serverless-development
AWS Lambda, Vercel Edge Functions, Cloudflare Workers, cold starts, deployment patterns, and infrastructure as code (SST, Serverless Framework).
Skill by travisjneuman
Install
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About
Use cases: devops, cloud
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Files it touches
~/.claude/skills/serverless-development
What's inside
- Skill name
serverless-development- Description
- AWS Lambda, Vercel Edge Functions, Cloudflare Workers, cold starts, deployment patterns, and infrastructure as code (SST, Serverless Framework). Use when building serverless applications or optimizing function-based architectures.
- License
- MIT
- Instructions
- 454 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Serverless Development
## Overview
This skill covers building applications on serverless compute platforms where infrastructure management is abstracted away. It addresses AWS Lambda (Node.js, Python, Go runtimes), Vercel Edge Functions and Serverless Functions, Cloudflare Workers, cold start optimization, serverless design patterns (fan-out, step functions, event-driven), database connection management, deployment with SAM/SST/Serverless Framework, monitoring, and cost optimization.
Use this skill when building APIs, webhooks, background processing, scheduled tasks, or any workload that benefits from auto-scaling, pay-per-use pricing, and zero infrastructure management.
---
## Core Principles
1. **Design for statelessness** - Every function invocation is independent. Never store state in global variables between invocations (though you can reuse connections). Use external state stores (databases, caches, queues) for persistence.
2. **Minimize cold starts** - Cold starts add 100ms-10s of latency on first invocation. Keep bundles small, use lightweight runtimes, and consider provisioned concurrency for latency-sensitive paths.
3. **Connection management is critical** - Serverless functions can spawn thousands of concurrent instances. Each opening its own database connection will exhaust connection pools. Use connection pooling (RDS Proxy, Prisma Data Proxy, PgBouncer).
4. **Pay-per-invocation thinking** - You pay for execution time and memory. Optimize hot paths, choose appropriate memory sizes (more memory = more CPU = potentially faster = sometimes cheaper), and batch operations where possible.
5. **Embrace the constraints** - Function timeouts, payload limits, and concurrency limits are features, not bugs. Design around them: use queues for long tasks, S3 for large payloads, and step functions for complex orchestration.
---
## Key Patterns
### Pattern 1: AWS Lambda with TypeScript
**When to use:** Backend APIs, event processing, scheduled tasks on AWS.
**Implementation:**
```typescript
// handler.ts - Lambda handler with proper typing
import {
APIGatewayProxyEventV2,
APIGatewayProxyResultV2,
SQSEvent,
ScheduledEvent,
Context,
} from "aws-lambda";
// Reusable across invocations (connection reuse)
let dbConnection: PrismaClient | null = null;
function getDb(): PrismaClient {
if (!dbConnection) {
dbConnection = new PrismaClient({
datasources: {
db: { url: process.env.DATABASE_URL },
},
});
}
return dbConnection;
}
// API Gateway handler
export async function apiHandler(
event: APIGatewayProxyEventV2,
context: Context
): Promise<APIGatewayProxyResultV2> {
// Don't wait for event loop to drain (for connection reuse)
context.callbackWaitsForEmptyEventLoop = false;
try {
const method = event.requestContext.http.method;
const path = event.rawPath;
if (method === "GET" && path === "/api/users") {
const db = getDb();
const users = await db.user.findMany({ take: 50 });
return response(200, { users });
}
if (method === "POST" && path === "/api/users") {
const body = JSON.parse(event.body ?? "{}");
const db = getDb();
const user = await db.user.create({ data: body });
return response(201, { user });
}
return response(404, { error: "Not found" });
} catch (error) {
console.error("Handler error:", error);
return response(500, { error: "Internal server error" });
}
}
// SQS event handler (batch processing)
export async function sqsHandler(event: SQSEvent): Promise<{ batchItemFailures: Array<{ itemIdentifier: string }> }> {
const failures: string[] = [];
for (const record of event.Records) {
try {
const body = JSON.parse(record.body);
await processMessage(body);
} catch (error) {
console.error(`Failed to process message ${record.messageId}:`, error);
failures.push(record.messageId);
}
}
// Partial batch failure reporting (only retry failed messages)
return {
batchItemFailures: failures.map((id) => ({ itemIdentifier: id })),
};
}
// Scheduled event handler (cron)
export async function cronHandler(event: ScheduledEvent): Promise<void> {
console.log("Running scheduled task at:", event.time);
const db = getDb();
// Clean up expired sessions
const deleted = await db.session.deleteMany({
where: { expiresAt: { lt: new Date() } },
});
console.log(`Cleaned up ${deleted.count} expired sessions`);
}
function response(statusCode: number, body: Record<string, unknown>): APIGatewayProxyResultV2 {
return {From travisjneuman/.claude, MIT.
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Signals
- Stars
- 106
- Forks
- 26
- Open issues
- 2
- Last commit (this folder)
- Feb 28, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/travisjneuman/.claude
- Website
- claude.travisjneuman.com
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
serverless-development skill. Agent Mart. https://agentmart.dev/skills/travisjneuman-serverless-development (last updated 2026-10-24)