github-featured/triggerdotdev--trigger.dev

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T

nicktrn fa15438e42 perf(ci): speed up unit tests with LPT sharding + container scoping (#3855 )

Speeds up and de-flakes the unit-test suite: testcontainers booted once
per vitest worker (per-test isolation kept only where a test runs
background redis work that outlives it), a duration-weighted shard
sequencer so each shard does roughly equal work, the slowest suites
split, two genuine flakes fixed (`streamBatchItems` shared-redis leak;
run-engine waits that relied on fixed sleeps), and transient DockerHub
pulls retried.

**Timings (CI, per-shard wall):** worst unit-test shard ~771s → ~294s;
packages/webapp shards ~250-270s, most internal ~190-240s. All 25 shards
green.

A shard breaks down as ~70s fixed setup (install / image-pull /
generate) + ~70s cold `^build` + the actual container tests. So the
remaining cost is mostly the tests themselves plus that fixed setup.

**Next (separate, timings):**
- **typecheck (~6m24s)** — the slowest check overall; bound by
full-graph `tsc`, not the TS version (a TS6 branch is still ~6m17s). The
real lever is **tsgo** (the Go compiler).
- Possible later: turbo CI caching could trim the ~70s cold build on
*warm* runs, but it's conditional (cold runs rebuild anyway) and doesn't
touch setup or test time — secondary.

`cli-v3` e2e and `sdk-compat` are path-gated (don't run on test-infra
changes) and already comfortably fast.

2026-06-07 12:00:32 +01:00

src

feat(schedule-engine): stop persisting per-tick schedule state (#3476 )

2026-05-01 08:22:39 +01:00

test

perf(ci): speed up unit tests with LPT sharding + container scoping (#3855 )

2026-06-07 12:00:32 +01:00

package.json

Update zod package to version 3.25.76 across all modules (#2352 )

2025-08-06 14:48:43 +01:00

README.md

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tsconfig.build.json

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tsconfig.json

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tsconfig.src.json

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tsconfig.test.json

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vitest.config.ts

perf(ci): speed up unit tests with LPT sharding + container scoping (#3855 )

2026-06-07 12:00:32 +01:00

README.md

@internal/schedule-engine

The @internal/schedule-engine package encapsulates all scheduling logic for Trigger.dev, providing a clean API boundary for managing scheduled tasks and their execution.

Architecture

The ScheduleEngine follows the same pattern as the RunEngine, providing:

Centralized Schedule Management: All schedule-related operations go through the ScheduleEngine
Redis Worker Integration: Built-in Redis-based distributed task scheduling
Distributed Execution: Prevents thundering herd issues by distributing executions across time windows
Comprehensive Testing: Built-in utilities for testing schedule behavior

Key Components

ScheduleEngine Class

The main interface for all schedule operations:

import { ScheduleEngine } from "@internal/schedule-engine";

const engine = new ScheduleEngine({
  prisma,
  redis: {
    /* Redis configuration */
  },
  worker: {
    /* Worker configuration */
  },
  distributionWindow: { seconds: 30 }, // Optional: default 30s
});

// Register next schedule instance
await engine.registerNextTaskScheduleInstance({ instanceId });

// Upsert a schedule
await engine.upsertTaskSchedule({
  projectId,
  schedule: {
    taskIdentifier: "my-task",
    cron: "0 */5 * * *",
    timezone: "UTC",
    environments: ["env-1", "env-2"],
  },
});

Distributed Scheduling

The engine includes built-in distributed scheduling to prevent all scheduled tasks from executing at exactly the same moment:

import { calculateDistributedExecutionTime } from "@internal/schedule-engine";

const exactTime = new Date("2024-01-01T12:00:00Z");
const distributedTime = calculateDistributedExecutionTime(exactTime, 30); // 30-second window

Schedule Calculation

High-performance CRON schedule calculation with optimization for old timestamps:

import {
  calculateNextScheduledTimestampFromNow,
  nextScheduledTimestamps,
} from "@internal/schedule-engine";

const nextRun = calculateNextScheduledTimestampFromNow("0 */5 * * *", "UTC");
const upcoming = nextScheduledTimestamps("0 */5 * * *", "UTC", nextRun, 5);

Integration with Webapp

The ScheduleEngine should be the API boundary between the webapp and schedule logic. Services in the webapp should call into the ScheduleEngine rather than implementing schedule logic directly.

Migration Path

Currently, the webapp uses individual services like:

RegisterNextTaskScheduleInstanceService
TriggerScheduledTaskService
Schedule calculation utilities

These should be replaced with ScheduleEngine method calls:

// Old approach
const service = new RegisterNextTaskScheduleInstanceService(tx);
await service.call(instanceId);

// New approach
await scheduleEngine.registerNextTaskScheduleInstance({ instanceId });

Configuration

The ScheduleEngine expects these configuration options:

prisma: PrismaClient instance
redis: Redis connection configuration
worker: Worker configuration (concurrency, polling intervals)
distributionWindow: Optional time window for distributed execution
tracer: Optional OpenTelemetry tracer
meter: Optional OpenTelemetry meter

Testing

The package includes comprehensive test utilities and examples. See the test directory for usage examples.