flyio-rate-limits
Handle Fly.io Machines API rate limits with backoff, concurrency control, and request batching for machine management operations. Trigger: "fly.io rate limit", "fly.io 429", "fly.io throttling", "machines API limit".
Best use case
flyio-rate-limits is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Handle Fly.io Machines API rate limits with backoff, concurrency control, and request batching for machine management operations. Trigger: "fly.io rate limit", "fly.io 429", "fly.io throttling", "machines API limit".
Teams using flyio-rate-limits should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/flyio-rate-limits/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How flyio-rate-limits Compares
| Feature / Agent | flyio-rate-limits | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Handle Fly.io Machines API rate limits with backoff, concurrency control, and request batching for machine management operations. Trigger: "fly.io rate limit", "fly.io 429", "fly.io throttling", "machines API limit".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Fly.io Rate Limits
## Overview
The Fly.io Machines API rate-limits per organization, with write operations (create, delete, update) throttled much more aggressively than reads. Deploying fleets of edge machines across multiple regions can easily trigger 429s, especially during rolling deployments or auto-scaling events. The API returns a `Retry-After` header on rate-limited responses, and organizations running 50+ machines should implement client-side token bucket limiting to avoid cascading failures during high-churn operations.
## Rate Limit Reference
| Endpoint | Limit | Window | Scope |
|----------|-------|--------|-------|
| Machine create/delete | 10 req | 1 minute | Per org |
| Machine start/stop | 30 req | 1 minute | Per org |
| Machine list/get | 120 req | 1 minute | Per org |
| App create/delete | 5 req | 1 minute | Per org |
| Volume operations | 15 req | 1 minute | Per org |
## Rate Limiter Implementation
```typescript
class FlyRateLimiter {
private tokens: number;
private lastRefill: number;
private readonly max: number;
private readonly refillRate: number;
private queue: Array<{ resolve: () => void }> = [];
constructor(maxPerMinute: number) {
this.max = maxPerMinute;
this.tokens = maxPerMinute;
this.lastRefill = Date.now();
this.refillRate = maxPerMinute / 60_000;
}
async acquire(): Promise<void> {
this.refill();
if (this.tokens >= 1) { this.tokens -= 1; return; }
return new Promise(resolve => this.queue.push({ resolve }));
}
private refill() {
const now = Date.now();
this.tokens = Math.min(this.max, this.tokens + (now - this.lastRefill) * this.refillRate);
this.lastRefill = now;
while (this.tokens >= 1 && this.queue.length) {
this.tokens -= 1;
this.queue.shift()!.resolve();
}
}
}
const writeLimiter = new FlyRateLimiter(8); // leave headroom under 10/min
const readLimiter = new FlyRateLimiter(100);
```
## Retry Strategy
```typescript
async function flyRetry<T>(fn: () => Promise<Response>, maxRetries = 4): Promise<T> {
for (let attempt = 0; attempt <= maxRetries; attempt++) {
const res = await fn();
if (res.ok) return res.json();
if (res.status === 429) {
const retryAfter = parseInt(res.headers.get("Retry-After") || "10", 10);
const delay = retryAfter * 1000 + Math.random() * 2000;
await new Promise(r => setTimeout(r, delay));
continue;
}
if (res.status >= 500 && attempt < maxRetries) {
await new Promise(r => setTimeout(r, Math.pow(2, attempt) * 1000));
continue;
}
throw new Error(`Fly API ${res.status}: ${await res.text()}`);
}
throw new Error("Max retries exceeded");
}
```
## Batch Processing
```typescript
async function rollingDeployMachines(appId: string, configs: any[], batchSize = 3) {
const results: any[] = [];
for (let i = 0; i < configs.length; i += batchSize) {
const batch = configs.slice(i, i + batchSize);
const batchResults = await Promise.all(
batch.map(async cfg => {
await writeLimiter.acquire();
return flyRetry(() =>
fetch(`https://api.machines.dev/v1/apps/${appId}/machines`, {
method: "POST", headers, body: JSON.stringify(cfg),
})
);
})
);
results.push(...batchResults);
if (i + batchSize < configs.length) await new Promise(r => setTimeout(r, 10_000));
}
return results;
}
```
## Error Handling
| Issue | Cause | Fix |
|-------|-------|-----|
| 429 on machine create | Exceeded 10 writes/min org limit | Use Retry-After header, batch deploys |
| 429 on fleet list | Monitoring polling too fast | Cache responses, poll every 30s max |
| Timeout on volume attach | Volume in another region | Verify region match before attach |
| 503 during region outage | Specific edge region down | Fail over to secondary region |
| 409 on machine update | Concurrent config change | Re-fetch machine state, retry with latest version |
## Resources
- [Fly.io Machines API](https://fly.io/docs/machines/api/)
## Next Steps
See `flyio-performance-tuning`.Related Skills
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