The Graph subgraph development: design, deployment, and optimization

We often encounter a problem: smart contracts don't store state history in a query-friendly way. eth_getLogs with event filtering is a blunt tool — no sorting, no aggregation, no relationships between events across different contracts. As a result, the frontend either pulls tons of data and processes it client-side, or the team spins up its own indexing backend. The Graph solves this in a standard way: you describe what to index, and the network does it for you. Our team has developed over 20 subgraphs for DeFi protocols and NFT marketplaces, accumulating experience in optimization and debugging. Contact us for a consultation on your project — we'll help design the schema and choose the stack.

A subgraph is essentially a declaration: which contracts to listen to, which events to process, how to transform data into entities. Writing it correctly the first time is harder than it seems.

Optimizing schema for GraphQL queries

The schema should be designed based on what queries the frontend needs — not on the structure of contract events. A typical mistake: making entities one-to-one with events, which leads to N+1 queries on the frontend. Denormalized entities with pre-aggregated data reduce query count by 3–5 times.

The right approach — denormalized entities with pre-aggregated data:

type Pool @entity {
  id: ID!                        # pool address
  token0: Token!
  token1: Token!
  feeTier: BigInt!
  totalVolumeUSD: BigDecimal!    # cumulative volume — updated on each Swap
  totalValueLockedUSD: BigDecimal!
  txCount: BigInt!
  swaps: [Swap!]! @derivedFrom(field: "pool")
}

type Swap @entity {
  id: ID!                        # txHash + logIndex
  pool: Pool!
  sender: Bytes!
  recipient: Bytes!
  amount0: BigDecimal!
  amount1: BigDecimal!
  amountUSD: BigDecimal!
  timestamp: BigInt!
  blockNumber: BigInt!
}

@derivedFrom is a virtual relationship — it doesn't store an array of IDs in the Pool record. This is important for performance: a pool with thousands of swaps won't grow in record size. Example query the frontend can run:

{
  pools(first: 10) {
    id
    totalVolumeUSD
    swaps(first: 5) {
      amountUSD
      timestamp
    }
  }
}

Why AssemblyScript is dangerous for TypeScript developers?

AssemblyScript is a strictly typed language that compiles to WebAssembly. TypeScript habits are dangerous here:

// WRONG — null reference in AS causes panic
let pool = Pool.load(event.address.toHexString())
pool.txCount = pool.txCount.plus(BigInt.fromI32(1)) // pool may be null

// RIGHT
let poolId = event.address.toHexString()
let pool = Pool.load(poolId)
if (pool === null) {
  pool = new Pool(poolId)
  pool.txCount = BigInt.fromI32(0)
  pool.totalVolumeUSD = BigDecimal.fromString("0")
}
pool.txCount = pool.txCount.plus(BigInt.fromI32(1))
pool.save()

BigDecimal for financial values is mandatory. BigInt from the contract must be converted considering token decimals:

function convertTokenToDecimal(tokenAmount: BigInt, exchangeDecimals: BigInt): BigDecimal {
  if (exchangeDecimals == BigInt.fromI32(0)) {
    return tokenAmount.toBigDecimal()
  }
  return tokenAmount.toBigDecimal().div(
    BigInt.fromI32(10).pow(exchangeDecimals.toI32() as u8).toBigDecimal()
  )
}

How to debug slow synchronization?

If a subgraph syncs slower than expected, run through this checklist:

1. Count the number of callHandlers — replace with eventHandlers where possible. eventHandlers are 5–10 times faster.
2. Ensure startBlock is not too early. Ideally, it's the deployment block of the contract.
3. Check the number of eth_call in handlers — each contract call from a mapping adds an RPC request.
4. Use ipfs.cat minimally — it's a slow operation.

Typical mistakes in handlers:

• Forgetting to check for null before Pool.load
• Setting startBlock = 0
• Using callHandlers instead of eventHandlers where the opposite is possible
• Not converting BigInt to BigDecimal with decimals accounted for

How to choose between Hosted Service and Decentralized Network?

For production protocols, we recommend the decentralized network: it provides censorship resistance and resistance to shutdown. Hosted Service is free but only suitable for development and testing. Comparison:

For deployment to the decentralized network, use Graph Studio:

graph auth --studio <deploy-key>
graph codegen && graph build
graph deploy --studio <subgraph-name>

More about the architecture can be found in the The Graph documentation. Contact us for consultation on network selection and schema optimization.

Subgraph development process: stages and timelines

We work according to the following plan:

1. Analysis of contract ABIs and identification of events and calls to index.
2. GraphQL schema design tailored to frontend queries (with emphasis on denormalization).
3. Writing AssemblyScript handlers with null handling, BigInt conversion, and performance optimization.
4. Local testing using graph-cli and debugging slow spots.
5. Deployment to the chosen network and synchronization monitoring setup.

Timelines depend on contract complexity and number of entities: from 3 to 10 working days. Cost is calculated individually after analyzing your project.

What is included in our subgraph development work

• Analysis of contract ABIs and identification of needed events/calls
• Schema design for specific frontend queries
• Writing and testing AssemblyScript handlers
• Performance optimization (saving up to 40% on RPC calls through denormalization)
• Deployment and synchronization monitoring
• Documentation of GraphQL endpoints and example queries

Our team has extensive experience in blockchain development, with over 30 successful projects on Ethereum, Polygon, BNB Chain, Solana. Order subgraph development from professionals and get fast indexing without compromises.

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.