Castai rate limits
Skill jeremylongshore/claude-code-plugins-plus-skills/skills/.curated/castai-rate-limits
'Handle CAST AI API rate limits with backoff and request queuing.From its SKILL.md
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CAST AI Rate Limits
Overview
The CAST AI REST API enforces rate limits per API key. The autoscaler agent communicates cluster state at 15-second intervals. For custom API integrations, implement exponential backoff and request queuing to avoid hitting limits.
Prerequisites
- CAST AI API key configured
- Understanding of the API endpoints you call
Rate Limit Behavior
| Aspect | Value |
|---|---|
| Rate limit scope | Per API key |
| Response on limit | HTTP 429 with Retry-After header |
| Agent sync interval | Every 15 seconds |
| Recommended polling | No more than once per 30 seconds |
Instructions
Step 1: Detect Rate Limits from Response Headers
async function castaiRequest(path: string): Promise<Response> {
const response = await fetch(`https://api.cast.ai${path}`, {
headers: { "X-API-Key": process.env.CASTAI_API_KEY! },
});
// Log rate limit headers for monitoring
const remaining = response.headers.get("X-RateLimit-Remaining");
const reset = response.headers.get("X-RateLimit-Reset");
if (remaining) {
console.log(`Rate limit remaining: ${remaining}, resets: ${reset}`);
}
if (response.status === 429) {
const retryAfter = parseInt(response.headers.get("Retry-After") ?? "5");
throw new RateLimitError(retryAfter);
}
return response;
}
class RateLimitError extends Error {
constructor(public retryAfterSeconds: number) {
super(`Rate limited. Retry after ${retryAfterSeconds}s`);
}
}
Step 2: Exponential Backoff with Jitter
async function withBackoff<T>(
fn: () => Promise<T>,
maxRetries = 5
): Promise<T> {
for (let attempt = 0; attempt <= maxRetries; attempt++) {
try {
return await fn();
} catch (err) {
if (attempt === maxRetries) throw err;
let delayMs: number;
if (err instanceof RateLimitError) {
delayMs = err.retryAfterSeconds * 1000;
} else {
delayMs = Math.min(1000 * Math.pow(2, attempt), 30000);
}
// Add jitter to prevent thundering herd
delayMs += Math.random() * 1000;
console.log(`Retry ${attempt + 1}/${maxRetries} in ${delayMs}ms`);
await new Promise((r) => setTimeout(r, delayMs));
}
}
throw new Error("Unreachable");
}
Step 3: Request Queue for Batch Operations
import PQueue from "p-queue";
// Limit concurrent requests and enforce interval
const castaiQueue = new PQueue({
concurrency: 3,
interval: 1000,
intervalCap: 5, // Max 5 requests per second
});
async function queuedCastAIRequest<T>(fn: () => Promise<T>): Promise<T> {
return castaiQueue.add(() => withBackoff(fn));
}
// Batch process multiple clusters
const clusterIds = ["id1", "id2", "id3", "id4", "id5"];
const savings = await Promise.all(
clusterIds.map((id) =>
queuedCastAIRequest(() =>
fetch(`https://api.cast.ai/v1/kubernetes/clusters/${id}/savings`, {
headers: { "X-API-Key": process.env.CASTAI_API_KEY! },
}).then((r) => r.json())
)
)
);
Step 4: Polling Best Practice
// Do NOT poll faster than 30 seconds for cluster state
// The agent syncs every 15s; polling faster adds no value
async function pollClusterStatus(
clusterId: string,
intervalMs = 30000
): Promise<void> {
const timer = setInterval(async () => {
try {
const status = await queuedCastAIRequest(() =>
fetch(
`https://api.cast.ai/v1/kubernetes/external-clusters/${clusterId}`,
{ headers: { "X-API-Key": process.env.CASTAI_API_KEY! } }
).then((r) => r.json())
);
console.log(`Cluster ${clusterId}: ${status.agentStatus}`);
} catch (err) {
console.error("Poll failed:", err);
}
}, intervalMs);
}
Error Handling
| Scenario | Detection | Response |
|---|---|---|
| 429 with Retry-After | Check header | Wait exact duration |
| 429 without header | Status code only | Exponential backoff from 1s |
| 5xx errors | Status >= 500 | Retry up to 3 times |
| Connection timeout | Fetch throws | Retry with longer timeout |
Resources
- CAST AI API Reference
- p-queue -- concurrent request queue
Next Steps
For security configuration, see castai-security-basics.
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