Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Multi-Site Content Deployment, GA4 Integration, and Daemon Health Monitoring

This session involved three parallel workstreams: deploying SEO content to a newly restructured domain, implementing Google Analytics 4 credential reuse across projects, and diagnosing a production daemon's health and token expiration issues. Here's what was accomplished and why.

Domain Restructuring and Site Deployment

The first task was renaming and deploying content for a restaurant/hospitality domain. The directory /Users/cb/Documents/repos/sites/86dfrom.com/ was renamed to /Users/cb/Documents/repos/sites/86from.com/ to correct a naming inconsistency. This was followed by:

  • Content migration: Moved the existing index.html and created a new SEO-focused page at /Users/cb/Documents/repos/sites/86from.com/site/what-does-86d-mean to capture search traffic for industry terminology.
  • S3 deployment: Published both files to the production S3 bucket backing the 86from.com domain, then invalidated the CloudFront distribution cache to serve fresh content immediately.
  • DNS verification: Confirmed via WHOIS and HTTP headers that 86from.com properly resolves, redirects correctly, and presents a valid TLS certificate.

Why this approach: Renaming the local directory before deployment ensures git history and local CI/CD references remain consistent. Deploying to S3 + CloudFront (rather than a traditional web server) provides automatic scaling, geographic distribution, and built-in caching control without managing server infrastructure.

GA4 Multi-Account Credential Reuse

Rather than generating new Google OAuth credentials for each new analytics integration, the session established a pattern of credential reuse through a shared authentication layer:

  • Existing token leverage: The dangerouscentaur@gmail.com Google account already had valid GA4 API credentials stored in /Users/cb/Documents/repos/tools/auth_ga.py. Instead of generating new client_id/client_secret pairs, the session confirmed both existed in the token store and verified their scope covered the Google Analytics Data API v1.
  • Multi-property queries: Used the reused credentials to query multiple GA4 properties under that account (e.g., 86dfrom.com, queenofsandiego.com). Pulled 7-day reports showing traffic, conversion, and user acquisition metrics.
  • Credential permissions: Locked down the secrets file with restricted file permissions to ensure only the daemon user can read stored tokens.

Why this matters: GA4's OAuth flow requires user interaction to grant consent. Rather than repeat that flow for each new property or script, centralizing credentials in a shared token store (with proper access controls) reduces friction and security surface area. The google-auth-oauthlib library handles token refresh automatically, so credentials remain fresh without manual intervention.

Production Daemon Health and Error Diagnosis

A health check was performed on the jada-agent orchestrator daemon running at 34.239.233.28 (AWS Lightsail instance). The investigation revealed:

Healthy Baseline

  • jada-agent.service is active and has been running for 3 days without restart.
  • Instance CPU: ~0.65% average (normal for the 60-second poll loop); no spikes detected.
  • Memory: 144MB of 914MB used; healthy margin.
  • Disk: 6.2GB of 39GB (17%); no capacity concerns.
  • Network and system status checks: 0 failures in the last 2 hours.

Session Activity Pattern

The daemon manages concurrent agent sessions, with a hard limit of 5 per day. On May 13:

  • Session 1 (00:00 UTC): Hit the 30-turn Claude limit and exited with code 1. Not a crash; the daemon correctly logged this as a limitation.
  • Session 2 (00:02 UTC): Completed successfully. Processed blockers on e-signature and crew page generation, created a needs-you task for manual review.
  • Session 3 (00:05 UTC): Also hit the 30-turn limit and exited with code 1.
  • After session 3, the task queue was empty; daemon returned to normal idle polling.

Why the exits matter: The 30-turn limit is a safety guardrail to prevent runaway API costs and ensure human oversight of agent decisions. When tasks are complex, they consume all 30 turns before completing. This is not a failure, but it does mean incomplete work gets queued for the next session or manual followup. The daemon handles this gracefully, logs the exit code, and continues running.

Critical Issue: Expired OAuth Token for Port Sheet Sync

A recurring failure was identified in the port_sheet_sync.py script (runs every 30 minutes):

[port-sheet] token error: HTTP Error 400: Bad Request

The Google OAuth token used by this script has expired or been revoked. Port sheet syncs have not executed since at least the afternoon of May 13. Action required: Re-authenticate the token for port_sheet_sync.py using the same pattern as the GA4 credential refresh—either manually trigger the OAuth flow or rotate the credential in the secrets store.

Infrastructure and Access Patterns

The session demonstrated several infrastructure patterns worth noting:

  • SSH via Lightsail API: The jada-key private key was not stored locally. Instead of searching for it, the session used AWS Systems Manager Session Manager and the Lightsail API to generate temporary SSH credentials on demand. This reduces the attack surface of long-lived SSH keys while maintaining secure access.
  • Daemon orchestration: The jada-agent runs as a systemd service, polling a task queue at regular intervals. Sessions are rate-limited (5 per day) and turn-limited (30 per session) to balance productivity with cost and safety.
  • Multi-site repository layout: Sites are stored as subdirectories under /Users/cb/Documents/repos/sites/, each with its own static assets, scripts, and configuration. This allows independent deployment pipelines (S3 + CloudFront per domain) while sharing build and auth tooling.

Key Decisions and Rationale

  • Credential reuse over generation: Reusing existing GA4 credentials reduces OAuth friction and eliminates duplicate credential management.
  • Temporary SSH keys over stored keys: Using the Lightsail API to generate temporary credentials for one-off access reduces the number of long-lived secrets on disk.
  • S3 + CloudFront for static sites: No servers to patch or maintain; automatic geo-distribution and edge caching; simple CloudFront invalidation for instant cache refresh.
  • Session/turn limits on the daemon: Caps cost and ensures human review of complex decisions; graceful degradation when limits are hit.

What's Next

  • Port sheet sync: Regenerate or refresh the Google OAuth token for port_sheet_sync.py to restore the 30-minute sync cycle.