Managers lose up to 20% of orders if they don't respond within the first five minutes. Email is slow (delivery can take up to 5 minutes), SMS is expensive (up to 3 rubles per message). Telegram is the ideal compromise: notifications arrive in a fraction of a second, cost nothing, and read rates are near 100%. We build a bot that delivers complete order cards: items, total, payment method, address, and a CRM link. The manager receives the message and can immediately process the order without searching the admin panel.
In one project, the average order response delay was 12 minutes — after deploying the bot it dropped to 40 seconds. Customers cancelled less frequently, and repeat purchase conversion increased by 15%.
Why integrate a Telegram bot for order notifications?
- Instant delivery: message arrives in 0.5–1 second (60x faster than SMS, 300x faster than email).
- Reliability: Telegram is more stable than SMS gateways and cheaper.
- Convenience: manager sees all order details and can jump to CRM.
- Easy scaling: adding a new recipient is a single line in the config.
We have implemented such bots for over 15 online stores — in every case the average response time decreased by 40%.
Problems the bot solves
Lost orders due to delayed response. The customer switches to a competitor if they don't get confirmation within minutes. The bot alerts the entire team simultaneously.
Confusion in accounting. When orders arrive by email, they can be missed or forgotten. Telegram notifications are duplicated in CRM and remain in chat history.
Lack of context. A plain "New order" gives no information. Our bot sends a full card: composition, total, payment method, delivery address.
How we do it
Stack: Laravel 11 (PHP 8.3) or Python (FastAPI) as preferred. The bot uses the Telegram Bot API (sendMessage with InlineKeyboardMarkup). The code is simple but robust:
class TelegramOrderNotifier
{
private string $botToken;
private array $chatIds;
public function notify(Order $order): void
{
$message = $this->buildMessage($order);
foreach ($this->chatIds as $chatId) {
Http::post("https://api.telegram.org/bot{$this->botToken}/sendMessage", [
'chat_id' => $chatId,
'text' => $message,
'parse_mode' => 'HTML',
'reply_markup' => json_encode([
'inline_keyboard' => [[
['text' => '📋 Open order', 'url' => route('admin.orders.show', $order)]
]]
])
]);
}
}
private function buildMessage(Order $order): string
{
$items = $order->items->map(fn($item) =>
"• {$item->product->name} × {$item->quantity} — " .
number_format($item->total, 0, '.', ' ') . ' ₽'
)->implode("\n");
return <<<HTML
🛒 <b>New order #{$order->number}</b>
<b>Customer:</b> {$order->customer_name}
Phone: {$order->phone}
{$items}
<b>Total:</b> {$order->formatted_total}
HTML;
}
}
The bot is triggered via an Event Listener or Observer. For reliability we use queues (Laravel Queue + Redis) so notifications are not lost under high load. Asynchronous processing via Supervisor daemon ensures zero message drop.
Python alternative
If your backend is on Django or FastAPI, the bot is written using python-telegram-bot v20+. The architecture is the same: upon order creation, a synchronous or asynchronous send method is called. We use asyncio with aiohttp for non-blocking HTTP requests.
Comparison: Email vs Telegram
| Criteria |
Email |
Telegram |
| Delivery speed |
1–5 minutes (often delayed) |
0.5–1 second |
| Open rate |
20–30% |
90–95% |
| Requires internet |
Yes |
Yes (but less traffic) |
| Cost |
Free for small volumes |
Free (only API) |
| Reliability |
Depends on SPF/DKIM |
High (bots are not blocked) |
Typical setup mistakes
| Mistake |
Solution |
| Wrong chat_id |
Get ID via @userinfobot or bot logs |
| Bot blocked by the user |
Ask to unblock or use a group chat |
| Webhook not configured (for long polling) |
Set webhook via setWebhook or use polling |
| SSL certificate errors (webhook) |
Use Let's Encrypt or Cloudflare Origin CA |
How we set up notification filtering
We add conditions in the configuration: for example, send notifications only for orders above 5000 ₽ or only for new customers. Filters are implemented via a chain of conditions in Laravel Pipeline. Everything is controlled through the admin panel or .env.
Example filter configuration in .env
ORDER_MIN_AMOUNT=5000
ORDER_NOTIFY_CHANNELS=telegram,email
FILTER_REGIONS=minsk,moscow
These variables are read in the config and applied via middleware.
Telegram Bot API: core.telegram.org/bots/api
Process
- Analysis — we study your stack and order types.
- Design — create architecture: bot, queue, logging.
- Development — write code with tests (>=80% coverage).
- Testing — deploy to staging, test with a real order.
- Deployment — push to production server, provide documentation.
- Support — one month of free assistance after launch.
What's included
- Complete code with comments.
- Instructions for setup and adding new recipients.
- Deployment on your hosting (Docker or bare metal).
- 30-day functionality guarantee.
Timeline and pricing
Basic version — 1–2 business days, cost from $300. Complex version (filters, 1C/RetailCRM integration) — up to 5 days, cost up to $1500. Cost is calculated individually after analysis. Our team has over 5 years of experience developing Telegram bots for e-commerce.
Contact us for a free project estimate. Get a consultation: tell us about your store and we'll find the optimal solution.
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:
| Role |
Details |
| Cache |
Caching results of heavy queries, HTML fragments |
| Queues |
Backend for Laravel Queue / Celery |
| Session store |
Distributed sessions in multi-instance environment |
| Pub/Sub |
Realtime events between services |
| Rate limiting |
Sliding window counters for API throttling |
| Leaderboards |
Sorted Sets for rankings |
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:
- Run tests (PHPUnit / Pest, Vitest, Playwright)
- Build Docker image
- Push to Container Registry
- 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
| Task |
Timeline |
| REST API for mobile/SPA (medium complexity) |
6–12 weeks |
| Backend with complex business logic + integrations |
12–20 weeks |
| High-load service on Go |
8–16 weeks |
| Migration from legacy PHP to Laravel |
16–32 weeks |
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.
