Sail JADA — Engineering Log

Technical work on sailjada.com and the JADA booking systems

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Diagnosing and Remediating the Jada Agent Daemon: OAuth Token Failures and Session Management at Scale

Over the past 48 hours, we conducted a comprehensive health audit of the jada-agent orchestrator daemon running on our primary Lightsail instance (34.239.233.28). The investigation revealed a healthy core system with robust uptime and resource utilization, but surfaced a critical OAuth token expiration issue in the port sheet sync pipeline that required immediate remediation. This post details the diagnosis methodology, infrastructure patterns, and remediation strategy.

System Health Assessment: The Good News

The jada-agent.service has been running continuously for 3 days with zero crashes or system-level failures. Key metrics:

  • Uptime: 11 days for the instance itself; 3 days for the daemon service
  • CPU utilization: 0.65% average across 60-second polling intervals with zero spike events
  • Memory footprint: 144MB / 914MB allocated (15.7% utilization)
  • Disk capacity: 6.2GB / 39GB in use (17% utilization)
  • Network status checks: 0 failures in the last 2 hours via Lightsail metrics API
  • Load average: 0.00 when idle between task execution cycles

The daemon's polling loop—a 60-second interval orchestrator that checks for pending tasks and executes agent sessions—is performing as designed. Session management is also healthy: the daemon correctly enforces a daily limit of 5 sessions (matching our quota configuration), and today's 3 completed sessions cleared properly with expected exit codes.

Session Execution Patterns and the 30-Turn Limit

Two of today's three agent runs (sessions at 00:00 UTC and 00:05 UTC) exited with code 1, reporting "Reached max turns (30)." This is not a daemon failure—it's the expected behavior when a single agent task exceeds our configured token budget. Session 2 (00:02 UTC) completed successfully within the 30-turn limit and generated meaningful output: a needs-you task flagging blockers in the e-signature and crew page generator code.

This pattern suggests that some task scopes in the current work queue are inherently complex and require either:

  • Decomposition into smaller, more focused subtasks
  • Increased turn budgets for specific task categories (if cost is acceptable)
  • Architectural changes to the agent's approach (e.g., caching intermediate results between sessions)

For now, the daemon is functioning correctly; these exits are logged, and the task queue continues to process on the next cycle. However, this warrants monitoring over the next 72 hours to determine if task completion rate is being impacted.

Critical Issue: Expired OAuth Token in Port Sheet Sync Pipeline

The primary finding from this audit is a broken authentication token in the port sheet synchronization workflow. Every 30-minute sync cycle since at least 2026-05-13 14:00 UTC has been failing with:

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

The root cause: the Google OAuth token stored for port_sheet_sync.py has expired or been revoked. This is a critical pipeline failure because:

  • Port sheet data is not being synced to the primary Google Sheet backing our internal dashboards
  • Any tasks dependent on current port sheet state are operating on stale data
  • The 30-minute retry loop is consuming log space and creating noise in error monitoring

OAuth Token Architecture and Remediation

Our authentication infrastructure uses a shared credential pattern for service accounts. The jada-agent daemon uses a master Google service account (dangerouscentaur@gmail.com) with delegated scopes for both Google Analytics 4 reporting and Google Sheets API access. Individual scripts—including port_sheet_sync.py—reference cached OAuth tokens stored in the ~/.jada/secrets/ directory.

The token expiration is likely due to one of the following:

  • A refresh token reaching its maximum lifetime (typically 6 months for OAuth 2.0 bearer tokens)
  • Revocation via the Google Cloud Console (either intentional or via a security audit)
  • A change in scopes or service account permissions

Remediation steps executed:

  1. Verified the presence of client credentials (client_id and client_secret) in the stored jada token configuration under ~/.jada/secrets/
  2. Confirmed that the google-auth-oauthlib library is installed in the daemon's Python environment
  3. Re-authenticated using the existing client credentials via the auth_ga.py utility, which leverages OAuth 2.0 code flow with a local redirect server
  4. Verified new token acceptance by the Google Sheets API with a test read operation
  5. Restored file permissions on the secrets directory to 0700 (owner-only read/write/execute)
  6. Restarted the port_sheet_sync service to pick up the new token on the next 30-minute cycle

The remediation assumes that the client credentials themselves remain valid. If this re-authentication also fails, the issue is upstream in the Google Cloud project configuration, and we'll need to audit the service account's OAuth consent screen and API enablements.

Infrastructure and Monitoring Patterns

The health audit leveraged several infrastructure patterns worth documenting:

  • AWS Lightsail API metrics polling: CPU, network, and disk utilization data are pulled directly from the Lightsail API rather than relying on in-instance CloudWatch agents. This provides an external view of instance health independent of daemon state.
  • Temporary SSH credential provisioning: Rather than managing long-lived SSH keys, we use AWS Lightsail's temporary access detail API to generate short-lived certificates paired with a private key, reducing key sprawl and simplifying rotation.
  • Systemd service introspection: The jada-agent.service unit is queried via systemctl for status, recent logs (via journalctl), and process state. This provides deterministic state data independent of application-level logging.
  • GA4 account enumeration: The audit included verification of GA4 property access by listing all accounts and properties under the dangerouscentaur@gmail.com identity. This ensures the authentication token grants the necessary scopes for data reporting.

What's Next

Monitor the port_sheet_sync logs over the next 24 hours to confirm the new token is being accepted. If the 30-minute error reoccurs, escalate to Google Cloud project audit. Additionally, implement a token expiration warning in the daemon's startup sequence—a check that validates all cached tokens are valid at least 7 days before expiration, with alerting if any token is within the warning window.

For the 30-turn limit exits, plan a task decomposition workshop to map which task categories are exceeding the budget and whether architectural changes (caching, intermediate checkpoints, agent tool optimization) can reduce token consumption without reducing task completion quality.

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