Sync Status Rapid

Instant synchronization status dashboard showing pipeline health, queue depth, error rates, and recent activity across all configured sync integrations.

When to Use This Command

Run this command when...

• You need a rapid overview of all active sync pipelines and their current operational state before starting your workday
• A sync failure was reported and you want to quickly identify which pipeline, stage, or integration is the source of the problem
• You want to verify that a recently deployed sync configuration change is working correctly

Avoid this command when...

• You need to actively fix sync issues (use this command to diagnose, then use the appropriate resolver command to fix)
• You want detailed historical analytics rather than a current-state snapshot (export sync logs to your analytics platform instead)

Quick Start

Copy
# .sync-config.json
{
  "integrations": [
    { "name": "github-linear", "type": "issue-sync" },
    { "name": "db-replica", "type": "data-sync" },
    { "name": "file-backup", "type": "file-sync" }
  ]
}

Copy
claude -p "Show me the current sync status for all integrations"

Expected output:
=== Sync Status Dashboard ===
Integration         Status    Last Run       Queue  Errors(24h)
github-linear       HEALTHY   8 min ago      0      0
db-replica          WARNING   2 hr ago       47     3
file-backup         HEALTHY   22 min ago     0      0

Recent Activity (last 1h):
  14:32 github-linear: synced 12 issues (0 conflicts)
  14:18 file-backup: uploaded 3 files (2.4 MB)
  13:45 db-replica: WARNING - 3 timeout errors on users table

Overall: 2 HEALTHY, 1 WARNING, 0 CRITICAL

Core Concepts

Concept	Description
Integration Status	Aggregate health state (HEALTHY, WARNING, CRITICAL) derived from error rate and queue depth
Queue Depth	Number of pending sync operations waiting to be processed for each integration
Error Window	Rolling time window (default 24h) over which errors are counted for status determination
Last Run Timestamp	When each integration last completed a sync cycle, revealing stale integrations
Activity Feed	Chronological log of recent sync events across all integrations

+----------------------------------------------------+
|              Sync Status Dashboard                  |
+----------------------------------------------------+
| Integration    | Status  | Queue | Errors | Last   |
|----------------|---------|-------|--------|--------|
| github-linear  | OK      |   0   |   0    | 8m ago |
| db-replica     | WARN    |  47   |   3    | 2h ago |
| file-backup    | OK      |   0   |   0    | 22m    |
+----------------------------------------------------+
| Recent: 14:32 github-linear synced 12 issues       |
|         14:18 file-backup uploaded 3 files          |
|         13:45 db-replica 3 timeout errors           |
+----------------------------------------------------+

Configuration

Parameter	Type	Default	Description	Example
integrations	array	auto-detect	List of sync integrations to monitor	See Quick Start
error_window	string	24h	Rolling window for error counting	12h
warn_threshold	number	3	Error count that triggers WARNING status	5
critical_threshold	number	10	Error count that triggers CRITICAL status	15
activity_limit	number	10	Max recent activity entries to display	25

Best Practices

1. Check status first thing each morning -- A quick status scan catches overnight failures before they compound into larger data consistency problems.
2. Set thresholds relative to sync frequency -- High-frequency syncs (every minute) tolerate more errors than daily syncs before WARNING is appropriate.
3. Investigate WARNING status immediately -- WARNING is the early signal. Addressing it promptly prevents escalation to CRITICAL and data loss.
4. Pipe output to team channels -- Schedule sync-status-rapid to post to Slack or Teams so the entire team has visibility without running the command manually.
5. Correlate queue depth with processing rate -- A queue depth of 47 is fine if processing rate is 100/minute, but alarming if the rate is 2/minute. Always consider both metrics together.

Common Issues

1. All integrations show HEALTHY but data is stale -- The health check may only verify connectivity, not data freshness. Check Last Run timestamps and add a stale_after threshold to flag integrations that have not synced recently.
2. Error counts reset unexpectedly -- The error window is rolling; errors older than the window duration drop off. If you need persistent error tracking, export error events to a separate logging system.
3. Auto-detect misses a configured integration -- Auto-detection scans for known config file patterns. If your integration uses a custom config path, explicitly list it in the integrations array.