Production is running with no Kratos deployed in-cluster (the deploy
script's kratos-secrets prerequisite isn't satisfied yet — see runbook
§11 #7). That means Whoami calls ALWAYS fail, so any time a user's Redis
session cache expires they get a 401, which the iOS app treats as session
invalid → forced re-login → can't re-authenticate because the same
Whoami is the only way back in.
Two-part mitigation:
1. Bump kratosSessionCacheTTL from 5 minutes to 24 hours. Active users
stay logged in indefinitely; idle users get bounced after a day.
2. Refresh the cache TTL on every successful cache hit (sliding window)
so usage-driven expiry is no longer a cliff at the original TTL.
When Kratos actually comes up:
- revert the TTL constant to a sensible value (1-15 min)
- the sliding-window refresh is fine to keep; it's good UX regardless
Caveat: this papers over the missing Kratos. New sign-ins still cannot
complete because the api needs Kratos to populate the cache the first
time. Real fix is to deploy Kratos.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Delegates all credential management (login, register, password reset,
email verification, social sign-in) to Ory Kratos. The Go API now acts
as a resource server: the new KratosAuth middleware validates sessions
against the Kratos whoami endpoint, writes the local User mirror into
Echo context, and all existing domain handlers continue working
unchanged. Hand-rolled token auth, AuthToken model, apple_auth/
google_auth services, and the auth refresh flow are removed. Tests are
updated to use the fake-token middleware pattern so existing integration
assertions require no rewrite.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Stack of optimizations against the same Hetzner→Neon transatlantic link.
The trace revealed every visible ms was network/proxy overhead — DB
execution itself is sub-millisecond per query (verified via EXPLAIN
ANALYZE: index scans on every hot path).
Connection layer:
- DB_HOST → Neon pooler endpoint (-pooler suffix). PgBouncer
transaction-mode keeps backend Postgres connections warm so we no
longer pay the ~110ms Postgres-startup RTT on cold queries.
- GORM pool tuned: MaxIdleConns 10→20, MaxLifetime 600s→1800s,
MaxIdleTime added (default 0 = never close idle).
- Eager pool warm-up at boot via parallel pings — first user request
no longer pays the ~440ms TCP+TLS+startup handshake.
- Redis maxmemory-policy noeviction → allkeys-lru. Cache writes will
evict cold keys instead of erroring at the 256MB limit.
Auth layer:
- TokenCacheTTL 5min → 1 hour (Redis token cache).
- UserCacheTTL 30s → 5min (in-memory User cache, per pod).
- UserCache gains a 5,000-entry LRU cap so a flood of unique users
can't blow up pod RSS. ~5MB worst-case per pod.
- Token + user lookup collapsed from 2 GORM Preload queries into a
single INNER JOIN. Saves 1 RTT per cold-cache request.
- Auth middleware's m.db.* now use db.WithContext(ctx) so the SQL
spans nest under the parent HTTP request in Jaeger.
Service layer:
- TaskService.ListTasks: replaced two-step
FindResidenceIDsByUser → GetKanbanDataForMultipleResidences
with a single GetKanbanDataForUser that uses a Postgres subquery
for residence-access. One round-trip instead of two.
- New CacheService residence-IDs cache: \"residence_ids_user:<id>\"
with 5-min TTL. Wired into Task/Residence/Contractor/Document
services for the four hot read paths that need this list.
- Cache invalidation on every relevant mutation: CreateResidence,
DeleteResidence, JoinWithCode, RemoveUser. DeleteResidence
invalidates every member of the residence, not just the owner.
What this stacks up to (Hetzner→Neon, before US migration):
Path Before After (target)
Cache-warm authed read ~800ms ~100-200ms
Cache-cold authed read (1st in 1hr) ~2500ms ~500-700ms
First request after deploy ~2500ms ~700-900ms
The endgame US-region migration on top of this gets us to ~30-50ms
warm-cache, but we're shippable at ~150ms warm right now.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The auth middleware's m.db.Preload + m.db.First calls were running without
ctx, so on cache miss the resulting SQL queries appeared as orphan
gorm.Query / gorm.Row spans in Jaeger. Now they nest under the parent
HTTP request span like every other repo call.
This was the last orphaned-SQL source on the request hot path. Combined
with the seven service migrations, every authenticated API call now
produces a fully-nested flame graph: HTTP → auth-token-lookup (cache hit)
or HTTP → auth-token-SQL (cache miss) → service → service-SQL.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Custom rate limiter replacing Echo built-in, with per-IP token bucket.
Every response includes X-RateLimit-Limit, Remaining, Reset headers.
429 responses additionally include Retry-After (seconds).
CORS updated to expose rate limit headers to mobile clients.
4 unit tests for header behavior and per-IP isolation.
Fix issue where tasks showed as "Overdue" on the server while displaying
"Tomorrow" on the client due to timezone differences between server (UTC)
and user's local timezone.
Changes:
- Add X-Timezone header support to extract user's timezone from requests
- Add TimezoneMiddleware to parse timezone and calculate user's local "today"
- Update task categorization to accept custom time for accurate date comparisons
- Update repository, service, and handler layers to pass timezone-aware time
- Update CORS to allow X-Timezone header
The client now sends the user's IANA timezone (e.g., "America/Los_Angeles")
and the server uses it to determine if a task is overdue based on the
user's local date, not UTC.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements a comprehensive monitoring system for the admin interface:
Backend:
- New monitoring package with Redis ring buffer for log storage
- Zerolog MultiWriter to capture logs to Redis
- System stats collection (CPU, memory, disk, goroutines, GC)
- HTTP metrics middleware (request counts, latency, error rates)
- Asynq queue stats for worker process
- WebSocket endpoint for real-time log streaming
- Admin auth middleware now accepts token in query params (for WebSocket)
Frontend:
- New monitoring page with tabs (Overview, Logs, API Stats, Worker Stats)
- Real-time log viewer with level filtering and search
- System stats cards showing CPU, memory, goroutines, uptime
- HTTP endpoint statistics table
- Asynq queue depth visualization
- Enable/disable monitoring toggle in settings
Memory safeguards:
- Max 200 unique endpoints tracked
- Hourly stats reset to prevent unbounded growth
- Max 1000 log entries in ring buffer
- Max 1000 latency samples for P95 calculation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Features:
- PDF service for generating task reports with ReportLab-style formatting
- Storage service for file uploads (local and S3-compatible)
- Admin authentication middleware with JWT support
- Admin user model and repository
Infrastructure:
- Updated Docker configuration for admin panel builds
- Email service enhancements for task notifications
- Updated router with admin and file upload routes
- Environment configuration updates
Tests:
- Unit tests for handlers (auth, residence, task)
- Unit tests for models (user, residence, task)
- Unit tests for repositories (user, residence, task)
- Unit tests for services (residence, task)
- Integration test setup
- Test utilities for mocking database and services
Database:
- Admin user seed data
- Updated test data seeds
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Complete rewrite of Django REST API to Go with:
- Gin web framework for HTTP routing
- GORM for database operations
- GoAdmin for admin panel
- Gorush integration for push notifications
- Redis for caching and job queues
Features implemented:
- User authentication (login, register, logout, password reset)
- Residence management (CRUD, sharing, share codes)
- Task management (CRUD, kanban board, completions)
- Contractor management (CRUD, specialties)
- Document management (CRUD, warranties)
- Notifications (preferences, push notifications)
- Subscription management (tiers, limits)
Infrastructure:
- Docker Compose for local development
- Database migrations and seed data
- Admin panel for data management
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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