Fully adaptive task executor for Node.js and browsers. Self-regulates concurrency limits, sheds load under pressure, and schedules fairly across lanes — no manual tuning, no environment-specific configuration. Automatically derives detection thresholds, filter parameters, and convergence rates.

Zero dependencies. ESM-only. Works in Node.js (>=18), Deno, Bun, and browsers.

npm install concurrex

import { Executor } from 'concurrex';

const executor = new Executor();
executor.registerPool("http", { baselineConcurrency: 50 });
executor.start();

await executor.run("http", () => handleRequest(), { lane: "tenant-123" });

executor.stop(); // rejects queued tasks, cleans up timers

Concurrex wraps any async operation — if it can saturate, overload, or fail under pressure, Concurrex can manage it.

• HTTP servers — admission control for Express, Fastify, Koa. Shed excess requests with instant 503s instead of letting the entire server slow down.
• Database access — cap concurrent queries to Postgres, MySQL, Redis. Prevent connection pool exhaustion and protect downstream capacity.
• External API calls — rate-limit outbound requests to third-party services. Per-lane fairness ensures one tenant cannot monopolize API quota.
• Message processing — throttle Kafka, RabbitMQ, or SQS consumers. Back-pressure signal (isOverloaded) tells the consumer when to pause fetching.
• Background jobs — manage parallel execution of cron jobs, data pipelines, or batch imports without overwhelming shared resources.
• AI/LLM inference — control concurrent requests to model endpoints with automatic latency-based backoff.
• File I/O and uploads — limit parallel disk or network operations to avoid thrashing.
• Multi-tenant systems — lane-based fairness prevents noisy neighbors. Each tenant gets equal access regardless of request volume.

Multiple pools let you isolate different workloads (e.g. user-facing commands vs background sync) with independent limits and detection sensitivity.

Five mechanisms cooperate:

1. ProDel (Probabilistic Delay Load-shedding) — sojourn-based AQM. Drop probability P = 1 - threshold/sojourn. Adaptive LIFO/FIFO admission (FIFO when healthy, LIFO when dropping to protect fresh work).
2. Probabilistic early shedding — rejects new arrivals at enqueue time with P = dropRate/(dropRate+completionRate) * shrinkage when ProDel is dropping and pool is at capacity. Instant rejections.
3. WoLF-EWMA throughput regulator — latency detection via operational Little's Law (W = integral N(t)dt / completions), log-transformed, smoothed by a WoLF Kalman filter (IMQ-weighted outlier rejection), with a z-test on the filtered trend. Concurrency adjusted via a convergent step formula with bisection damping for O(log L) equilibrium convergence.
4. Per-lane error shedding — each lane tracks its own error rate EWMA. High-error lanes probabilistically reject new requests without affecting pool-wide concurrency.
5. Fair lane scheduling — round-robin across lanes (per-tenant, per-user, or shared). Prevents noisy neighbors from monopolizing capacity.

All statistical parameters derive from one constant: zScoreThreshold (default: 2). This determines HALF_LIFE (EWMA decay), WoLF Kalman Q/R, IMQ outlier threshold, Bayesian shrinkage strength, warm-up period, evaluation cadence, and detection sensitivity. Configurable globally and per-pool.

// Global default
const executor = new Executor({ zScoreThreshold: 2 });

// Per-pool override — tighter detection for user-facing, looser for background
executor.registerPool("commands", { zScoreThreshold: 1.5 });
executor.registerPool("background", { zScoreThreshold: 3 });
executor.registerPool("queries"); // inherits global z=2

executor.registerPool("commands", {
    delayThreshold: 100,       // Max acceptable sojourn time (ms) before ProDel reacts
    controlWindow: 100,        // Time window for ProDel grace period and throughput measurement
    baselineConcurrency: 50,   // Starting concurrency limit; gravity target during recovery
    minimumConcurrency: 5,     // Floor — limit never decreases below this
    maximumConcurrency: 200,   // Ceiling — regulator never increases above this
    zScoreThreshold: 1.5,      // Override detection sensitivity for this pool
});

// Per-user lane — fairness across users
await executor.run("commands", handleCommand, { lane: "tenant-123" });

// No lane — each call gets a unique transient lane (maximum fairness)
await executor.run("commands", handleCommand);

// Shared lane — all requests compete in one queue
await executor.run("http", handleRequest, { lane: "shared" });

import { Executor, DebounceMode } from 'concurrex';

// Only executes once even if called 3 times concurrently
const p1 = executor.runDebounced("queries", "user-123", () => fetchUser("123"));
const p2 = executor.runDebounced("queries", "user-123", () => fetchUser("123"));
const p3 = executor.runDebounced("queries", "user-123", () => fetchUser("123"));
// p1, p2, p3 all resolve to the same result

// BeforeResult mode — deduplicate until the task completes
executor.runDebounced("queries", "user-123", () => fetchUser("123"), {
    mode: DebounceMode.BeforeResult
});

Two modes:

• DebounceMode.BeforeExecution (default): Deduplicate until the task starts running.
• DebounceMode.BeforeResult: Deduplicate until the task completes.

executor.isOverloaded("commands");         // true when in DROPPING state
executor.isThroughputDegraded("commands"); // latency degradation detected
executor.getInFlight("commands");          // current in-flight count
executor.getQueueLength("commands");       // current queue depth
executor.getConcurrencyLimit("commands");  // current regulated limit
executor.getRegulatorState("commands");    // full filter state snapshot

isOverloaded returns true only during confirmed sustained overload (dropping state). Use this to pause upstream work fetching.

getRegulatorState returns a RegulatorState with the filter internals: logW, logWBar, zScore, degrading, se, dLogWBarEwma, dLogWBarVariance, inFlightEwma, completionRateEwma, dropRateEwma, errorRateEwma, regulationPhase, regulationDepth, elapsedWindows, alpha.

import { Executor, ResourceExhaustedError, ConcurrexError } from 'concurrex';

try {
    await executor.run("commands", () => handleCommand());
} catch (err) {
    if (err instanceof ResourceExhaustedError) {
        // Task rejected — overloaded, early shed, or per-lane shed
        return res.status(503).send("Service busy");
    }
    throw err; // re-throw application errors
}

// Or catch all concurrex errors
try { ... } catch (err) {
    if (err instanceof ConcurrexError) { /* any concurrex error */ }
}

Error classes:

• ConcurrexError — base class for all concurrex errors. Use for catch-all.
• ResourceExhaustedError — task rejected due to overload (ProDel drop, early shed, or per-lane shed).
• ExecutorNotRunningError — run() called after stop().
• ArgumentError — invalid configuration (duplicate pool, bad parameters).

Defaults to console. Pass any object with info, warn, error, and debug methods (pino, winston, etc.).

const executor = new Executor(); // uses console
const executor2 = new Executor({ logger: myPinoLogger });

class Executor {
    constructor(options?: { logger?: Logger; zScoreThreshold?: number });

    // Lifecycle
    start(): void;
    stop(): void;

    // Configuration
    registerPool(name: string, options?: PoolOptions): void;

    // Task execution
    run<T>(pool: string, task: () => T, options?: TaskRunOptions): Promise<T>;
    runDebounced<T>(pool: string, key: string, task: () => Promise<T> | T,
                    options?: TaskRunDebouncedOptions): Promise<T>;

    // Inspection
    isOverloaded(pool: string): boolean;
    isThroughputDegraded(pool: string): boolean;
    getInFlight(pool: string): number;
    getQueueLength(pool: string): number;
    getConcurrencyLimit(pool: string): number;
    getRegulatorState(pool: string): RegulatorState;

    // Derived constants (read-only, executor-level defaults)
    readonly zScoreThreshold: number;
    readonly halfLife: number;
}

See THEORY.md for formal analysis with 16 theorems and proofs covering convergence guarantees, stability bounds, and fairness properties.

MIT