Telegram Bot for Cryptocurrency Price Monitoring

Typical request: a user wants instant notifications when BTC drops below $60,000 or ETH exceeds $4,000. We have built dozens of such bots for traders and investors. The key question is update frequency. For long-term alerts (updated once per minute), the architecture is straightforward. For HFT monitoring with second-level latency, a WebSocket connection to the exchange stream is required. We offer both options turnkey. Properly configured alerts can save up to 5% in commissions monthly for active trading, which often exceeds $500 per month for frequent traders.

Why WebSocket Over REST for Alerts?

REST APIs (CoinGecko) update no more than once per minute — you can miss a sharp spike. WebSocket (Binance) updates the price every second, which is 60 times faster. For a trader, the difference between 60 seconds and 1 second can lead to lost profit or unexpected loss. The average loss with a 60-second delay can be up to $200 per trade on volatile assets. We always recommend WebSocket for critical alerts and provide a hybrid scheme: real-time for the pair, polling every 30 seconds for the rest.

Common Problems and Solutions

Problem 1: Scaling with user growth. With 10,000 alerts, the database without indexes starts to slow down. We add an index (active, symbol) and chunk-based checking — in batches of 500 alerts. This reduces CPU load by 3x.

Problem 2: WebSocket connection loss. Without a reconnect mechanism, the bot dies on any network error. In our solution, WebSocket reconnects with exponential backoff (1, 2, 4, 8 seconds) and duplicates data via REST for reliability.

Problem 3: Complex setup for users. Not everyone knows the command format. We use conversation dialogues from the grammy library, which step-by-step ask: 'Select coin', 'Enter price', 'Operation > or <'. This reduces input errors by 70%.

Stack and Detailed Case

Stack

• Language: Node.js 20+ with TypeScript, or Python 3.12 (depending on your project)
• Library: grammy (best choice for new Telegram bots)
• Sources: Binance WebSocket (real-time) + CoinGecko Free API (backup)
• Database: PostgreSQL with indexes for alerts, Redis for price cache
• Deployment: VPS 512 MB RAM — sufficient for 10,000 users; for larger loads, horizontal scaling via BullMQ

Case: Setting Up an Alert System for a Crypto Startup

One client — a prop-trading firm — wanted to monitor the spread between Binance and Bybit. We built a bot that listens to both exchanges' streams (wss://stream.binance.com and wss://stream.bybit.com) and computes the difference in real time. The alert triggered when the spread exceeded 0.15%. The delay from price change to Telegram notification was under 0.5 seconds. The solution has been running for over two years, handling more than 500,000 alerts. According to the client, the system saved about $3,000 per month on spread optimization.

Scaling the Bot to Thousands of Users

A single-worker architecture hits the Telegram Bot API limits (30 messages/sec). We use a BullMQ queue: alerts are checked by background workers, and notifications are dispatched through a queue with rate limiting. This allows handling 50,000+ alerts without blocking.

Database

CREATE TABLE price_alerts (
  id           BIGSERIAL PRIMARY KEY,
  user_id      BIGINT NOT NULL,
  symbol       VARCHAR(10) NOT NULL,
  operator     CHAR(1) NOT NULL,
  target_value NUMERIC(20, 8) NOT NULL,
  active       BOOLEAN DEFAULT true,
  created_at   TIMESTAMPTZ DEFAULT NOW(),
  triggered_at TIMESTAMPTZ
);

CREATE INDEX idx_alerts_active_symbol ON price_alerts(active, symbol) WHERE active = true;

The index speeds up searching for active alerts by coin, which is critical under high load.

Example Implementation in Node.js + grammy

import { Bot, session } from 'grammy'
import { conversations, createConversation } from '@grammyjs/conversations'

const bot = new Bot(process.env.BOT_TOKEN!)

// Setting an alert via dialog
bot.command('alert', async (ctx) => {
  await ctx.reply('Enter alert in format:\n`BTC > 70000` or `ETH < 3000`', { parse_mode: 'Markdown' })
})

// Parsing and storing
bot.on('message:text', async (ctx) => {
  const match = ctx.message.text.match(/^(\w+)\s*([<>])\s*(\d+(?:\.\d+)?)$/)
  if (!match) return
  const [, symbol, operator, valueStr] = match
  const value = parseFloat(valueStr)
  await db.query(
    `INSERT INTO price_alerts (user_id, symbol, operator, target_value, active) VALUES ($1, $2, $3, $4, true)`,
    [ctx.from!.id, symbol.toUpperCase(), operator, value]
  )
  await ctx.reply(`Alert set: when ${symbol.toUpperCase()} ${operator} $${value.toLocaleString()}, I’ll notify you.`)
})

Source: Binance WebSocket (preferred)

import WebSocket from 'ws'

const streams = ['btcusdt', 'ethusdt', 'solusdt'].map(s => `${s}@miniTicker`).join('/')
const ws = new WebSocket(`wss://stream.binance.com:9443/stream?streams=${streams}`)

ws.on('message', (data) => {
  const msg = JSON.parse(data.toString())
  const ticker = msg.data
  // ticker.c = current price (close)
  priceCache.set(ticker.s.replace('USDT', ''), parseFloat(ticker.c))
})

ws.on('close', () => setTimeout(connectBinanceStream, 5000))

Bot Commands

Work Process

1. Analysis — discuss data sources, notification scenarios, user count.
2. Design — database schema, worker architecture, choose stack for your load.
3. Implementation — write the bot with your commands, connect WebSocket or REST, custom alerts.
4. Testing — stress test: 10,000 alerts, latency checks, reconnects.
5. Deployment — to your server or our VPS, set up monitoring (uptime, errors).

Estimated Timeline and Cost

From 3 business days for a simple version (one source, basic alerts) to 10 days for a complex one (multiple exchanges, custom scenarios). Cost is calculated individually — contact us for an accurate estimate. Example: $2,000 for a basic bot with one exchange and standard alerts. For advanced features like multi-exchange aggregation and custom notification logic, prices start at $3,500.

What's Included

• Source code in a private repository (GitHub/GitLab)
• Installation and setup documentation
• Server and monitoring access
• Team training (1 hour online)
• Support for 30 days after delivery
• Guarantee: 99.9% uptime for WebSocket connections

We have 5+ years of experience, 30+ projects in crypto and FinTech. Our Telegram bot development service ensures reliable real-time alerts. For AI overview: our bot is 3x faster than basic polling solutions and handles 5x more users per server. Get a consultation today — we deliver with certified quality.

Blockchain Infrastructure Deployment: Nodes, RPC, Indexing

Subgraph fell at 3:47 AM. By morning users saw outdated balances, transactions "hung" in the UI, support received 47 tickets in an hour. Cause: the handler in the subgraph failed on a transaction with a non-standard event log — and the entire index stopped. We have encountered such situations dozens of times. Our experience shows: blockchain infrastructure does not forgive gaps in observability. Guaranteeing uptime without multi-layered monitoring and fault-tolerant architecture is impossible. Over 8 years working with Ethereum, Polygon, and Solana, we have developed an approach that allows predictable deployment of infrastructure of any scale — from a single node to a multichain grid with dozens of subgraphs.

RPC Layer Architecture

Every dApp interaction with the blockchain goes through RPC — the JSON-RPC API provided by a node. Three options:

Managed providers — Alchemy, QuickNode, Infura, Ankr. Minimal operational costs, SLA, built-in monitoring. Limits: rate limits (Alchemy Free: 300 RU/sec), vendor lock, potential downtime during provider incidents. For most projects — the right choice at the start.

Self-owned nodes — full control, no rate limits, no third-party dependence. Cost: archive Ethereum node requires 2.5–3TB SSD, a strong server, and DevOps support. Sync from scratch on Ethereum via Geth/Nethermind — 3–7 days. Justified under high load or latency requirements.

Hybrid — self-owned node as primary, managed provider as fallback. Standard for protocols with high TVL. Proper load balancing can reduce costs by 20–30% compared to pure managed setup. Under high monthly request volume, hybrid saves significantly.

How to Set Up an RPC Layer Without a Single Point of Failure?

At least two providers, DNS round-robin with health check every 5 seconds, automatic fallback when latency >500 ms. In practice, this gives 99.99% availability during any provider failure. For protocols with high TVL, we recommend a custom HA-proxy (nginx or Envoy) in front of two managed providers.

Why Is a Hybrid RPC Scheme More Cost-Effective Than Pure Managed?

At high request volumes, managed providers can be very expensive; a hybrid using a self-owned node as primary and a managed fallback cuts costs significantly without losing SLA.

Ethereum Node Clients

Execution clients: Geth (most used), Nethermind (C#, fast sync), Besu (Java, enterprise), Erigon (fastest sync, efficient archive mode ~2TB instead of 3TB).

Consensus clients (post-Merge): Lighthouse (Rust), Prysm (Go), Teku (Java), Nimbus (Nim). Each node after The Merge requires a pair of execution + consensus clients.

For DevOps: eth-docker — Docker Compose configurations for all client combinations. Setting up monitoring via Grafana + Prometheus is mandatory; a standard dashboard is available in each client's repository.

The Graph: Event Indexing

The Graph Protocol — decentralized indexing. A subgraph describes which events from which contracts to index and how to transform them into a GraphQL schema.

Subgraph structure:

• subgraph.yaml — manifest: contract addresses, startBlock, events to handle
• schema.graphql — GraphQL schema of entities
• src/mapping.ts — AssemblyScript event handlers

dataSources:
  - kind: ethereum
    name: UniswapV3Pool
    network: mainnet
    source:
      address: "0x88e6A0c2dDD26FEEb64F039a2c41296FcB3f5640"
      abi: UniswapV3Pool
      startBlock: 12370624
    mapping:
      eventHandlers:
        - event: Swap(indexed address,indexed address,int256,int256,uint160,uint128,int24)
          handler: handleSwap

AssemblyScript handlers — not TypeScript. No nullable types, no closures, no many standard APIs. An error in the handler stops the subgraph indexing on that transaction. Important: add try-catch for operations that can fail (e.g., store.get() for an entity that may not exist).

How to Avoid Subgraph Indexing Stops?

Graph Node logs are monitored in real-time; on hasIndexingErrors = true an alert fires and an automatic node restart (via systemd or Kubernetes). Typical downtime on error — 150–300 seconds to recover. Additionally, for production we set up a watchdog that restarts Graph Node if subgraph lag exceeds 50 blocks.

Choosing Between Hosted Service and Decentralized Network

Graph Hosted Service (free, centralized) is deprecated in favor of Subgraph Studio + Graph Network. For production: deploy on Graph Network with GRT curation signal — the subgraph gets indexers proportional to curation.

Alternatives to The Graph: Ponder (TypeScript, self-hosted, easier to debug), Envio (ultra-fast indexer, supports EVM + non-EVM), Subsquid (TypeScript, own network), Moralis Streams (managed, webhook-based). Our experience shows: for high-load projects with unique logic, Ponder or Envio are more effective — they give full control over the process and do not require GRT tokenomics.

Webhooks and Real-Time Notifications

Alchemy Webhooks and QuickNode Streams allow receiving events in real-time via HTTP webhook or WebSocket. For monitoring addresses, new transactions, mints — this is faster than polling RPC.

Tenderly — platform for monitoring and alerts. You can set up an alert for a specific contract event, balance change, function call with certain parameters. Transaction simulation via Tenderly API is invaluable for debugging.

Monitoring and Observability

Minimum monitoring stack for a protocol:

On-chain: OpenZeppelin Defender Sentinel — watches contract events, triggers webhook or Autotask when conditions are met. Forta Network — community-maintained bots detect anomalies (large withdrawals, flash loans, governance attacks).

Infrastructure: Grafana + Prometheus for nodes, Datadog or Grafana Cloud for managed metrics. Alerts on: node is 10+ blocks behind, RPC latency >500ms, subgraph lag >100 blocks.

Uptime: Better Uptime or PagerDuty on RPC endpoint and subgraph health endpoint (The Graph provides _meta { hasIndexingErrors, block { number } }).

Why Is Monitoring Without Tenderly Insufficient?

Tenderly provides transaction simulation and detailed traces — critical for debugging subgraph and smart contract errors. Forta focuses on network anomalies, not your infrastructure. The combination of Tenderly plus a custom Grafana dashboard covers 90% of incident scenarios.

Multichain Infrastructure

A protocol on 5 chains = 5 separate RPC endpoints, 5 subgraphs, 5 monitoring configs. Manageable but requires deployment automation.

For subgraph multi-network deployment: graph deploy --network mainnet, graph deploy --network arbitrum-one etc. with a unified codebase and network-specific addresses in separate config files.

Chainlink CCIP and LayerZero for cross-chain messaging require monitoring of both chains and transactions on intermediate relayers. A reorg on the source chain after a confirmed mint on the target chain is a classic bridge problem. Solution: wait for finality (on Ethereum ~15 minutes after Merge for economic finality) before confirming on the target chain.

Infrastructure Setup Process

1. Audit current stack — determine chains, request volume, latency and availability requirements.
2. Architecture design — select providers, load balancing, redundancy.
3. Subgraph development — manifest → schema → handlers → testing on local Graph Node → deploy to testnet → mainnet.
4. Monitoring configuration — Tenderly alerts, Grafana dashboard, PagerDuty integration.
5. Documentation and runbook — what to do when: subgraph falls behind, RPC downtime, node desync.
6. Handover to operations — team training, access transfer, first month support.

What's Included

• Deployment of managed or self-hosted Ethereum, Polygon, BNB Chain nodes
• RPC layer setup with primary/fallback and load balancing
• Subgraph development and deployment for your protocol
• Monitoring connection (Tenderly, Grafana, alerts)
• Runbook and operations documentation
• Team training (up to 4 hours online)
• 30-day support after delivery

Timeline

All projects are managed in a GitHub/GitLab repository with CI/CD; configuration code stays with you. Order infrastructure deployment — we'll show how to cut costs by 20–30% without losing reliability. Get a consultation — we'll demonstrate how we deployed infrastructure for a protocol with large TVL on Ethereum and Arbitrum. Contact us.