The o6-automation benchmark gap analysis listed several server quick
wins that need no wire or public API change. This PR implements three of
them. The 2.0 server now passes the benchmark's 10 clients × 1000
outstanding Reads test with the benchmark's own queue sizing. Its 100 Hz
sampling capacity grows about 7–10× on the same machine, and a
single-value Read allocates 8 % less.
## Results
Paired A/B against `master` (071660354): alternating builds, 3 rounds (5
for Read), medians, 24-core machine shared with other sessions.
Allocated bytes and CPU per operation are the reliable signal here.
Throughput varied up to 3× between rounds of the same build, so it is
listed only where the result is pass/fail.
| Scenario | Server alloc / op | Server CPU / op | Result |
|---|---|---|---|
| o6 `sub_client`, 2048 counters, 10 ms sampling, 1 s publishing |
**2309 → 111 B / sample (−95 %)** | **3.75 → 1.14 µs / sample (−70 %)**
| PASS on both |
| Harness `counters`, 2048 items, 10 ms / 1 s | 232 → 11.2 KB /
notification (−95 %) | −74 % | GC pause 644 → 24 ms in 12 s |
| **o6 sampling capacity** (largest count with every item ≥ 99 % of
samples, doubling from 1024, then bisect) | | | **2176–2304 →
16384–22528 items** (2 searches each) |
| o6 `client`, 10 × 1000 outstanding Reads, `MaxQueuedRequestCount =
10000` | | | **master fails 3/3 (BadServerTooBusy), this PR passes 3/3**
(31–36k req/s) |
| o6 `client`, 10 × 100 outstanding Reads | 7823 → 7556 B (−3 %) | ±0 |
|
| Read, 1 value (20 sessions) | 6534 → 6020 B (**−8 %**) | −1 % | |
| Read, 100 values | −1 % | ±0 | |
| Write, 100 values | −1 % | −5 % | |
For reference, open62541 (single thread, same Windows machine and native
client) sustained 5632 items in the gap analysis.
## Changes
### 1. `MaxQueuedRequestCount` admits that many established requests
(Balanced / TrustedReservations)
- `ServerResourceIsolationOptions.CreateRuntimePlan` carved the
bootstrap, reconnect, control and trusted floors out of the configured
queue, so established sessions could queue only `N − 3`. The default
totals of the decoded-request admission stages (RequestQueue,
RequestQueueBytes, ParkedRequest) now add the floors on top; the shared
capacity equals the configured value.
- `FairRequestQueue` takes its physical bound from the provider's stage
capacity (internal `IResourceIsolationCapacitySource`), so the protected
entries stay reachable when the shared part is full.
- RequestExecution keeps its floors inside the worker limit, so an idle
worker remains for protected requests. Explicit `Stages[].Capacity`
overrides keep their meaning as absolute totals including the floors.
### 2. Sampling without a role permission check per sample
- Since #4503 every sampling cycle called `ValidateRolePermissionsAsync`
for every item. For a `CustomNodeManager2` node that built full node
metadata (13-attribute read, namespace defaults via sync-over-async,
three nested node manager operations) only to return Good: about 80 % of
the 2.3 KB per sample.
- Each sampling loop now keeps per-item state between cycles:
ReadValueIds, result buffers and the last permission verdict. A verdict
is reused while the item's Session, effective identity and node handle
are unchanged and no permission change was signalled:
- `NodeState` bumps an internal version counter when `RolePermissions`
or `UserRolePermissions` of any node change (setter or Write);
- `IConfigurationNodeManager.DefaultPermissionsChanged` (namespace
defaults);
- a new `EffectiveIdentity` instance (ActivateSession with another user,
or roles refreshed after `RoleConfigurationChanged`).
- Independently, every item is revalidated once per second, spread over
the cycles, which bounds the delay for permissions that a node manager
computes without a signal (`OnReadRolePermissions`, custom
`ValidateRolePermissionsAsync`).
- The loop reuses its item snapshot until items are added or removed,
reads all items of one owner with one context instead of a LINQ
`GroupBy` (items moved to another session by TransferSubscriptions still
use the per-owner path), marks disabled items processed instead of
rebuilding the list, and checks for a detached loop without taking the
group lock.
- `Opc.Ua.Types` grants `InternalsVisibleTo` to `Opc.Ua.Server` for the
version counter.
### 3. Read and Write call only the node managers routed for the request
- `NodeManagerServiceDispatcher.ReadAsync`/`WriteAsync` called every
node manager. Every `AsyncCustomNodeManager` (configuration,
diagnostics, core, …) then copied the system context and allocated a
dictionary and a list, even with none of the requested nodes in its
namespaces.
- Validation now collects the namespace routes of the valid operations
and the dispatcher skips node managers outside them. Every manager of a
requested namespace is still called in dispatch order, so overlapping
managers keep their precedence. A namespace without a route still calls
every node manager, which keeps `BadNodeIdUnknown` and custom routing
unchanged.
- Not done: reusing the handle resolved during validation inside
`ReadAsync` needs a new node manager overload (public API), so nodes are
still resolved twice. HistoryRead and Call keep the old dispatch: Call
routes by object and method, and HistoryRead releases continuation
points per manager.
## Behaviour notes
- **`MaxQueuedRequestCount`** keeps its 1.5.x meaning again: established
sessions can have that many decoded requests waiting. Balanced and
TrustedReservations size the RequestQueue stage at
`MaxQueuedRequestCount + floors` (for example 10,003 for 10,000). A
deployment that relied on the smaller queue lowers
`MaxQueuedRequestCount` or sets the RequestQueue `Capacity`.
`docs/MigrationGuide.md`, `docs/ResourceIsolation.md` and
`docs/ServerScalability.md` are updated.
- **Permission changes for sampled items** still apply within one or two
sampling cycles when they come through
`NodeState.RolePermissions`/`UserRolePermissions`, namespace default
permissions, or a new effective identity. Permissions that a node
manager computes without changing those (for example
`OnReadRolePermissions` or a custom `ValidateRolePermissionsAsync`)
apply within one second instead of on the next sample.
`docs/NodeManagers.md` describes it.
- **Custom node managers** that process Reads or Writes of nodes in
namespaces they did not register receive those calls only while some
valid node of the request is in an unrouted namespace. Such a manager
registers its namespaces with `RegisterNamespaceManager` (documented in
`docs/NodeManagers.md`).
## Testing
- New unit tests:
- `RuntimeResourceIsolationTests`: plan sizing per mode, explicit
capacities, and a fair queue that admits exactly `MaxQueuedRequestCount`
requests from four owners, rejects the next and still admits bootstrap
and reconnect.
- `SamplingGroupPermissionCacheTests`: verdict reuse, revocation through
node RolePermissions in the same cycle, namespace default change,
identity change, periodic revalidation, disabled items. Each change is
injected inside the Read of a known cycle, so the tests do not depend on
timing.
- `NodeManagerDispatchRoutingTests`: non-owning managers are skipped,
several owners keep result order, an unrouted namespace still calls
everyone, two managers of one namespace keep their precedence, Write.
- net10.0: `Opc.Ua.Server.Tests` 8462 passed,
`Opc.Ua.Subscriptions.Tests` 643 passed, `Opc.Ua.Sessions.Tests` 851
passed / 379 skipped, `Opc.Ua.Core.Tests` (Stack.Server) 1858 passed,
`Opc.Ua.Stress.Tests` Contract|Integration 45 passed; 0 failures.
- net48 build of `Opc.Ua.Server.Tests` clean; `dotnet format whitespace`
clean.
- Measured with `perf/ServerLoadHarness` and the o6 scenarios (`o6read`,
`o6counters`) from the gap-analysis harness, which is not part of this
PR.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
10 KiB
Server session scalability
This document describes how the reference server scales to large numbers of concurrent client sessions on a single node, what bounds that scale, the built-in controls for degrading gracefully under load, and how to configure the server and scale out. For measured numbers see Performance Benchmarks — Server session scalability.
Contents
- How a session is established
- What bounds single-node scale
- Admission control and rate limiting
- Held Publishes and the request-thread budget
- Session diagnostics cost
- Garbage collector mode
- Configuration
- Scaling out
- See also
How a session is established
A client session is brought up in four stages:
- TCP accept — the operating system accepts the socket and the listener creates a channel object.
- Secure channel —
OpenSecureChannelperforms the asymmetric (RSA) handshake: decrypt and signature-verify with the server certificate's private key, and generate nonces. - CreateSession — admission checks (session and channel limits), server-nonce generation and signing, and per-session diagnostics node creation.
- ActivateSession — verification of the client signature and the user identity token, and activation of the session.
After activation the session enters steady state: it keeps one long-polled Publish request outstanding and receives notifications as its monitored items change.
What bounds single-node scale
Session establishment is CPU-bound. The dominant cost of bringing up a session is the asymmetric secure-channel handshake — the RSA decrypt, the certificate-chain validation, and the server- and client-signature operations. Handshakes run per channel on the thread pool and parallelize across cores, so establishment throughput scales with the core count, but a large simultaneous connect burst can saturate every core. On a typical multi-core developer machine the server establishes on the order of a thousand or more concurrent sessions cleanly; beyond that, connect throughput is bounded by handshake CPU. This is the fundamental single-node ceiling.
Connect storms amplify overload. If the server is saturated and a handshake is slow enough to time out, a client may retry; the retry can create a fresh server session while the original is left orphaned, adding load rather than relieving it. Unchecked, this is a positive-feedback loop. The server's admission controls break the loop by returning a fast, deterministic busy response that a cooperating client honors, instead of failing deep in the handshake and inviting a retry.
Steady-state delivery is not the bottleneck. Once sessions are up, the asynchronous publish path continues to deliver notifications. A held Publish is asynchronously parked while it waits and, with request decoupling enabled (the default), does not tie up a request-processing worker.
Admission control and rate limiting
The server can shed excess load deterministically rather than aborting work mid-handshake. The full configuration surface — algorithms, limits, and dependency-injection hooks — is described in Rate Limiting and Admission Control. In summary, the server provides:
- Connection-admission rate limiting at the TCP listener, bounding the rate of new secure-channel handshakes to what the host can absorb.
- Session-establishment admission:
CreateSessionandActivateSessionrequests beyond the configured concurrency are rejected withBadServerTooBusy, carrying a machine-readable retry-after hint, instead of queuing unboundedly. - Incomplete-message capacity: a shared reassembly budget bounds retained chunks across listeners, leaves headroom for activated sessions, and releases abandoned messages at a fixed assembly deadline.
- HTTPS/Kestrel rate limiting: the HTTPS binding can attach an ASP.NET Core rate limiter through dependency injection.
- Client-side adaptive backoff: the client honors a server's busy signal — and any retry-after hint — with bounded exponential backoff, so a well-behaved client ramps its connects instead of hammering.
Session establishment keeps the CPU-bound signature work outside the session-table lock, so concurrent CreateSession calls are not serialized behind one signing operation.
Held Publishes and the request-thread budget
A steady-state session keeps one or more long-poll Publish requests
outstanding. Each waits for the next notification. The number depends on the
client's publish-pipelining strategy; the classic subscription engine queues
several per session to smooth delivery.
The operating-system thread is released while a Publish waits. By default,
DecoupleHeldPublishRequests also releases the request-processing worker when
the request parks. Each parked request releases its worker, so a session with
several outstanding Publishes releases several workers. A small pool can
therefore support many thousands of parked Publishes without scaling
MaxRequestThreadCount to the number of sessions or Publishes.
Set DecoupleHeldPublishRequests to false to restore the legacy behavior.
Each held Publish then occupies a worker for the duration of its wait. A
server serving N sessions needs MaxRequestThreadCount well above N to avoid
starving other requests.
Session diagnostics cost
Creating a session or subscription registers a diagnostics node and marks the live SessionDiagnostics and SubscriptionDiagnostics arrays for refresh. The arrays are rebuilt on demand when they are read or monitored, and the rebuild is throttled so that a burst of session creates does not trigger a rebuild per create. Servers that do not need the live session-diagnostics arrays can turn them off with the DiagnosticsEnabled server setting to remove the cost entirely.
Garbage collector mode
A server allocates per request on many threads at once. With the default workstation garbage collector the heap's gen0 budget is a few megabytes, so a loaded server collects hundreds of times per second and every collection suspends all request threads. In a 20-session Read load (100 values per request, 24-core machine) the workstation collector paused the process for about half of the wall-clock time; enabling Server GC on the same build doubled the request rate (21k to 44k Reads per second) and cut the 90th-percentile latency from 2.1 ms to 0.6 ms, at the price of a larger working set (about 430 MB instead of 210 MB).
Enable Server GC in the server's project file:
<PropertyGroup>
<ServerGarbageCollection>true</ServerGarbageCollection>
</PropertyGroup>
or set DOTNET_gcServer=1 in the environment. On .NET 8 and later, Server GC adapts its heap count to the load (DATAS), so idle servers stay small. The console reference server enables it.
Configuration
The following settings size a single node for its hardware (see also the sizing notes in Benchmarks.md and the admission-control settings in RateLimiting.md):
MaxSessionCountcaps concurrently open sessions. SizeMaxChannelCount(one channel per session) andMaxSubscriptionCountat or above the target session count.MaxRequestThreadCountcaps concurrent request processing. WithDecoupleHeldPublishRequestsenabled it can be sized for the active (non-parked) request concurrency rather than the session count.MinRequestThreadCountpre-warms the pool so a connect burst is not throttled by thread-pool cold-start.MaxQueuedRequestCountis how many decoded requests established sessions can have waiting for a worker. Size it at or above the total pipelining of your clients (for example 10 clients with 1,000 outstanding requests each need 10,000). The reserved queue entries of the Balanced and TrustedReservations isolation profiles are added on top; see request and caller limits.DecoupleHeldPublishRequests(defaulttrue) releases a heldPublish's request-processing worker while it waits, so a small worker pool can hold many outstanding long-polls.MaxMonitoredItemCountandMaxMonitoredItemsPerSubscription(default0, no limit) cap the monitored items in the server and in one subscription.CreateMonitoredItemsanswersBad_TooManyMonitoredItemsfor the items over the limit, and the values are published inServerCapabilities.MaxMonitoredItemsandMaxMonitoredItemsPerSubscription. Set them on servers reachable by untrusted clients;MaxMonitoredItemsPerCallonly bounds a single request.MaxFailedAuthenticationAttempts(default 5;0disables) is the per-certificate brute-force lockout. A single-certificate client that opens many sessions can trip it on transient handshake failures and then be rejected withBadUserAccessDenied; raise or disable it for bulk-connect clients.- Stagger client connects. Because establishment is CPU-bound but parallelizes across cores, throttling and staggering concurrent connects — rather than bursting them all at once — avoids self-inflicting a connect storm and is the most effective client-side measure.
Scaling out
A single node's handshake throughput is bounded by its cores. To scale beyond one node, distribute connections across several server nodes behind a connection-distributing front end. The stack provides distributed mirroring of the address space, sessions, and subscriptions for exactly this high-availability and distributed topology.
See also
- Rate Limiting and Admission Control — the connection and session-establishment limiters, the
BadServerTooBusysignalling, and the client's adaptive reconnect backoff. - Performance Benchmarks — the measured session-scaling table and the
ServerManySessionsLoadTestAsyncmacro test. - Sessions, Reconnection, and Subscription Engines — session and subscription-engine architecture.
- Subscriptions and Monitored Items Service Set — the subscription engine.
- Diagnostics — server diagnostics nodes and how to control them.