Custom Make Scenarios for Complex Automation

Custom Make Scenarios: When Standard Modules Fall Short

The standard Make module is easy to set up in minutes, but when you need to process an array of hundreds of orders, call multiple APIs in a specific sequence, handle errors, and preserve state between runs—a single trigger and action won't suffice. For instance, one of our clients spent 2 hours daily manually exporting orders from WooCommerce to 1C. After implementing a custom scenario, the time dropped to 10 minutes, and errors virtually disappeared. This resulted in significant savings by reallocating resources. If you need a similar result, contact us—we will develop a scenario tailored to your business logic.

Problems We Solve with Custom Scenarios

Custom scenarios go beyond simple trigger → action: they include data transformation, conditional logic, multiple API calls, array iteration, and error handling. Here are typical complex tasks:

• Array operations: For example, summing the cost of all items in an order and applying a discount. Built-in functions like map, sum, and filter handle this.
• Error handling: If an API returns 500, the scenario should retry after one minute. We configure a router based on response statuses and send a Telegram notification.
• Non-module API calls: For a custom API, we set up an HTTP module with OAuth2, Basic Auth, or API key.

Error handling is built as follows: the router checks the HTTP response status. If it's 429 (Too Many Requests), the scenario waits 60 seconds and retries. If it's 5xx, it logs the error to Data Store and sends a Telegram notification. This prevents data loss and simplifies monitoring.

Why Standard Make Modules Fall Short for Complex Logic

Standard modules are designed for simple chains: get data → process → send. When you need to combine data from multiple sources, apply complex filters, or perform transactional operations with rollback on error, custom logic is necessary. Custom scenarios enable arbitrary business logic: branching, loops, waits, and external service calls with authorization.

How to Automate WooCommerce to 1C Order Synchronization

Task: synchronize new orders from WooCommerce to 1C via REST API every hour, with error notifications in Telegram. The scenario includes:

[Schedule: every hour]
         |
[WooCommerce: Get Orders
 status=processing
 after={{addHours(now; -1)}}]
         |
[Router]
    ├── [Filter: order_count > 0]
    │         |
    │   [Iterator: for each order]
    │         |
    │   [HTTP POST: 1C API
    │    /api/orders/create]
    │         |
    │   [Router: by response status]
    │      ├── [201: update WooCommerce
    │      |   meta _synced_to_1c = true]
    │      └── [Error: Telegram
    │          orderId + error message]
    │
    └── [Filter: order_count == 0]
              |
        [ignore]

This custom Make scenario processes orders three times faster than manual export and reduces errors by 90%. Time savings allow reallocating resources to more critical tasks. Order development of such a scenario—we will configure the integration for your systems.

Transforming Data with Make Functions

Make has a built-in functional language for transformations. Here are the key tools:

# Strings
{{upper(1.name)}}                           → "IVAN"
{{substring(1.email; 0; indexOf(1.email; "@"))}}  → "ivan"
{{replace(1.phone; " "; "")}}              → "+79001234567"

# Numbers
{{round(1.price * 1.19; 2)}}               → 1190.00 (with 19% VAT)
{{formatNumber(1.total; 2; "."; " ")}}     → "1 234 567.89"

# Dates
{{formatDate(now; "DD.MM.YYYY HH:mm")}}    → "28.03.2026 14:30"
{{addDays(1.created_at; 30)}}              → date + 30 days

# Arrays
{{length(1.items)}}                        → 5
{{map(1.items; "product_id")}}             → [1, 2, 3, 4, 5]
{{sum(map(1.items; "price"))}}             → sum of prices

What If an API Doesn't Have a Ready Module?

For APIs without a built-in module, we use a custom HTTP request with authorization. Example OAuth 2.0 configuration per the OAuth 2.0 specification:

{
  "type": "oauth2",
  "clientId": "{{connection.clientId}}",
  "clientSecret": "{{connection.clientSecret}}",
  "authorizeUrl": "https://api.example.com/oauth/authorize",
  "accessTokenUrl": "https://api.example.com/oauth/token",
  "scope": "read write",
  "tokenPlacement": "header",
  "tokenHeaderName": "Authorization",
  "tokenHeaderPrefix": "Bearer "
}

Working with JSON and XML

// Parse JSON in scenario's Data Store
// Incoming text: '{"orders": [{"id": 1}, {"id": 2}]}'

// Use Make's parseJSON function
{{parseJSON(1.response_body).orders}}

// For XML — use XML → JSON module
// Then work as with an object
{{2.root.order[].id}}

Handling Rate Limits in Make

If an API returns 429 Too Many Requests, the scenario waits and retries:

[HTTP Request]
     |
[Router: status 429]
     |
[Sleep: 60 seconds]  ←── (built-in wait module)
     |
[HTTP Request]      ←── retry

What's Included in Our Work

We provide the full cycle: requirements analysis, scenario design, implementation with modular testing, documentation, team training, and one month of post-release support. Step-by-step process:

1. Requirements analysis: we study your business logic and integrations.
2. Scenario design: we create a schema with routers and error handling.
3. Implementation and testing: we write the scenario and test with sample data.
4. Documentation and training: we prepare instructions and train your staff.
5. Support: one month of free maintenance.

Timelines and Pricing

An average custom scenario (10–15 modules) takes 2–4 days. A complex one with Data Store, multiple APIs, and error handling takes one week. Pricing is determined individually—we evaluate the project after a briefing. Our engineers have many years of automation experience in Make. We guarantee stable scenario operation and provide support. If you need a reliable custom scenario, contact us. Get a consultation and precise estimate.

Backend Development Services: Laravel, Node.js, Go, Django, PostgreSQL

On a production server at 3:14 AM, the Laravel Jobs queue stopped processing. 40,000 unprocessed jobs in Redis. Cause: worker crashed due to a memory leak in one of the Jobs (leak via a static variable in an Eloquent observer), supervisor didn't restart it because of misconfigured stopwaitsecs. This is not a hypothetical scenario — it's Tuesday. We analyzed such an incident on a project with 500 RPS load: diagnosis took 4 hours, fix — 20 minutes. So you don't lose money on downtime, we offer backend development services with a focus on production-grade reliability. We'll assess your project in 2 days.

Backend is what works when no one is watching. Or doesn't work. We guarantee you'll have the first option.

How do we ensure production-grade reliability from day one?

What we do correctly from day one

Service Layer over Fat Controllers. Controller receives HTTP request, validates it via Form Request, passes data to Service, returns response. Business logic in Service, not Controller. This sounds trivial, but most legacy projects have controllers with 500 lines and SQL queries inside.

Repository Pattern we use cautiously. If you just wrap Model::where(...) in a repository method — that's boilerplate without benefit. Repository is justified when: you need to abstract from the data source (DB + cache + external API) or when query logic is complex enough to isolate.

Jobs, Events, Listeners. Everything that can be async — make async. Sending email, PDF generation, external API sync, aggregate recalculation — into Queue. Laravel Horizon for queue monitoring in Redis: see throughput, failed jobs, processing time per queue.

How Octane handles high load

Laravel Octane with RoadRunner or Swoole keeps the app in memory between requests — removes bootstrap overhead (config loading, class autoloading) on each HTTP request. Gain: 3–8x on synthetic benchmarks, 2–4x on real applications. Important: no state between requests in static variables — that leads to exactly the incidents from the beginning. We use this in projects with >1000 RPS.

What to do about N+1 queries

N+1 is the most common cause of slow pages in Laravel apps. Standard story: page worked fine on dev with 10 records, on production with 10,000 — 8-second load.

Laravel Debugbar in dev environment shows the number of queries per page. More than 20 queries per page — signal for audit.

Model::preventLazyLoading(! app()->isProduction());

Telescope for profiling in staging: logs all queries, jobs, mail, notifications with time detail. Numbers: after implementing eager loading, page load time drops from 8s to 0.3s — 27 times faster.

PostgreSQL: indexes that are actually needed

PostgreSQL 14+ is the primary DB on all projects. We use PgBouncer + PostgreSQL combination. 10+ years experience, more than 50 backend projects, 5 years on the market.

How PostgreSQL helps avoid slow queries

Composite indexes for frequent WHERE + ORDER BY. If you have WHERE user_id = ? AND status = ? ORDER BY created_at DESC — you need (user_id, status, created_at DESC). A separate index on (user_id) doesn't help much with sorting.

Partial indexes. If 95% of queries go with WHERE status = 'active':

CREATE INDEX idx_orders_active ON orders (created_at DESC)
WHERE status = 'active';

The index is small, fast, covers the main load.

GIN indexes for JSONB and arrays. @> operator without GIN index — seq scan. With index — fast even on millions of rows.

GIN for full-text search. to_tsvector + GIN instead of LIKE '%query%'. LIKE without index is always seq scan. With pg_trgm extension and gin_trgm_ops — supports LIKE with index, useful for CRM search by partial match.

Connection pooling: why it's more important than it seems

Rails, Laravel, Django open a new connection to PostgreSQL for each PHP/Python process. With 100 workers — 100 connections. PostgreSQL starts degrading from 200–300 active connections — overhead on connection management becomes significant.

PgBouncer — connection pooler in front of PostgreSQL. Transaction pooling mode: connection to PostgreSQL is occupied only during a transaction, returned to pool between requests. 1000 application workers → 20–50 actual connections to PostgreSQL. This reduces latency by 40% and hosting costs by 30%.

Node.js with Fastify: when it's better than Laravel

Node.js is justified for:

• Realtime: WebSocket servers, Server-Sent Events, chat, live updates
• Streaming: large files, video, streaming data
• High I/O concurrency: many parallel requests to external APIs without heavy business logic
• Serverless: Lambda/Cloud Functions — Node.js starts faster than PHP

Fastify over Express: 2–3 times faster on benchmarks, built-in JSON Schema validation, better TypeScript support, plugin architecture.

Typical realtime architecture: Laravel — core business logic and REST API. Node.js + Socket.io or ws — WebSocket server. Laravel publishes events to Redis Pub/Sub, Node.js subscribes and broadcasts to clients. This separation allows scaling the WebSocket server independently of the main app.

Go: microservices and high load

Go we use for:

• High-load microservices (>10,000 RPS)
• Background workers with strict latency requirements
• DevOps tools and CLI
• gRPC services in microservice architecture

Goroutines — thousands of times cheaper than OS threads. 10,000 concurrent connections on Go is normal on one server.

But Go is not a silver bullet. Development is slower than Laravel: more boilerplate, no ORM at Eloquent level, error handling with if err != nil everywhere. Justified only when performance is a real requirement, not an assumption.

Django and Python backend

Django with DRF (Django REST Framework) — for tasks where Python is needed: ML pipelines, data processing, integrations with AI tools.

Celery for background tasks — similar to Laravel Queue but more complex to configure. Celery Beat for cron tasks.

Django ORM vs raw SQL: ORM is convenient for CRUD. For analytical queries with multiple JOINs, window functions, and CTEs — connection.execute() with raw SQL is more readable and predictable.

Redis: not just cache

Redis in our projects plays multiple roles:

Redis Cluster for horizontal scaling. Sentinel for automatic failover on standalone setups.

Deployment and infrastructure

Docker + docker-compose — standard for local development and production. Each service in a container: PHP-FPM/Octane, Nginx, PostgreSQL, Redis, Queue Worker, Scheduler.

CI/CD via GitHub Actions:

1. Run tests (PHPUnit / Pest, Vitest, Playwright)
2. Build Docker image
3. Push to Container Registry
4. Deploy: docker pull → docker-compose up -d on server, or Kubernetes rolling update

Zero-downtime deploy for Laravel: php artisan down --secret=TOKEN is not needed with proper configuration. Strategy: new container starts next to the old one, Nginx switches traffic after health check, old container stops.

Monitoring: Sentry for exception tracking with alerting in Slack/Telegram. Grafana + Prometheus (or Grafana Cloud) for metrics: CPU, memory, request rate, queue depth, database connection count. Alerts on: error rate > 1%, p99 latency > 2s, queue depth > 1000 jobs.

What's included in turnkey work

• Architecture design (API documentation, DB schema, service diagram)
• Implementation according to agreed specification with code review
• CI/CD, monitoring, alerting setup
• Load testing (k6, wrk) with report
• Handover of source code, access, deployment instructions
• Training of customer's team (2-3 sessions)
• Warranty support for 1 month after delivery

Timeline benchmarks

Pricing is calculated individually after analyzing load, integrations, and business logic. Contact us for a free audit of your current backend — get an optimization plan in 2 days. Request a consultation.