How to Develop a Mempool Monitoring Bot for Ethereum and L2

Build a Custom Mempool Monitoring Bot for Ethereum and L2

In the Ethereum public mempool, eth_subscribe("newPendingTransactions") reveals only a small fraction of transactions. Private transactions from Flashbots and MEV Blocker remain invisible. For a DeFi protocol dependent on liquidations or gas analytics, this is a blind spot. A custom mempool bot with access to the txpool API gives the full picture: it sees 90–100% of pending transactions, including those sent via private channels. We design such bots turnkey — from node selection to deployment with a metrics dashboard.

Own Node vs. Public RPC

Public RPC via eth_subscribe("newPendingTransactions") shows only broadcast transactions — private ones (Flashbots, MEV Blocker) are not visible. Running your own Geth node with txpool API provides a complete snapshot: txpool_content displays all pending and queued transactions passing through your node. For latency-critical tasks, colocation with major validators (Equinix, Amsterdam) reduces latency to 10–50 ms versus 200 ms on public RPC — that is a 4x improvement. Our colocation setup reduces latency by 4x compared to public RPC.

An own node sees 3x more transactions than public RPC. For a bot monitoring liquidations, this is the difference between a profitable trade and a missed opportunity.

How to Decode Transactions in Real Time?

A raw transaction is bytes. To understand what it does, decode the calldata via ABI. For well-known protocols (Uniswap, Aave, Curve), we use preloaded interfaces. For unknown ones, we query 4byte.directory: send the selector (first 4 bytes) and get the function signature. Typical decoding code for Uniswap V3 exactInputSingle:

const uniV3Iface = new Interface(UNISWAP_V3_ABI);
function decodeUniswapTx(tx: ethers.TransactionResponse): DecodedSwap | null {
  if (!tx.data || tx.data === '0x') return null;
  const selector = tx.data.slice(0, 10);
  if (selector === '0x414bf389') {
    const decoded = uniV3Iface.decodeFunctionData('exactInputSingle', tx.data);
    return { tokenIn: decoded.params.tokenIn, tokenOut: decoded.params.tokenOut, amountIn: decoded.params.amountIn };
  }
  return null;
}

Which Scenarios Bring the Most Profit?

Different tasks require different levels of mempool access. Compare them by latency and complexity:

Liquidation bot. Monitor positions on Aave/Compound; catch Chainlink price update transactions in the mempool. Decode the new price, simulate liquidation via local eth_call. If found, send a liquidation with increased maxFeePerGas to beat the oracle. Average gas savings: 30% due to priority queue. Typical gas savings: $50–$100 per liquidation compared to standard gas.

Sandwich detection. Parse pending transactions for DEX swaps. If two transactions target the same pool—first with high gas (frontrun), second victim—the system alerts the operator or automatically blocks the protocol. Implemented via a map of pending hash to swap details.

Gas price forecasting. Take a txpool_content snapshot, analyze maxFeePerGas distribution. Compute p50, p75, p95 — this predicts the next base fee within 15% accuracy. Used to send non-urgent transactions at optimal gas prices.

What's Included?

• Architecture: design of a high-load system (Redis Streams + Worker Pool + Execution Engine).
• Development: decoding modules, filters (by address, signature, gas), alerting system.
• Deployment: configure own node (Geth/Reth) with optimal peering, latency monitoring.
• Documentation: API description, run instructions, metrics dashboard.
• Support: 14 days post-launch for adjustments.

Detailed Work Plan:

1. Analysis (2 days): discuss the task — liquidations, analytics, anti-sandwich, MEV. Define SLA for latency, transaction volume.
2. Design (3 days): choose stack (Geth/Reth, Foundry, ethers.js, Redis), draw queue architecture.
3. Implementation (5–15 days): write decoding modules, filters, execution engine. End-to-end testing on shadow node.
4. Test (3 days): simulate load of 300+ tx/s, measure latency, catch regressions.
5. Deployment (2 days): node setup, monitoring, documentation.

Our engineers have 6+ years in blockchain development. We have completed 27+ projects on MEV, mempool analysis, and decentralized protocols. We guarantee transparency: all code undergoes internal audit and formal verification (Slither, Mythril).

Process and Timelines

Final timeline: from 2 to 8 weeks depending on complexity. Cost is determined individually after a task audit. Own node setup costs around $500/month for a colocated server. Request a consultation — we assess the scope of work for free.

Sources

• Ethereum Mempool — official documentation.
• Flashbots MEV-Boost — MEV-Boost specification.

Get a detailed proposal for your scenario — contact us.

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.