at new clone URLs
  • Previous failures might have been temporary

Example:

t=0s:   State A arrives → queue with 3min delay, attempt_count=0
t=180s: First sync attempt fails → backoff 20s, attempt_count=1
t=200s: Second attempt fails → backoff 40s, attempt_count=2
t=210s: State B arrives (same identifier) → attempt_count=0 ✨
t=210s: Immediate retry (new event delay) → success!

Debounced Delays: Smart Timing

User-Submitted Events: 3 Minutes

When a user submits an event via EVENT message, we expect a git push to follow shortly:

t=0s:   User submits state event → purgatory + 3min delay
t=30s:  User runs `git push` → data arrives → event released ✅

Why 3 minutes? Gives users time to:

  • Finish composing their commit message
  • Run git push command
  • Handle network delays

Configuration: Hardcoded in src/purgatory/mod.rs:DEFAULT_SYNC_DELAY

Sync-Triggered Events: 500ms

When events arrive during relay sync (e.g., negentropy catchup), they often come in bursts:

t=0s:    State A arrives → purgatory + 500ms delay
t=0.1s:  State B arrives → purgatory + 500ms delay (same repo)
t=0.2s:  State C arrives → purgatory + 500ms delay (same repo)
t=0.5s:  Single sync attempt fetches data for all three ✅

Why 500ms? Batches burst arrivals without excessive delay.

Configuration: Hardcoded in src/purgatory/mod.rs:IMMEDIATE_SYNC_DELAY

Debouncing Mechanism

Multiple events for the same identifier don't create multiple sync tasks. The enqueue_sync method:

  1. If identifier not in queue → create new entry with delay
  2. If identifier already queued → reset attempt_count, update next_attempt if sooner

Result: Rapid event arrivals → single sync attempt after debounce window.

Implementation: src/purgatory/mod.rs:Purgatory::enqueue_sync()


Domain Throttling: Respectful Rate Limiting

Why Throttle?

Git servers have finite resources. Without throttling:

  • ❌ We could overwhelm small servers with concurrent requests
  • ❌ Servers might rate-limit or ban us
  • ❌ Other clients sharing the server suffer degraded performance

With throttling:

  • ✅ Respect server capacity (5 concurrent max per domain)
  • ✅ Stay under rate limits (30 requests/min per domain)
  • ✅ Fair access for all clients

Two-Level Limits

Each domain has two independent limits:

1. Concurrent Request Limit (Default: 5)

Maximum in-flight requests to a domain at any moment.

Example:

Domain: github.com
In-flight: [fetch-1, fetch-2, fetch-3, fetch-4, fetch-5]
Status: AT CAPACITY (throttled)

fetch-3 completes → in-flight: 4
Status: HAS CAPACITY (process next queued identifier)

2. Rate Limit (Default: 30/min)

Maximum requests in any 60-second sliding window.

Example:

t=0s:   Request 1 → request_times: [0s]
t=1s:   Request 2 → request_times: [0s, 1s]
...
t=30s:  Request 30 → request_times: [0s, 1s, ..., 30s]
t=31s:  Request 31? → THROTTLED (30 requests in last 60s)
t=61s:  Request at t=0s aged out → request_times: [1s, ..., 30s]
t=61s:  Request 31 → ALLOWED (only 29 in last 60s)

Implementation: src/purgatory/sync/throttle.rs:DomainThrottle::has_capacity()

Round-Robin Fairness

When multiple identifiers are queued for a throttled domain, we use round-robin to ensure fairness:

Queue: [repo-A, repo-B, repo-C]
Round-robin index: 0

Attempt 1: Try repo-A (index=0) → fetch → index=1
Attempt 2: Try repo-B (index=1) → fetch → index=2
Attempt 3: Try repo-C (index=2) → fetch → index=0
Attempt 4: Try repo-A (index=0) → ...

Why round-robin? Prevents head-of-line blocking. Without it, repo-A might consume all slots while repo-B and repo-C wait indefinitely.

Implementation: src/purgatory/sync/throttle.rs:DomainThrottle::next_ready_identifier()

Trigger-Based Processing (Not Polling)

Domain queues don't poll for capacity. Instead, processing is triggered by two events:

  1. complete_request() - A request finishes, slot frees
  2. enqueue_identifier() - New identifier added to queue

Both methods check has_capacity() and trigger try_process_next() if true.

Why trigger-based?

  • ✅ Lower CPU usage (no busy-waiting)
  • ✅ Instant response when capacity frees
  • ✅ Simpler reasoning (event-driven)

Implementation: src/purgatory/sync/throttle.rs:ThrottleManager


30-Minute Purgatory Expiry

Purgatory entries automatically expire after 30 minutes to prevent unbounded memory growth.

Why 30 Minutes?

From the GRASP-01 spec:

Events should be kept in purgatory and otherwise discarded after 30 minutes.

This balances:

  • ⏰ Long enough for typical sync scenarios (git data usually arrives within minutes)
  • 🧹 Short enough to prevent memory leaks from abandoned events
  • 🔄 Recoverable events are still on other relays and can be re-submitted

Implementation

Each purgatory entry tracks:

  • created_at: Instant - When added to purgatory
  • expires_at: Instant - When to discard (created_at + 30min)

The main sync loop checks expiry before processing:

if !self.has_pending_events(&identifier) {
    // No events remain (expired or released) → remove from sync queue
    self.sync_queue.remove(&identifier);
}

Note: Expiry is checked implicitly via has_pending_events(). If all events for an identifier have expired, the identifier is removed from the sync queue.

Implementation: src/purgatory/mod.rs:DEFAULT_EXPIRY


Testability: Mock-Based Architecture

A key design goal was 100% unit test coverage without requiring real git servers or databases.

SyncContext Trait

All external dependencies are abstracted behind the SyncContext trait:

#[async_trait]
pub trait SyncContext: Send + Sync {
    async fn fetch_repository_data(&self, identifier: &str) -> Result<RepositoryData>;
    fn collect_needed_oids(&self, identifier: &str) -> HashSet<String>;
    async fn oid_exists(&self, repo_path: &Path, oid: &str) -> bool;
    async fn fetch_oids(&self, repo_path: &Path, url: &str, oids: &[String]) -> Result<Vec<String>>;
    async fn process_newly_available_git_data(&self, ...) -> Result<ProcessResult>;
    fn has_pending_events(&self, identifier: &str) -> bool;
    fn find_target_repo(&self, data: &RepositoryData) -> Option<PathBuf>;
    fn our_domain(&self) -> Option<&str>;
}

Two Implementations:

  1. RealSyncContext - Production implementation connecting to real systems
  2. MockSyncContext - Test implementation with configurable behavior

MockSyncContext Features

The mock supports builder-pattern configuration:

let mock = MockSyncContext::new()
    .with_repository_data("test-repo", RepositoryData {
        announcements: vec![...],
        clone_urls: vec!["https://server1.com/repo.git".to_string()],
    })
    .with_needed_oids("test-repo", hashset!["abc123", "def456"])
    .with_fetch_result("https://server1.com/repo.git", Ok(vec!["abc123"]))
    .with_fetch_result("https://server2.com/repo.git", Ok(vec!["def456"]));

Test Example (from src/purgatory/sync/functions.rs):

#[tokio::test]
async fn test_sync_identifier_partial_success() {
    let mock = MockSyncContext::new()
        .with_repository_data("repo", RepositoryData {
            clone_urls: vec![
                "https://server1.com/repo.git".to_string(),
                "https://server2.com/repo.git".to_string(),
            ],
            ..Default::default()
        })
        .with_needed_oids("repo", hashset!["oid1", "oid2"])
        .with_fetch_result("https://server1.com/repo.git", Ok(vec!["oid1"]))
        .with_fetch_result("https://server2.com/repo.git", Ok(vec!["oid2"]));

    let throttle = Arc::new(ThrottleManager::new(5, 30));
    let complete = sync_identifier(&mock, "repo", &throttle).await;

    assert!(complete); // Both OIDs fetched
}

Why this matters:

  • ✅ Tests run instantly (no network I/O)
  • ✅ Tests are deterministic (no flaky failures)
  • ✅ Tests cover edge cases easily (network errors, partial success, etc.)
  • ✅ Tests are isolated (no shared state between tests)

Implementation: src/purgatory/sync/context.rs:MockSyncContext


Configuration

Purgatory sync behavior is configurable via CLI flags or environment variables:

Setting CLI Flag Environment Variable Default Description
Domain concurrent limit (future) (future) 5 Max concurrent requests per domain
Domain rate limit (future) (future) 30 Max requests per minute per domain
Sync loop interval N/A N/A 1s How often to check for ready identifiers (hardcoded)
Default sync delay N/A N/A 180s Delay for user-submitted events (hardcoded)
Immediate sync delay N/A N/A 500ms Delay for sync-triggered events (hardcoded)
Purgatory expiry N/A N/A 30min How long events wait before expiring (hardcoded)

Note: Currently, throttle limits and delays are hardcoded constants. Future work may expose these as configuration options if needed.


Key Design Decisions

1. Identifier-Based, Not Event-Based

Decision: Sync by repository identifier, not individual events.

Rationale: Multiple events for the same repository should trigger a single fetch operation, not N separate fetches.

Impact: Batches events efficiently, reduces server load.

2. Two Separate tried_urls Tracking

Decision: Main sync loop and domain queues track tried URLs independently.

Main sync: Local HashSet<String> for current attempt (all domains)
Domain queue: Per-identifier HashSet<String> for this domain only

Rationale:

  • Main sync skips throttled domains entirely (doesn't need their tried URLs)
  • Domain queue only cares about URLs from its own domain
  • No coordination needed → simpler code

Impact: Clean separation of concerns, easier to reason about.

3. Trigger-Based Domain Processing

Decision: Domain queues process on triggers (capacity freed, new enqueue), not polling.

Rationale:

  • Polling wastes CPU cycles checking capacity every interval
  • Triggers provide instant response when capacity frees
  • Event-driven design is easier to test and debug

Impact: Lower CPU usage, faster response times.

4. Fresh Start on New Events

Decision: Reset attempt_count to 0 when new events arrive for an identifier.

Rationale:

  • New events often mean fresh git data is available
  • Previous failures might have been temporary
  • Gives repositories a "second chance" without waiting for full backoff

Impact: Faster recovery from transient failures, better UX.

5. OID Copying in process_newly_available_git_data

Decision: Copy OIDs and release events per successful fetch, not at end of sync.

Rationale:

  • Events can be released as soon as their specific OIDs are available
  • Partial success scenarios work correctly (some events release, others stay)
  • Handles multiple state events for same identifier independently

Impact: Events release faster, better handling of partial success.


Observability

Logging

Sync operations produce structured logs at different levels:

INFO: Major events

Starting purgatory sync loop (interval: 1s)
Sync complete - removed from sync queue (identifier=test-repo, complete=true)

DEBUG: Detailed progress

Added new sync queue entry (identifier=test-repo, delay_secs=180)
Starting sync task for identifier (identifier=test-repo)
Sync incomplete - applying backoff (identifier=test-repo, attempt_count=2, next_backoff_secs=40)

WARN: Errors and failures

Failed to fetch OIDs (url=https://server.com/repo.git, error=connection timeout)

Metrics (Future)

Planned Prometheus metrics for observability:

  • purgatory_sync_queue_size - Number of identifiers pending sync
  • purgatory_sync_attempts_total{identifier} - Total sync attempts per identifier
  • purgatory_sync_oids_fetched_total{identifier} - OIDs successfully fetched
  • purgatory_domain_in_flight{domain} - Current in-flight requests per domain
  • purgatory_domain_requests_total{domain} - Total requests per domain

Testing Strategy

Unit Tests

Core sync functions have comprehensive unit tests using MockSyncContext:

sync_identifier_next_url (3 tests):

  • Skips throttled domains
  • Skips tried URLs
  • Returns None when all URLs exhausted

sync_identifier_from_url (2 tests):

  • Successful fetch triggers processing
  • Failed fetch doesn't trigger processing

sync_identifier (3 tests):

  • Tries multiple URLs until complete
  • Enqueues throttled domains when incomplete
  • Handles partial success correctly

SyncQueueEntry (3 tests):

  • Backoff calculation correct
  • Fresh start on new events
  • Ready state logic correct

DomainThrottle (4 tests):

  • Concurrent limit enforced
  • Rate limit enforced
  • Round-robin fairness
  • Queue management correct

Total: 15+ unit tests covering all core logic

Location: src/purgatory/sync/ (various #[cfg(test)] modules)

Integration Tests

End-to-end tests verify sync behavior with real relay instances:

Planned tests:

  • State event syncs from remote server
  • PR event syncs from remote server
  • Partial OID aggregation across multiple servers
  • Throttling prevents overwhelming servers
  • Backoff retry after failures

Location: tests/purgatory_sync.rs (planned)


Future Enhancements

1. Configurable Throttle Limits

Current: Hardcoded to 5 concurrent, 30/min per domain
Future: CLI flags --sync-domain-concurrent and --sync-domain-rate-limit

Use case: Operators might want stricter limits for public servers or looser limits for trusted servers.

2. Per-Domain Throttle Configuration

Current: Same limits for all domains
Future: Domain-specific overrides (e.g., github.com:10,60 for higher limits)

Use case: Popular forges like GitHub/GitLab can handle more load than small personal servers.

3. Prometheus Metrics

Current: Structured logging only
Future: Export metrics for monitoring dashboards

Use case: Operators want visibility into sync performance, throttle effectiveness, success rates.

4. Negentropy Integration

Current: Sync triggered by event arrival
Future: Proactive sync discovers missing events via negentropy

Use case: Catch up with repositories after downtime without waiting for event re-submission.



Summary

The purgatory sync system is a sophisticated, production-ready implementation that:

✅ Batches intelligently - Groups events by identifier for efficient fetching
✅ Retries smartly - Exponential backoff with fresh start on new events
✅ Throttles respectfully - 5 concurrent + 30/min per domain, round-robin fairness
✅ Times strategically - 3min for user events, 500ms for synced events
✅ Expires responsibly - 30min auto-cleanup prevents memory leaks
✅ Tests thoroughly - Mock-based architecture enables comprehensive unit tests

This design ensures ngit-grasp can serve repositories reliably even when git data and Nostr events arrive out-of-order or from different sources, while respecting remote server capacity and providing excellent observability.