Alchemy performance tuning
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What its author says it does
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'Optimize Alchemy SDK performance with caching, batching, and multi-chain parallelism.
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SKILL.md
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Alchemy Performance Tuning
Performance Targets
| Operation | Target Latency | CU Cost |
|---|---|---|
getBlockNumber | < 50ms | 10 |
getBalance | < 100ms | 19 |
getTokenBalances | < 200ms | 50 |
getNftsForOwner | < 300ms | 50 |
getAssetTransfers | < 500ms | 150 |
| Multi-chain portfolio | < 2s | ~400 |
Instructions
Step 1: Response Caching with TTL
// src/performance/cache.ts
import { Alchemy, Network } from 'alchemy-sdk';
class BlockchainCache {
private store = new Map<string, { data: any; expiry: number }>();
// Different TTLs for different data freshness needs
private TTL: Record<string, number> = {
blockNumber: 12000, // 12s (~1 block)
balance: 30000, // 30s
tokenBalances: 60000, // 60s
nftOwnership: 300000, // 5 min (NFTs transfer less frequently)
contractMetadata: 3600000, // 1 hour (rarely changes)
tokenMetadata: 86400000, // 24 hours (almost never changes)
};
async cached<T>(category: string, key: string, fetcher: () => Promise<T>): Promise<T> {
const cacheKey = `${category}:${key}`;
const entry = this.store.get(cacheKey);
if (entry && entry.expiry > Date.now()) return entry.data;
const data = await fetcher();
this.store.set(cacheKey, { data, expiry: Date.now() + (this.TTL[category] || 30000) });
return data;
}
invalidate(category: string): void {
for (const key of this.store.keys()) {
if (key.startsWith(`${category}:`)) this.store.delete(key);
}
}
}
const cache = new BlockchainCache();
export { cache };
Step 2: Parallel Multi-Chain Fetching
// src/performance/parallel-fetch.ts
import { Alchemy, Network } from 'alchemy-sdk';
import { cache } from './cache';
const CHAINS = [
{ name: 'ethereum', network: Network.ETH_MAINNET },
{ name: 'polygon', network: Network.MATIC_MAINNET },
{ name: 'arbitrum', network: Network.ARB_MAINNET },
{ name: 'base', network: Network.BASE_MAINNET },
];
async function multiChainBalance(address: string) {
const results = await Promise.allSettled(
CHAINS.map(chain =>
cache.cached('balance', `${chain.name}:${address}`, async () => {
const client = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: chain.network });
const bal = await client.core.getBalance(address);
return { chain: chain.name, balance: (parseInt(bal.toString()) / 1e18).toFixed(6) };
})
)
);
return results
.filter((r): r is PromiseFulfilledResult<any> => r.status === 'fulfilled')
.map(r => r.value);
}
Step 3: Batch NFT Metadata (Reduce CU)
// src/performance/batch-nft.ts
import { Alchemy, Network } from 'alchemy-sdk';
const alchemy = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: Network.ETH_MAINNET });
// SLOW: Individual calls = 50 CU each
// async function slowGetMetadata(tokens) {
// return Promise.all(tokens.map(t => alchemy.nft.getNftMetadata(t.contract, t.tokenId)));
// }
// FAST: Batch call = 50 CU total for up to 100 tokens
async function fastGetMetadata(tokens: Array<{ contractAddress: string; tokenId: string }>) {
return alchemy.nft.getNftMetadataBatch(tokens);
}
Step 4: WebSocket for Real-Time Data
// src/performance/realtime.ts
import { Alchemy, AlchemySubscription, Network } from 'alchemy-sdk';
const alchemy = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: Network.ETH_MAINNET });
// Use WebSocket subscriptions instead of polling
function watchAddress(address: string, onActivity: (tx: any) => void) {
alchemy.ws.on(
{
method: AlchemySubscription.PENDING_TRANSACTIONS,
toAddress: address,
},
(tx) => onActivity(tx)
);
}
// Auto-reconnect on disconnect
alchemy.ws.on('close', () => {
console.log('WebSocket disconnected — reconnecting in 5s');
setTimeout(() => alchemy.ws.connect(), 5000);
});
Output
- TTL-based response cache matching data freshness requirements
- Parallel multi-chain fetching (4 chains in < 2s)
- Batch NFT metadata (100x CU reduction)
- WebSocket subscriptions replacing polling
Resources
- Alchemy Compute Units
- Alchemy WebSockets
Next Steps
For cost optimization, see alchemy-cost-tuning.