Shipping commit 88fb175 changed the trace shape and added a new caching
layer with required invalidation rules. Updating the operator-facing
docs so they match the running system.
ch08 (database):
- DB_HOST is the -pooler Neon endpoint, not direct compute
- Connection pool: MaxIdleConns 20 (was 10), MaxLifetime 30m (was 10m),
MaxIdleTime 0 (never close idle)
- New \"Pool warm-up at boot\" section documenting the 20-parallel-ping
warm-up in database.Connect
- Replaced the \"Neon regions\" section: explicit RTT numbers, the
optimization stack that minimizes round-trips, when this still matters
ch15 (observability):
- Replaced the 2,473ms/5-span sample trace with the new 229ms/2-span
post-optimization trace; kept the old one underneath for diff context
ch16 (failure modes):
- Added: stale residence-IDs cache (data freshness bug + recovery)
- Added: Redis at maxmemory limit (verify allkeys-lru policy)
- Added: Neon pooler unreachable but direct endpoint up — emergency
switchover procedure
ch17 (runbook):
- §23 Invalidate residence-IDs cache for a user (DEL key + grep for
missing invalidation in new code)
- §24 Verify DB pool warm-up is working (log pattern + impact test)
- §25 Switch DB host between pooler and direct endpoints
observability-plan.md status flipped from \"plan only\" to shipped
with the latency-cut summary.
README links to the new ch08 latency section.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
14 KiB
08 — Database (Neon Postgres)
Summary
Authoritative user data lives in a Neon-managed Postgres database in AWS
us-east-1. Connections use TLS (DB_SSLMODE=require). Schema is managed
via GORM AutoMigrate inside the api binary, coordinated across replicas
by a Postgres advisory lock to prevent concurrent migration attempts.
Why Neon
Decision matrix
At deploy time we considered:
| Option | Setup effort | Monthly cost | Backup/PITR | Scale ceiling | Notes |
|---|---|---|---|---|---|
| Neon Launch | Zero (managed) | $5-15 | Included | Large | Picked |
| Postgres on a Hetzner VPS | High | $8 (VPS) | Manual | Medium | More ops |
| AWS RDS | Medium | $30+ | Included | Huge | Overkill, expensive |
| Supabase Free | Zero | $0 | Limited | Small | Free tier has quota limits |
| CNPG on our k3s | High (Helm) | $0 (using cluster) | Self-rolled | Medium | Operational burden |
Neon Launch won on:
- Serverless: scales compute to zero when idle (cheap)
- Branch databases: we can create dev/staging branches from prod in seconds
- Connection pooling built-in: PgBouncer on the hostname suffix
-pooler - Point-in-time recovery included (paid tier)
- Pay-as-you-go with a $5 minimum — fits a bootstrapped app
Connection details
| Field | Value |
|---|---|
| Hostname | ep-floral-truth-amttbc5a-pooler.c-5.us-east-1.aws.neon.tech |
| Port | 5432 |
| Username | neondb_owner |
| Database | honeyDue (case-sensitive!) |
| TLS mode | require (enforced by Neon; app pg driver verifies) |
| Branch | production (Neon's concept — isolated DB within the project) |
The database name is case-sensitive
Postgres identifiers are lowercase unless quoted. Neon's UI created the
database as "honeyDue" (quoted, camelCase preserved). In prod.env /
ConfigMap we must use exactly POSTGRES_DB=honeyDue — lowercase
honeydue gets a database "honeydue" does not exist error. This bit
us during the initial Swarm deploy (Chapter 19 §Neon DB name).
Connection pooling
Why it matters
Postgres is memory-hungry per connection (~5-10 MB each). 3 api replicas
× DB_MAX_OPEN_CONNS=25 = up to 75 direct Postgres connections. Add
the worker's 25. Neon's free tier caps at 100 concurrent connections;
paid tiers much higher.
PgBouncer on Neon
Neon provides a built-in PgBouncer at the -pooler subdomain. The
non-pooler endpoint (ep-floral-truth-amttbc5a.c-5.us-east-1...) is
the direct compute endpoint and connects straight to Postgres,
paying the full TCP+TLS+startup handshake on every cold connection.
The -pooler endpoint multiplexes through PgBouncer in Neon's
infrastructure.
We use the -pooler endpoint because the direct endpoint paid
~440ms per cold handshake on a transatlantic link, visible as
1500ms-tail spikes in /api/tasks/ traces. The pooler keeps backend
Postgres connections warm in Neon's data center, so the only
latency our Go pods see is one TCP+TLS to PgBouncer (already
warm via our pool) plus one query round-trip.
Modes PgBouncer supports:
- session — one server connection held per client session (transparent)
- transaction — server connection released after each transaction (high-throughput)
- statement — per-statement (most aggressive; breaks many features)
Neon's pooler runs in transaction mode. This is compatible with GORM
out of the box (we don't use session-level features like LISTEN/NOTIFY
or session-scope advisory locks). Note: database.MigrateWithLock()
needs the direct (non-pooler) endpoint because session-level
advisory locks don't survive PgBouncer's per-transaction cycling — but
the migration helper opens its own ad-hoc connection bypassing the
configured pool, so this happens automatically. See MigrateWithLock
in internal/database/database.go.
Connection pool settings
In config.yaml (rendered into ConfigMap → env vars):
database:
max_open_conns: 25
max_idle_conns: 20
max_lifetime: "1800s"
max_idle_time: "0s"
These map to Go database/sql pool settings:
- MaxOpenConns: 25 — at most 25 concurrent connections per replica.
- MaxIdleConns: 20 — keep up to 20 warm connections per replica ready to reuse. Bumped from 10 because the pooler tolerates many client connections cheaply, and the cost of a cold handshake (~440ms transatlantic) is far higher than the cost of holding an idle connection.
- MaxLifetime: 1800s — recycle connections after 30 min. Bumped from 600s; with the pooler keeping things warm, longer lifetime reduces churn.
- MaxIdleTime: 0s — never close idle connections. Lifetime drives recycling instead.
Pool warm-up at boot
database.Connect() issues 20 parallel PingContext calls
immediately after opening the pool. This pre-establishes
MaxIdleConns connections to the pooler so the first user request
doesn't pay any handshake.
The warm-up is bounded by one round-trip time (~440ms cold), not one round-trip per connection — pings run concurrently. Confirmed in pod logs at boot:
{"level":"info","requested":20,"warmed":20,"message":"DB pool warm-up complete"}
If warm-up partially fails (e.g., 18/20 succeed), the pod still
starts; the pool fills the rest under traffic. Failure to ping at all
would be caught by the synchronous sqlDB.Ping() immediately before,
which is fatal.
Worst-case connection count
3 api + 1 worker replicas × 25 conns = 100 peak. Right at Neon free tier's ceiling, with zero margin. This is a real risk — a spike that saturates the pool on all replicas simultaneously would exhaust Neon's limit.
Mitigations to consider:
- Drop
DB_MAX_OPEN_CONNSto 15 → 60 peak. Safe on free tier. - Upgrade to Neon Scale plan (1000+ connections).
- Rely on Neon's PgBouncer to multiplex — the raw backend connections to Postgres-proper are pooled, not our TCP connections to Neon.
Currently we trust Neon's pooler to handle the multiplexing and run with the default 25/10. If we hit connection errors in prod, adjust.
Schema management
GORM AutoMigrate
On startup, the Go API's cmd/api/main.go calls
database.MigrateWithLock() which:
- Opens a dedicated Postgres connection
SELECT pg_advisory_lock(1751412071)— acquires a session-level advisory lock on a hardcoded key- Calls
db.AutoMigrate(&models.*{})for every GORM model SELECT pg_advisory_unlock(...)via deferred function- Close the connection
The advisory lock serializes migrations across replicas: when 3 api pods start simultaneously, one acquires the lock and migrates; the others block on the lock. Once the first finishes (≤2s for already- migrated schema, up to 90s on first cold boot), the next acquires and sees the schema is current (no-op migrate).
Why an advisory lock
Without it, concurrent CREATE TABLE IF NOT EXISTS ... statements from
multiple replicas would race — Postgres usually handles it, but GORM's
AutoMigrate also alters tables (adds columns, indexes) which can deadlock
under concurrency.
The advisory lock pattern (also used by Rails + Django + Alembic) is the canonical solution.
The lock key
1751412071 is a hardcoded integer in internal/database/database.go.
Arbitrary but unique — as long as nothing else in the Postgres instance
uses the same advisory lock key, no conflicts.
First-boot behavior
On a fresh database (new Neon project), the first api pod runs
through every model's CREATE TABLE statement. This is ~50 tables for
honeyDue and takes ~90 seconds.
On a warm database (tables already exist), AutoMigrate is fast — typically under 2 seconds. It still runs (GORM checks every model against the schema) but finds no work to do.
Where this bit us
With 3 api pods starting simultaneously and migrations taking 90s first time, the lock queue for the last replica is ~180s. We needed a startupProbe grace of 240s to cover this without false restart loops. See Chapter 7 §startupProbe and Chapter 19 §MigrateWithLock.
Downside: no schema versioning
AutoMigrate can only add — new tables, new columns, new indexes. It
won't drop columns, rename them, or change types destructively. For
those we'd need raw SQL migrations (a tool like golang-migrate or
dbmate).
Today: we accept that schema changes are additive-only. When we need destructive changes, we'd hand-write them.
What's in the database
Major tables (see honeyDueAPI-go/internal/models/):
| Table | Purpose |
|---|---|
auth_user |
Users (Django legacy name kept for compatibility) |
user_userprofile |
Profile data |
authtoken_token |
API auth tokens |
residence_residence |
Properties users manage |
task_task |
Maintenance tasks |
task_taskcompletion |
Task completion history |
contractor_contractor |
Contractor contacts |
documents_document |
Document records (files in B2) |
notification_notification |
In-app notifications |
subscription_usersubscription |
IAP subscriptions |
admin_users |
Next.js admin panel users |
See honeyDueAPI-go/docs/TASK_LOGIC_ARCHITECTURE.md for the task logic
model details.
Backup and recovery
Neon's built-in
Neon Launch includes point-in-time recovery within the last 24h (longer on Scale plan). To restore:
- Go to Neon console → project → Backups
- Create a branch from a timestamp
- Point the app at the new branch (change
DB_HOSTin our ConfigMap)
Done. No tape-wrangling.
What we don't have
- Off-site backup (if Neon itself is compromised, we have no exfil). A
nightly
pg_dumpto Backblaze B2 would close this gap. TODO (Chapter 20). - Tested DR drills. We've never actually restored from a Neon backup into a new branch and pointed the app at it. Should be routine; hasn't been exercised.
Migrations from old MyCrib/Casera data
honeyDue originally ran on a Django codebase (MyCrib / Casera-era). The
schema inherits Django's naming (app_model table names, _id suffix
foreign keys). The Go app's GORM models have TableName() methods that
preserve this:
func (Task) TableName() string { return "task_task" }
This isn't ideal (GORM's default tasks would be cleaner), but changing
would require a migration that renames every table — more risk than
value.
Neon regions
Neon's default region for new projects is aws-us-east-1 (Virginia).
Our DB is there. Latency from Nuremberg to us-east-1 is ~108ms one-way
TCP-level (verified by nc -z -w 5 from hetzner1), so ~220ms RTT
through Neon's pooler stack.
This is the slowest hop in our data flow. Every api request that needs
a DB query pays this latency at least once. Sub-millisecond Postgres
execution time (verified via EXPLAIN ANALYZE: 0.04-0.34 ms on every
hot path) means wall-clock latency = network + Neon proxy overhead.
Optimizations layered on top to minimize round trips
We don't move the DB region (yet) but we cut the number of RTTs per request via:
- Auth caching (Chapter 7 §Redis) — token + user lookups served from Redis (1-hour TTL) and per-pod in-memory cache (5-min TTL). On warm cache: 0 SQL round-trips for auth.
- JOIN consolidation — two-step
find residence-IDs → find tasks IN idscollapsed into a single query with a Postgres subquery. One RTT instead of two. - Single-query auth — token + user fetched in one INNER JOIN instead of GORM's two-query Preload pattern.
- Residence-IDs Redis cache — cached per user with 5-min TTL,
invalidated on Create/Delete/Join/Remove. Saves 1 RTT per
/api/documents/,/api/contractors/,/api/residences/summary/request.
After these, a fully-warm /api/tasks/ is 1 SQL round-trip total
(~220ms wall-clock). Verified via Jaeger trace — see Chapter 15.
When this still matters
- Any cold-cache request still pays 2-3 RTTs (~500-700ms).
- Pod startup pays 1 RTT × 20 (warm-up), but that runs in parallel: ~440ms one-shot.
Long-term fix: migrate Neon to aws-eu-central-1 (Frankfurt) — drops
RTT to ~5ms and brings warm-cache requests under 50ms. Tracked in
docs/observability-plan.md and Chapter 18 §migration triggers.
Environment variables the app reads
From ConfigMap:
| Var | Purpose |
|---|---|
DB_HOST |
Neon pooler hostname (-pooler suffix) |
DB_PORT |
5432 |
POSTGRES_USER |
neondb_owner |
POSTGRES_DB |
honeyDue |
DB_SSLMODE |
require |
DB_MAX_OPEN_CONNS |
25 |
DB_MAX_IDLE_CONNS |
20 |
DB_MAX_LIFETIME |
1800s |
DB_MAX_IDLE_TIME |
0s (never close idle) |
From Secret (honeydue-secrets):
| Var | Purpose |
|---|---|
POSTGRES_PASSWORD |
Neon DB password |
Operator cheat sheet
# Connect to Neon from workstation (requires psql + the password)
PGPASSWORD="<pw>" psql -h ep-floral-truth-amttbc5a.c-5.us-east-1.aws.neon.tech \
-U neondb_owner -d honeyDue
# From a pod (lets you debug against the actual in-cluster network path)
kubectl exec -n honeydue -it deploy/api -- sh
# inside the pod (no psql by default, but wget + JSON API works)
wget -qO- http://127.0.0.1:8000/api/health/
# See current migration state (no direct CLI, but the api logs show it)
kubectl logs -n honeydue deploy/api | grep -i migration
# See active connections (run against Neon)
SELECT count(*), usename, state, application_name
FROM pg_stat_activity
GROUP BY usename, state, application_name;