Documenso Performance Tuning
Overview
Optimize Documenso integrations for speed and efficiency. Key strategies: reduce API round-trips with templates, cache document metadata, batch operations with concurrency control, and use async processing for bulk signing workflows.
Prerequisites
- Working Documenso integration
- Redis or in-memory cache (recommended)
- Completed
documenso-sdk-patternssetup
Instructions
Step 1: Reduce API Calls with Templates
The biggest performance win: templates reduce a multi-step document creation (create + upload + add recipients + add fields + send = 5+ calls) to just 2 calls (create from template + send).
// WITHOUT templates: 5+ API calls per document
async function createDocumentManual(signer: { email: string; name: string }) {
const doc = await client.documents.createV0({ title: "Contract" }); // 1
await client.documents.setFileV0(doc.documentId, { file: pdfBlob }); // 2
const recip = await client.documentsRecipients.createV0(doc.documentId, { // 3
email: signer.email, name: signer.name, role: "SIGNER",
});
await client.documentsFields.createV0(doc.documentId, { // 4
recipientId: recip.recipientId, type: "SIGNATURE",
pageNumber: 1, pageX: 10, pageY: 80, pageWidth: 30, pageHeight: 5,
});
await client.documents.sendV0(doc.documentId); // 5
}
// WITH templates: 2 API calls per document
async function createDocumentFromTemplate(templateId: number, signer: { email: string; name: string }) {
const res = await fetch( // 1
`${BASE}/templates/${templateId}/create-document`,
{
method: "POST",
headers: { Authorization: `Bearer ${API_KEY}`, "Content-Type": "application/json" },
body: JSON.stringify({
title: `Contract — ${signer.name}`,
recipients: [{ email: signer.email, name: signer.name, role: "SIGNER" }],
}),
}
);
const doc = await res.json();
await fetch(`${BASE}/documents/${doc.documentId}/send`, { // 2
method: "POST",
headers: { Authorization: `Bearer ${API_KEY}` },
});
}
Step 2: Cache Document Metadata
// src/cache/documenso-cache.ts
import NodeCache from "node-cache";
const cache = new NodeCache({ stdTTL: 300, checkperiod: 60 }); // 5 min TTL
export async function getCachedDocument(client: Documenso, documentId: number) {
const key = `doc:${documentId}`;
const cached = cache.get(key);
if (cached) return cached;
const doc = await client.documents.getV0(documentId);
// Only cache completed documents (immutable)
if (doc.status === "COMPLETED") {
cache.set(key, doc, 3600); // 1 hour for completed
} else {
cache.set(key, doc, 30); // 30 seconds for in-progress
}
return doc;
}
// Invalidate on webhook events
export function invalidateDocument(documentId: number) {
cache.del(`doc:${documentId}`);
}
Step 3: Batch Operations with Concurrency Control
// src/batch/documenso-batch.ts
import PQueue from "p-queue";
const queue = new PQueue({
concurrency: 5, // Max 5 concurrent API calls
interval: 1000, // Per second window
intervalCap: 10, // Max 10 per second
});
export async function batchCreateDocuments(
client: Documenso,
templateId: number,
signers: Array<{ email: string; name: string; company: string }>
): Promise<Array<{ email: string; documentId?: number; error?: string }>> {
const results = await Promise.allSettled(
signers.map((signer) =>
queue.add(async () => {
const res = await fetch(
`https://app.documenso.com/api/v1/templates/${templateId}/create-document`,
{
method: "POST",
headers: {
Authorization: `Bearer ${process.env.DOCUMENSO_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
title: `Agreement — ${signer.company}`,
recipients: [{ email: signer.email, name: signer.name, role: "SIGNER" }],
}),
}
);
if (!res.ok) throw new Error(`HTTP ${res.status}`);
const doc = await res.json();
// Send immediately
await fetch(
`https://app.documenso.com/api/v1/documents/${doc.documentId}/send`,
{
method: "POST",
headers: { Authorization: `Bearer ${process.env.DOCUMENSO_API_KEY}` },
}
);
return { email: signer.email, documentId: doc.documentId };
})
)
);
return results.map((r, i) => {
if (r.status === "fulfilled") return r.value as any;
return { email: signers[i].email, error: (r.reason as Error).message };
});
}
Step 4: Async Processing with Background Jobs
// src/jobs/signing-queue.ts
import Bull from "bull";
const signingQueue = new Bull("documenso-signing", process.env.REDIS_URL!);
// Producer: queue signing requests
export async function queueSigningRequest(data: {
templateId: number;
signerEmail: string;
signerName: string;
}) {
const job = await signingQueue.add(data, {
attempts: 3,
backoff: { type: "exponential", delay: 5000 },
});
return job.id;
}
// Consumer: process in background
signingQueue.process(5, async (job) => {
const { templateId, signerEmail, signerName } = job.data;
// Create and send document...
return { status: "sent" };
});
signingQueue.on("completed", (job, result) => {
console.log(`Job ${job.id} completed: ${JSON.stringify(result)}`);
});
signingQueue.on("failed", (job, err) => {
console.error(`Job ${job.id} failed: ${err.message}`);
});
Step 5: Efficient Pagination
// Paginate through all documents without loading everything into memory
async function* iterateDocuments(client: Documenso, perPage = 50) {
let page = 1;
while (true) {
const { documents } = await client.documents.findV0({
page,
perPage,
orderByColumn: "createdAt",
orderByDirection: "desc",
});
for (const doc of documents) {
yield doc;
}
if (documents.length < perPage) break; // Last page
page++;
}
}
// Usage: process all documents without memory issues
for await (const doc of iterateDocuments(client)) {
if (doc.status === "COMPLETED") {
await archiveDocument(doc.id);
}
}
Performance Targets
| Operation | Target | If Exceeded | |-----------|--------|-------------| | Single document create | < 500ms | Check network latency | | Template create + send | < 1s | Normal for template workflow | | Batch of 100 documents | < 30s | Use concurrency 5-10 | | Document list (page) | < 300ms | Add caching layer | | Webhook processing | < 100ms | Process async, respond 200 immediately |
Error Handling
| Performance Issue | Cause | Solution |
|------------------|-------|----------|
| Slow responses | No connection reuse | Use singleton client pattern |
| Rate limit errors | Too many concurrent calls | Use p-queue with concurrency cap |
| Memory issues | Loading all documents | Use async generator pagination |
| Queue backlog | Slow processing | Increase worker concurrency |
Resources
Next Steps
For cost optimization, see documenso-cost-tuning.