Build, schedule, execute, retry, and monitor background jobs without building the infrastructure around them.
Your Application
POST /api/v1/jobs
Job Queue Partition
billing-critical [Raft Index #49102]
Worker Node
wrk-04 (us-east-1) [Lease 30s]
Persisted State
SUCCEEDED (842ms • ACK)
One unified lifecycle guarantees durability from the instant your application dispatches a payload to final state commitment.
Your application creates a durable job with an idempotency key.
POST /api/v1/jobsThe platform determines exact execution time and allocates queue slots.
Lease allocation & concurrency checkA connected worker claims the atomic lease and executes the handler.
wrk-04 claimed lease #48102Transient failures trigger jittered exponential backoff policies.
1s → 5s → 25s → 2mThe execution is persisted with final status, telemetry, and logs.
Duration 842ms • ACKStrict transitions prevent race conditions, orphan leases, and duplicate runs.
Hardened developer infrastructure designed for predictable throughput, fault tolerance, and zero operational mystery.
Partition-based queue scheduling with deterministic at-least-once delivery, tenant isolation, and microsecond lease handoffs.
Automated backoff with full jitter stops thundering herds when external services degrade.
Cron intervals and ISO schedules executed with distributed consensus locks. Zero duplicate runs.
Dynamic worker registration, heartbeat liveness monitoring, and zero-downtime graceful drain timeouts during rolling deployments.
Throttle execution per tenant, queue, or custom key to prevent exceeding downstream database connection pools.
Direct stdout/stderr logs and lifecycle traces bound directly to every job ID for instant debugging.
10:42:18 [info] lease acquired by wrk-04
10:42:19 [ack] completed in 842ms
Idiomatic type-safe clients for your production stack. Submit work in one line and define resilient worker handlers with complete observability.
import { JobOrcClient } from '@joborc/sdk';const jobs = new JobOrcClient({ apiKey: process.env.JOBORC_API_KEY });// Enqueue durable background jobconst job = await jobs.enqueue('process-invoice', { invoiceId: 'inv_9981a', amountUsd: 4900, customerId: 'cus_3301',}, { queue: 'billing', priority: 'high', maxRetries: 3, backoff: { type: 'exponential', initialMs: 1000, maxMs: 30000 }, idempotencyKey: 'inv_9981a:settle',});console.log(`Job ${job.id} enqueued to ${job.queue}`);Eliminate guesswork. Inspect exact runtime payloads, attempt timelines, worker hostnames, and live structured stdout/stderr streams.
{
"invoiceId": "inv_881920",
"customerId": "cus_99182",
"amountUsd": 1450,
"currency": "USD",
"autoPay": true,
"recipient": "billing@acme-corp.com"
}Networks drop connections. Downstream services timeout. JobOrc ensures failed executions recover automatically without dropping payloads or corrupting state.
HTTP 504 Gateway Timeout (payment provider unresponsive after 2000ms)
Connection reset by peer (socket hang up)
HTTP 200 OK — charge captured and receipt committed
Decorrelated jitter prevents synchronized worker thundering herds.
Unique keys guarantee identical payloads execute exactly once.
Exhausted attempts route safely to DLQ with zero data loss.
Leases and state transitions replicated across clustered nodes.
Stop stitching fragile DIY queues, ad-hoc retry timeouts, and uncoordinated cron daemons. Build your production systems on hardened primitives.
| Infrastructure Primitive | Fragile DIY Plumbing | JobOrc Engine |
|---|---|---|
| Queue Storage & Buffer | Manual Redis memory config, maxclients limits, persistent disk sync | Durable partitioned storage with sub-millisecond append & zero-drop guarantee |
| Worker Lease Coordination | Custom Redis SETNX locks, split-brain race conditions, dangling locks | Raft consensus lease manager with automatic heartbeat expiration & steal |
| Retries & Exponential Backoff | Ad-hoc setTimeout, unjittered retries that stampede downstream databases | Deterministic exponential backoff with full jitter & isolated dead-letter triage |
| Distributed Cron Scheduling | Single-node cron daemons without high availability or duplicate prevention | Consensus-backed distributed scheduler with timezone & overlap policies |
| Operational Visibility | Scattered logs in Datadog/CloudWatch with no trace back to the job payload | Unified per-job execution timeline with input payloads, attempts, and live logs |
| Concurrency & Rate Limiting | Complex token-bucket scripts in Redis prone to drift under worker scaling | Strict tenant and queue partition concurrency throttles enforced at engine core |
Eliminate queue boilerplate, flaky cron daemons, and invisible background failures. Start building on hardened infrastructure in minutes.