Laravel Scheduler for ERP Workflows is the work that turns a collection of business systems into a coherent operation. ERP, CRM, e-commerce, payment, marketing, support — each is a tool. The workflow is what connects them. This guide is the field-tested pattern for this workflow tool in a business context.
What is workflow automation
Workflow automation is the discipline of moving data between systems, transforming it, and triggering actions — without a human in the loop for the routine cases. The three categories:
- Scheduled — runs at a time (daily reconciliation, weekly report).
- Event-driven — runs when something happens (order created, payment received).
- On-demand — runs when a user clicks a button (re-send invoice, re-process batch).
The 80/20 of workflow automation: 80% of the value comes from automating the 20% of cases that are routine. The other 80% of cases — the exceptions — need a human. A good workflow automation routes exceptions to a human, with all the context.
The tool landscape
The tools you can choose from, in increasing order of code involvement:
| Tool | Use when | Trade-off |
|---|---|---|
| Zapier, Make, n8n | Simple integrations, no-code | Fast to build, hard to scale |
| Workato, Tray.io, Boomi | Enterprise iPaaS, governance | Expensive, but with audit and SLAs |
| Custom code (Laravel, .NET, Node) | Complex logic, performance-critical | Full control, full responsibility |
| Acumatica Business Events | ERP-native automation | Built-in, no external dependency |
The patterns that work
1. Webhook-first
For event-driven workflows, use webhooks. The source system pushes; the destination listens. Polling is the tax you pay when webhooks are not available.
2. Idempotency
Every event handler must be idempotent. The same event can fire twice (webhook redelivery, retry on timeout). The handler must recognise the second call and skip the work.
import hashlib
from redis import Redis
redis = Redis()
def handle_event(event_id: str, event_body: dict):
# Compute a deterministic key for this event
key = f"event:{hashlib.sha256(event_id.encode()).hexdigest()}"
# Try to claim the event
if not redis.set(key, "processing", nx=True, ex=3600):
# Already claimed — skip
return {"status": "already-processed"}
# Process
do_the_work(event_body)
redis.set(key, "done", ex=86400)
return {"status": "ok"}
3. Saga / compensation
For multi-step workflows (e.g. Acumatica invoice + payment + email), the steps are not atomic. If step 3 fails after step 1 succeeded, you have an inconsistent state. The pattern: each step has a compensation (an undo). The saga runs the steps; if a step fails, the compensations run in reverse.
class InvoiceSaga:
def execute(self, order):
invoice = self.create_invoice(order)
try:
payment = self.create_payment(order, invoice)
except Exception:
self.cancel_invoice(invoice) # compensate
raise
try:
self.send_email(order, invoice, payment)
except Exception:
self.refund_payment(payment) # compensate
self.cancel_invoice(invoice) # compensate
raise
For the broader saga patterns, see the saga pattern guide.
4. Dead-letter queue
For workflows that fail repeatedly (an integration that is down), the events cannot be lost. The pattern: dead-letter queue. Failed events go to a queue (or table) instead of being dropped; a worker replays them after the integration is fixed.
def handle_with_dlq(event):
try:
process(event)
except Exception as e:
attempts = event.get("attempts", 0) + 1
if attempts >= 5:
# Send to dead-letter
dead_letter_queue.push(event, str(e))
else:
# Retry with exponential backoff
delay = 2 ** attempts
retry_queue.push(event, delay=delay, attempts=attempts)
Monitoring the workflow
A workflow that fails silently is worse than a workflow that does not exist. The monitoring:
- Event counts. How many events fired, how many succeeded, how many failed.
- Latency p50/p95/p99. How long from event fire to action completion.
- Dead-letter count. The most important metric. If it is not zero, something is broken.
- Idempotency collision rate. How often the same event is being processed twice.
For the broader monitoring patterns, see the monitoring guide.
Wrapping up
The tools, the patterns, the safety, the monitoring. Get all four right and the workflow runs itself. Skip any one and you are debugging at 2 AM. The discipline is the same as any production system — fail loudly, fail safely, and have a runbook for when the automation breaks.
Wrapping up
That is the working approach I use on Acumatica projects. The same patterns show up whether you are in Nairobi, Johannesburg, Kigali, Lusaka or Harare — and they are the things that keep work moving when an upgrade lands at 6 PM on a Friday. If you are stuck on something specific, reach out or keep reading through the rest of the Acumatica blog.
Independent software engineer in Nairobi specialising in Acumatica customisations, Laravel backends, and tax fiscalisation integrations across East and Southern Africa.