Row 81 — the cap could not be enforced on a replicated node. MaxStorageMb was compared against page_count-freelist_count over the WHOLE consolidated LocalDb file, which since Phase 1/2 holds ten tables plus __localdb_oplog / __localdb_row_version / __localdb_snapshot_state. Every 1000-row trim batch freed ~390 KB of site_events pages and added ~1000 oplog rows + ~1000 tombstones to the same file, so the measured size did not fall, the "size did not decrease" guard fired, and the trim stopped 2.5x over a 64 MB cap with 226 k rows still present. A node whose peer was down could not enforce its cap at all, and the event log's budget was in practice shared with bookkeeping it does not own. The cap now measures site_events AND ITS FOUR INDEXES only, so replication bookkeeping can neither consume nor block the budget — and the cap stops being a function of the peer's health, which was the wrong direction of coupling: an inflated oplog is a replication fault, and letting it drive event deletion would destroy operational history in response to one. dbstat — the exact per-table measurement the register proposed — is NOT usable here, verified before implementing. It is a compile-time option and the bundled SQLitePCLRaw.lib.e_sqlite3 (SQLite 3.53.3) does not enable it: PRAGMA compile_options lists no ENABLE_DBSTAT_VTAB, pragma_module_list returns ten modules with neither dbstat nor sqlite_dbpage, and selecting from dbstat fails with "no such table". Switching SQLite builds was rejected — the provider is shared with ZB.MOM.WW.LocalDb and every other consumer, so it trades cap accuracy for fleet-wide version skew. The footprint is therefore modelled from sampled row width (500 rows each end, octet_length so multi-byte UTF-8 is not under-counted) through a page-layout model; whole pages rather than a flat rate, because page fill collapses once rows approach half a page and a linear model underestimates that by ~40%. Clamped by whole-file logical size, a true upper bound that can only correct an over-estimate and never binds on a replicated node. Index pages count against the cap deliberately: measured at ~34% of the table's footprint, and the 1 GB default was sized against a 393 B/row figure that already included them. Guard semantics restated — two backstops replace the single on-disk check: (1) row width unsampleable => refuse to trim (checked before the cap comparison, since a zero width makes "over cap" unanswerable rather than false; the old loop's answer to an unanswerable cap was to keep deleting); (2) estimated size not falling across a batch => stop. (2) is the old guard re-based onto the table-scoped metric, so it can no longer be tripped by replication bookkeeping and now means exactly one thing: events are arriving as fast as the trim removes them. For that to be observable the loop re-reads the row count each batch, while bytes-per-row is sampled once per tick and held fixed — re-sampling per batch would jitter the estimate as the trim eats the head of the table and could stall the loop through guard (2), the same self-defeating measurement as row 81 itself. Row 84 — LogReplicationBacklogNote moved from per-phase to once per tick, driven by the shared PurgeBudget. A tick where retention AND the cap trim both deleted used to emit two identical Information notes; the tick total is also the more useful number beside an oplog spike. Measured model error: -0.8% / +8.4% / +12.8% across representative workloads, biased high on purpose (an early cap forfeits budget; a low one fails at its only job). Independently cross-checks row 34's harness at 397.2 vs 393 B/row. Fail-before: reverting the estimator to whole-file semantics fails 5 of the new tests and reproduces the original signature exactly (remaining=2000 estimate=21725184 cap=11534336 — rows destroyed, cap still unmet); restoring per-phase notes fails the row-84 test with "collection contained 2 matching items". No config keys added or renamed, so no rig/deploy changes. Decision record: docs/plans/2026-08-17-site-event-log-cap-semantics-decision.md Tests: SiteEventLogging 104/104 (was 93), Host 520/520, solution build clean.
32 KiB
ScadaBridge Cluster Topology Guide
Architecture Overview
ScadaBridge uses a hub-and-spoke architecture:
- Central Cluster: Two-node active/standby Akka.NET cluster for management, UI, and coordination.
- Site Clusters: Two-node active/standby Akka.NET clusters at each remote site for data collection and local processing.
%%{init: {'theme':'base', 'themeVariables': {'textColor':'#111111','lineColor':'#555555','edgeLabelBackground':'#ffffff','fontSize':'15px'}}}%%
flowchart TD
USERS["Users<br/>(HTTPS / LB)"]
subgraph CENTRAL["Central Cluster"]
NA["Node A<br/>Active"]
NB["Node B<br/>Standby"]
NA <--> NB
end
USERS --> NA
CENTRAL --> SITE01
CENTRAL --> SITE02
CENTRAL --> SITE03
CENTRAL --> SITEN
subgraph SITE01["Site 01"]
S01A["A<br/>Active"]
S01B["B<br/>Standby"]
end
subgraph SITE02["Site 02"]
S02A["A<br/>Active"]
S02B["B<br/>Standby"]
end
subgraph SITE03["Site 03"]
S03A["A<br/>Active"]
S03B["B<br/>Standby"]
end
subgraph SITEN["Site N"]
SNA["A<br/>Active"]
SNB["B<br/>Standby"]
end
classDef start fill:#d5e8d4,stroke:#82b366,color:#111111;
classDef proc fill:#dae8fc,stroke:#6c8ebf,color:#111111;
classDef dec fill:#fff2cc,stroke:#d6b656,color:#111111;
classDef warn fill:#ffe6cc,stroke:#d79b00,color:#111111;
classDef muted fill:#f5f5f5,stroke:#999999,color:#666666;
class USERS dec
class CENTRAL proc
class NA,S01A,S02A,S03A,SNA start
class NB,S01B,S02B,S03B,SNB muted
class SITE01,SITE02,SITE03,SITEN warn
Central Cluster Setup
Cluster Configuration
Both central nodes must be configured as seed nodes for each other:
Node A (central-01.example.com):
{
"ScadaBridge": {
"Node": {
"Role": "Central",
"NodeHostname": "central-01.example.com",
"RemotingPort": 8081
},
"Cluster": {
"SeedNodes": [
"akka.tcp://scadabridge@central-01.example.com:8081",
"akka.tcp://scadabridge@central-02.example.com:8081"
]
}
}
}
Node B (central-02.example.com):
{
"ScadaBridge": {
"Node": {
"Role": "Central",
"NodeHostname": "central-02.example.com",
"RemotingPort": 8081
},
"Cluster": {
"SeedNodes": [
"akka.tcp://scadabridge@central-02.example.com:8081",
"akka.tcp://scadabridge@central-01.example.com:8081"
]
}
}
}
Seed order is load-bearing — each node lists ITSELF first (decision 2026-07-22). Note Node B's list is the reverse of Node A's. Akka only lets
seed-nodes[0]form a new cluster, so a node listing its partner first can never boot while that partner is down.StartupValidatorrejects the boot if the ordering is wrong, comparing host and port; use the same spelling of the hostname inNodeHostnameand in the seed URI, since Akka does no DNS canonicalisation (central-02andcentral-02.example.comare different seed identities). Seedocs/requirements/Component-ClusterInfrastructure.md→ Seed Node Ordering.
Cluster Behavior
- Split-brain resolver:
auto-down(AutoDowningprovider,auto-down-unreachable-after= 15s) since the 2026-07-21 availability-over-partition-safety decision — the leader among the reachable members downs the unreachable peer, so a hard crash of either node fails over. Accepted trade: a real partition leaves both sides active until an operator restarts one.keep-oldest(withdown-if-alone = on) remains a supportedSplitBrainResolverStrategyvalue, but in a two-node cluster it cannot survive a crash of the oldest node. Seedocs/plans/2026-07-21-auto-down-availability-decision.md. - Minimum members:
min-nr-of-members = 1— a single node can form a cluster. - Failure detection: 2-second heartbeat interval, 10-second threshold.
- Total failover time: ~25 seconds from node failure to singleton migration.
- Singleton handover: Uses CoordinatedShutdown for graceful migration.
Shared State
Both central nodes share state through:
- SQL Server: All configuration, deployment records, templates, and audit logs.
- JWT signing key: Same
JwtSigningKeyin both nodes' configuration. - Data Protection keys: Shared key ring (stored in SQL Server or shared file path).
Load Balancer
A load balancer sits in front of both central nodes for the Blazor Server UI:
- Health check:
GET /health/ready - Protocol: HTTPS (TLS termination at LB or pass-through)
- Sticky sessions: Not required (JWT + shared Data Protection keys)
- If the active node fails, the LB routes to the standby (which becomes active after singleton migration).
Site Cluster Setup
Cluster Configuration
Each site has its own two-node cluster:
Site Node A (site-01-a.example.com):
{
"ScadaBridge": {
"Node": {
"Role": "Site",
"NodeHostname": "site-01-a.example.com",
"SiteId": "plant-north",
"RemotingPort": 8081
},
"Cluster": {
"SeedNodes": [
"akka.tcp://scadabridge@site-01-a.example.com:8081",
"akka.tcp://scadabridge@site-01-b.example.com:8081"
]
}
}
}
Site Node B reverses this list —
site-01-bfirst,site-01-asecond — per the self-first seed rule above. It applies to site pairs exactly as it does to the central pair: without it,site-01-bcannot boot whilesite-01-ais down.
Site Cluster Behavior
- Same split-brain resolver as central (
auto-down, per the 2026-07-21 decision — see the Central Cluster Behavior note above). - Singleton actors: Site Deployment Manager migrates on failover.
- Staggered instance startup: 50ms delay between Instance Actor creation to prevent reconnection storms.
- SQLite persistence: each node owns its own consolidated LocalDb database, kept in step by asynchronous CDC replication over a gRPC sync stream (LocalDb Phase 1 + 2). The nodes do NOT share a SQLite file.
- CDC capture triggers are installed only on a node that has replication configured —
LocalDb:Replication:PeerAddressorLocalDb:Replication:ApiKey. Either key counts, because only the initiating half of a pair setsPeerAddress(one bidirectional stream, dialled by one side); the passive half carries the key alone. A deliberately unreplicated node — site-b and site-c on the rig — runs with no triggers at all and stops paying the per-write capture cost. - Stale-trigger cleanup is automatic (LocalDb 0.2.0). A node with no replication configured does
not merely skip registration — at boot it calls
DeregisterReplicatedon all ten tables, dropping any capture triggers an earlier build installed and pruning those tables' oplog and row-version rows. It is idempotent, so a file that was never registered reports nothing to clean; when something was cleaned the node logs it once at Information. Recreating the data volume is no longer required to stop an in-place-upgraded node from capturing.
Turning replication ON for a site that has been running without it
Supported as of LocalDb 0.2.0. Set the keys on both nodes and restart both (see the stop-and-start-together rule below — this is a pair-wide change, not a rolling one). Existing rows are carried across:
- Pre-existing rows are baselined automatically. ScadaBridge registers every replicated table
with
baselineExistingRows: true. Capture is change-data-capture, so rows written while the node had no triggers appear in neither the oplog nor__localdb_row_version— and LocalDb's snapshot resync streams from that ledger. Baselining seeds the ledger for those rows at the LWW floor (HLC0, stamped with the node's own id) and flags a snapshot resync, so the peer actually receives them. Copying one node's database onto the other beforehand is no longer necessary. - What the floor means for conflicts. Every genuine HLC is a UTC millisecond shifted left 16
bits, so it is strictly greater than
0: a baselined row loses to any real remote write of the same key and wins only where the peer holds no version of that key at all. The one ambiguous case is both nodes baselining the same key (e.g. both were restored from the same legacy file) — both hold HLC0and the node-id tie-break decides. That is convergent but arbitrary as to which content survives, so if the two files may disagree on a key, start both nodes from one node's database. - Seeding is idempotent (
ON CONFLICT DO NOTHING), so a row that already has a genuine version keeps it and no snapshot is flagged. Booting with baselining on every start is free after the first. - The flag is per-table as of LocalDb 0.3.0. Turning replication on for the first time still
seeds all ten tables at once, so the flagged set is every registered table and the pair exchanges
an ordinary full snapshot — that part is unchanged, so a site whose
site_eventstable is at its 1 GB cap should still be purged before the first enable, and one slow first sync expected. What changes is every later edit: adding an eleventh table toSiteLocalDbSetup.ReplicatedTableson a site that is already replicating now snapshots that one table, where through 0.2.x the single per-database flag re-streamed all eleven in full, in both directions at once. Upgrading a replicating pair to 0.3.0 in place is a no-op for this: the ten tables are already ledgered, so nothing seeds and nothing is flagged. - Mixed 0.2.x/0.3.0 versions still sync. Scoped snapshots are negotiated per session by capability, and a peer that does not advertise it is sent a full snapshot — so the pin bump does not have to be simultaneous for replication's sake. (It still has to be simultaneous for the stop-and-start-together rule below, which is a separate constraint.)
Turning replication back OFF is likewise a both-nodes change: deregistration must be symmetric, because the sync handshake compares the two nodes' registered-table digests fail-closed — a node that drops a table its peer still replicates stops syncing with a schema-mismatch error rather than diverging silently. Turning it on again later re-baselines, which is what makes the ledger prune on deregistration safe.
Reading the replication backlog — the daily site_events purge burst
The site health report carries LocalDbReplicationConnected and LocalDbOplogBacklog (nullable —
null means "no reading", not "disconnected with an empty backlog"), and the same numbers export
as the localdb_* Prometheus series (localdb_oplog_depth is the backlog gauge). A healthy pair
sits at a backlog of roughly zero, so a sudden spike naturally reads as a replication problem.
One expected spike is not a problem: the daily site_events retention purge. site_events is
one of the ten replicated tables, and its retention DELETE is captured by CDC exactly like an
ordinary write — by design, since LocalDb Phase 2 there is deliberately no purge-exemption path
(the same property that makes a mass DELETE dangerous, which is why ReplaceAllAsync was deleted
rather than reinstated). One oplog row is therefore queued per deleted event, and the backlog jumps
by the size of the batch the tick deleted.
The spike is bounded per tick (register row 34, measured:
docs/plans/2026-08-15-site-events-purge-burst-measurement.md). One purge tick deletes at most
ScadaBridge:SiteEventLog:MaxPurgedRowsPerTick rows — default 250 000, across the retention
purge and the cap trim combined — so the height of the spike is a property of the configuration,
not of how much history had expired. That matters because the burst used to be unbounded: a full
1 GB event log holds ~2.73 million rows, and expiring all of them at once queued 2 731 947 oplog
rows, 2.7x LocalDb's MaxOplogRows (default 1 000 000) — enough for the maintenance tick to
prune the oplog and flag a full ten-table snapshot resync. A healthy peer blunts that (the oplog
drains while the purge runs — measured peak was 391 000, not 2.73 M), which is precisely the problem:
the old safety margin was a function of how fast the peer happened to be, and vanished when the peer
was down. Set MaxPurgedRowsPerTick to 0 to restore the old unbounded behaviour.
- When. Every
ScadaBridge:SiteEventLog:PurgeInterval(default 24 h), plus once at startup — except after a tick that hit the ceiling, which schedules the next tick afterScadaBridge:SiteEventLog:PurgeCatchUpInterval(default 5 minutes) instead. So a large backlog appears as a run of bounded spikes minutes apart rather than one huge one; a worst-case 2.73 M-row backlog converges in ~11 ticks ≈ 55 minutes. The cadence is anchored to the end of the previous purge, not to a wall-clock hour, so the burst lands at a different time of day after each failover or restart — do not expect it at a fixed hour. The storage-cap trim (default 1 GB) can produce the same shape off-schedule, and draws from the same per-tick budget. - Where it shows. Only on a node with replication configured — the rig's site-a. site-b/site-c have no capture triggers at all and report no backlog for a purge.
- What healthy looks like.
LocalDbReplicationConnectedstays true across the spike, and the backlog drains back to ~0 as the peer acks the batch. Measured on a loopback pair at ~10 800 tombstones/second, so a full 250 000-row tick drains in well under a minute (delta messages are bounded byLocalDb:Replication:MaxBatchBytes, default 2 MB, and secondarily byMaxBatchSize). No dead letters, no schema-mismatch errors. - What is actually wrong.
LocalDbReplicationConnectedfalse while the backlog climbs, a backlog that keeps rising across successive readings rather than draining, or a backlog that never returns near zero between bursts. Those point at the sync stream — an ApiKey mismatch (fail-closed: the pair simply stops converging), an unreachable peer, or an asymmetric registered-table set.
Correlating it in the log. When a purge on a replication-enabled node actually deletes rows it logs an Information line next to the purge count:
Purged 41230 events older than 30 days
Purged 41230 site_events rows on a replication-enabled node — a transient LocalDb oplog backlog
of up to that many rows is expected while the deletes replicate to the peer. It drains on its own;
LocalDbReplicationConnected staying true with the backlog returning to ~0 is the healthy signature.
A tick deletes at most 250000 rows, so the spike is bounded by that number rather than by how much
history had expired.
An unreplicated node logs only the first line. If a backlog spike has no such line near it in the active node's log, the purge is not the explanation and the spike is worth investigating.
The second line is emitted once per purge tick, and its count covers the retention purge and
the storage-cap trim together. If you are comparing it against the Purged N events older than…
line above it, expect the two numbers to differ whenever the cap trim also ran — the note reports
the tick's whole contribution to the oplog, which is what a backlog spike is made of. (Through
2026-08-16 the note was emitted per phase, so a tick that ran both produced two near-identical
lines; register row 84.)
A tick that hit the ceiling adds a Warning, rate-limited to one line per 15 minutes so a converging backlog does not flood the log:
Event log purge stopped at its per-tick ceiling of 250000 rows (250000 deleted); expired events
remain and the next purge runs in 00:05:00 instead of 1.00:00:00.
Every hit — throttled line or not — increments the counter
scadabridge_site_event_log_purge_ceiling_hits. Read the counter's shape, not a single hit: a
short run of hits that stops is a backlog converging (normal, e.g. the first purge after enabling
replication on a long-running site); hits that never stop mean the site writes events faster than
one paced tick can purge, i.e. MaxPurgedRowsPerTick or PurgeCatchUpInterval is mis-sized for
that site's event rate.
Two dashboard surfaces make this reviewable rather than a log-archaeology exercise (register row 33):
- The "Replication backlog" badge on the site tile of the Health dashboard. It is deliberately
a sustained signal, not a bare threshold: the badge appears only once the backlog has stayed
above
ScadaBridge:HealthMonitoring:LocalDbBacklogThreshold(default 1000) continuously forScadaBridge:HealthMonitoring:LocalDbBacklogSustainedFor(default 15 minutes). The daily purge burst described above drains in seconds to a couple of minutes, so it never reaches the dwell and never badges the site — which is the entire reason the dwell exists. The per-tick ceiling reinforces that rather than threatening it: pacing lowers the spike (250 000 rows maximum instead of an unbounded 2.7 M) at the cost of more ticks, and a 250 000-row tick was measured draining in well under a minute — even allowing 10x for a real inter-node link that is ~4 minutes, against a 15-minute dwell and a 5-minute gap to the next tick. (The unpaced 2.73 M burst drained in 6.0 minutes on loopback: inside the dwell, but with only 2.5x of margin, so a materially slower link would have badged.) A bare threshold would fire once a day on every replicated site and be ignored within a week. The dwell is validated to be at least oneReportInterval, since a shorter window could be satisfied by a single sample and would collapse back into a bare threshold. - The "LocalDb Replication Backlog" trend chart in the dashboard's per-site Site Health Trends panel, backed by the KPI history store (sampled every minute, retained 90 days raw / 365 days hourly). This is what answers the question a point-in-time reading cannot: did that spike drain? A past purge burst appears as a spike that returns to ~0; a real fault appears as a level that never comes back down.
Both surfaces are silent on an unreplicated site, by design. LocalDbOplogBacklog and
LocalDbReplicationConnected are nullable, and null means "no reading", never zero. The KPI
sampler therefore writes no sample at all rather than a fabricated 0, so site-b/site-c show an
empty chart rather than a flat zero line, and they never accumulate the dwell anchor the badge
keys off. A gap in those series means "not replicated / not reporting" — which is the truth. Note
that false and null differ for the connected flag: a configured link that is DOWN samples as 0,
while no link at all samples as nothing.
Site Pair Upgrades — stop and start BOTH nodes together
A rolling upgrade of a site pair, one node at a time, is no longer supported. It worked while
the bespoke replicator kept a legacy SfBufferSnapshot compatibility handler so a new standby
could still apply an old active node's monolithic snapshot. LocalDb Phase 2 deleted that handler
along with the replicator, so a mixed-version pair has no common replication path: the two nodes
will run, but they will not converge, and the divergence is silent.
Stop both nodes of a site pair, upgrade both, then start both.
A release that adds a column to a replicated table is the same constraint, enforced louder.
ReplicatedTable.ComputeDigest hashes every column name and declared type, and the sync handshake
compares those digests fail-closed — so a mixed-version pair whose builds disagree about a table's
columns does not diverge silently, it refuses to sync with a LocalDbSchemaMismatchException.
Stopping and starting both nodes together, which is already the rule above, is the whole fix; no
manual trigger or oplog migration is needed, because RegisterReplicated re-reads
PRAGMA table_info on every boot and rebuilds the capture triggers (DROP + CREATE) over the
current column set. The site schema's own AddColumnIfMissing runs before registration on that
same boot, so a node picks up the new columns and the matching triggers in one start.
(Most recent instance: external_systems gained max_retries / retry_delay_ms for the
per-system store-and-forward retry policy.)
Related bound — do not leave one node of a pair offline for long. A node absent for longer than
LocalDb:Replication:TombstoneRetention (default 7 days) can resurrect deleted rows when
it rejoins: deletes replicate as HLC-ordered tombstones, and once a tombstone is pruned there is
nothing left to suppress the stale row the returning node still holds. Within the retention window
a rejoin is safe and self-correcting (verified live: a node stopped and restarted mid-load rejoined
with both nodes byte-identical and zero duplicates). Beyond it, rebuild the returning node's
database from its peer rather than letting it rejoin.
Docker-rig data files on macOS/OrbStack — a virtiofs corruption + availability hazard
Scope: the local docker/ and docker-env2/ development rigs on macOS only. This is a
host-level property of the filesystem the rig's data files sit on, not a ScadaBridge defect and
not something a production Linux deployment is exposed to. It is documented here because it has
already cost two databases and half a session, and because the recovery is non-obvious.
Every ScadaBridge data file on the rig rides a relative bind mount out of the repo working tree
— ./site-a-node-a/data:/app/data and its siblings, which is where site-localdb.db,
auditlog.db and the secrets store all live. On macOS that path crosses virtiofs to reach the
Linux VM, and virtiofs does not give SQLite true fsync durability. SQLite's crash-safety
contract assumes a successful fsync means the bytes are on stable storage; when that is not true,
an abrupt container kill mid-write can leave a torn file. docker compose up --force-recreate
— which deploy.sh uses — is exactly such an abrupt kill.
Two distinct failure modes have been observed live (both 2026-08-15):
1. Silent database corruption. Both site-a LocalDb files were found malformed:
SQLite Error 11: 'database disk image is malformed'
Note how differently the two nodes presented, because this is the part that makes it hard to spot:
- site-a-b surfaced it as a running fault — every sync call threw, replication reported
connected: falsewith a backlog of 892, and the faulted session retried about once a minute. The node stayed up and otherwise healthy-looking. - site-a-a was corrupt too, but latently — nothing on the running build ever read the
damaged pages. It only became fatal on the next upgrade, when a new build's boot-time
re-registration read pages the old build never touched:
SqliteLocalDbconstruction threw and the container SIGABRT crash-looped (×12).
The lesson to carry: a clean-looking node proves nothing about its file. Corruption can sit latent until an unrelated code change happens to read further into the database.
2. The OrbStack VM idle-sleeping mid-operation. The VM can suspend under its idle policy while
work is in flight. ~/.orbstack/log/vmgr.log records it plainly:
vmgr ... msg=sleep
On wake, the virtiofs layer logs repeated errors of the form:
refresh_nodeid: race with new lookup
and docker hangs — commands stop returning, docker ps comes back empty — for as long as it
takes to notice. The fix is orb restart docker; data survives and containers auto-restart.
Observed cost: roughly 20 minutes of a session lost to diagnosing what looked like a cluster
failure but was a host one. If the rig goes unresponsive as a whole, check vmgr.log before
investigating ScadaBridge.
Recovery runbook — LocalDb corruption on a site pair (proven)
This is the procedure that recovered site-a. It relies on the pair being able to reseed itself, so it is a replicated pair's recovery; an unreplicated node has no peer to reseed from and must be restored from a backup instead.
-
Stop BOTH nodes of the site pair, together. Not one at a time — this is the same stop-and-start-together rule as Site Pair Upgrades above, for the same reason.
-
Quarantine the database and its sidecars — do not delete them. Rename all three, keeping them for forensics:
# per affected node's data directory mv site-localdb.db site-localdb.db.corrupt-$(date +%F) mv site-localdb.db-wal site-localdb.db-wal.corrupt-$(date +%F) mv site-localdb.db-shm site-localdb.db-shm.corrupt-$(date +%F)The
-waland-shmfiles must move with the main file. Leaving a stale WAL beside a fresh database is its own corruption. -
Start both nodes together. The fresh files reseed themselves from two independent paths:
SiteReconciliationActor's node-startup fetch pulls config back from central when central reports gaps, and LocalDb's CDC snapshot resync merges the peer's rows under LWW. -
Verify convergence, do not assume it:
LocalDbReplicationConnectedshould readtrueandLocalDbOplogBacklogshould settle to ~0 on the site health report. (See Reading the replication backlog above for why a transient spike is normal and not a fault.)
On the live recovery, both quarantined files were large (394 MB and 416 MB), the pair converged to
connected: true / backlog 0, and a schema change in flight at the time additionally proved the
digest handshake green.
Mitigation options, with their trade-offs
None of these is applied today; the rig deliberately still runs on bind mounts, and the accepted position is the runbook above. Recorded so the choice is a choice:
| Option | Gains | Costs |
|---|---|---|
| Move rig data dirs to named docker volumes | Files live on native ext4 inside the VM, out of virtiofs entirely — removes the corruption mechanism at the source | Loses the host-side inspectability the debugging sessions lean on constantly: no more opening site-localdb.db from the Mac, no ls of a node's data dir from the repo tree. Requires a compose change. |
| Disable OrbStack's idle pause | Removes failure mode 2 (the mid-operation sleep and the virtiofs refresh_nodeid storm) |
A host-level setting outside this repo, so it cannot be version-controlled or applied by deploy.sh — it silently does not exist on a new machine. Does nothing about failure mode 1. |
| Accept, and use this runbook (current) | No changes to compose or host config; full host-side inspectability retained | Corruption recurs on the next unlucky --force-recreate, and can sit latent until a later upgrade turns it into a crash loop. |
Central-Site Communication
Three transports cross the boundary, not one — all now gRPC or HTTP; Akka ClusterClient was removed in Phase 4 of the ClusterClient→gRPC migration (2026-07-23), and Akka remoting no longer crosses the boundary at all:
- gRPC command/control — both directions, on sticky-failover channel pairs, dialled directly (no
receptionist, no "active central" to identify — each side dials both of the peer's node endpoints):
- Site → central to the central-hosted
CentralControlService(GrpcCentralTransport): the site lists the central nodes' gRPC endpoints inScadaBridge:Communication:CentralGrpcEndpoints(e.g.http://scadabridge-central-a:8083, the central'sCentralGrpcPort, default 8083 — direct h2c, not via Traefik, which is HTTP/1 only). A Site node must list at least one; central nodes leave it empty. - Central → site to the site-hosted
SiteCommandService(GrpcSiteTransport): central dials the site'sGrpcNodeAAddress/GrpcNodeBAddress(from the Site entity), NodeA→NodeB failover.
- Site → central to the central-hosted
- gRPC streaming + audit pull — real-time data and audit/telemetry pull on the site-hosted
SiteStreamService. Note the direction is inverted from the data flow: each site node hosts the server onGrpcPort(default 8083, h2c) and central dials in. - Plain HTTP — the deploy config itself, fetched by the site with a per-deployment token.
gRPC control-plane preshared key (required)
Every site node must set ScadaBridge:Communication:GrpcPsk, and central must hold the same
value for that site. StartupValidator refuses to boot a site node without it, deliberately:
the gate is fail-closed, so an unset key would leave the node joined, healthy-looking and
answering heartbeats while refusing every gRPC call — no live subscriptions, no audit pull, no
cached-telemetry ingest.
| Side | Where the key lives |
|---|---|
| Site node (both nodes of the pair, identical) | ScadaBridge:Communication:GrpcPsk, in production ${secret:SB-GRPC-PSK-<siteId>} |
| Central | secret SB-GRPC-PSK-<siteId> in its store — or ScadaBridge:Communication:SitePsks:<siteId> |
The store is the source that matters in production, because sites are added at runtime and their
keys cannot be enumerated in configuration at boot; SitePsks covers a host running without a
master key (the docker rig) and one-off pins.
One key per site, never one for the fleet: a compromised site must not yield another site's
key. And never share it with LocalDb:Replication:ApiKey — that authenticates the pair partner
for database replication, a different trust relationship on the same listener.
Rotation: set the new value on both sides, then restart the pair (pairs restart together
anyway — see above). Upgrading to a build that has this gate requires seeding the key first,
including in the on-host deploy/ overlays.
The key is a bearer token over plaintext h2c, so it is readable and replayable by anyone on the path. That is the accepted posture today — the same trusted-network assumption the boundary already made, now with authentication rather than none. TLS on these listeners is follow-on hardening and needs no change to the key design.
Scaling Guidelines
Target Scale
- 10 sites maximum per central cluster
- 500 machines (instances) total across all sites
- 75 tags per machine (37,500 total tag subscriptions)
Resource Requirements
| Component | CPU | RAM | Disk | Notes |
|---|---|---|---|---|
| Central node | 4 cores | 8 GB | 50 GB | SQL Server is separate |
| Site node | 2 cores | 4 GB | 20 GB | SQLite databases grow with S&F |
| SQL Server | 4 cores | 16 GB | 100 GB | Shared across central cluster |
Sizing a site's data volume — MaxStorageMb is not the whole story
ScadaBridge:SiteEventLog:MaxStorageMb (default 1 GB) bounds site_events and its four
indexes, and nothing else. It is deliberately not a cap on the consolidated LocalDb file
(register row 81 — decision record
docs/plans/2026-08-17-site-event-log-cap-semantics-decision.md). Before that change it did
measure the whole file, which on a replicated node made the cap unenforceable: the trim's own CDC
oplog rows and tombstones grew the file as fast as the deletes shrank it, and the trim stopped
2.5x over cap. Tying the event log's budget to the peer's liveness was the defect, not a feature
worth preserving.
So budget the volume as the sum of:
MaxStorageMb— the event log proper.- LocalDb replication bookkeeping —
__localdb_oplogand__localdb_row_version, bounded separately byLocalDb:Replication:MaxOplogRows(default 1 000 000) andTombstoneRetention(default 7 days). This is transient: it drains as the peer acks and as tombstones expire, but it is not small during a burst. Measured worst case (register row 34): purging a full 1 GB event log left 707 MB of bookkeeping in the file. Unreplicated sites carry none of this — they have no capture triggers at all. - The other eight consolidated tables plus the separate, unreplicated audit database at
AuditLog:SiteWriter:DatabasePath.
The 20 GB figure above has ample headroom for all three at default settings. Raising
MaxStorageMb on a replicated site should be paired with a look at the oplog settings, not done
in isolation.
Network Bandwidth
- Health reports: ~1 KB per site per 30 seconds = negligible
- Tag value updates: Depends on data change rate; OPC UA subscription-based
- Deployment artifacts: One-time burst per deployment (varies by config size)
- Debug view streaming: ~500 bytes per attribute change per subscriber
Dual-Node Failure Recovery
Scenario: Both Nodes Down
- First node starts: Forms a single-node cluster (
min-nr-of-members = 1). - Central: Reconnects to SQL Server, reads deployment state, becomes operational.
- Site: Opens SQLite databases, rebuilds Instance Actors from persisted configs, resumes S&F retries.
- Second node starts: Joins the existing cluster as standby.
Automatic Recovery
No manual intervention required for dual-node failure. The first node to start will:
- Form the cluster
- Take over all singletons
- Begin processing immediately
- Accept the second node when it joins