hubspot-rate-limit-survival
Survive HubSpot API rate limits at production scale. Covers daily 500K portal quota, per-10s burst limits, batch API efficiency (100x), token bucket pattern, queue-based worker architecture, and Retry-After header parsing. Use when a sync job burns the daily quota before 8am, when a parallelized batch job retry-storms on 429s, when single-record reads waste 99% of available throughput, or when instrumenting a rate-limit dashboard for an Ops Hub Enterprise portal. Trigger with "hubspot rate limit", "hubspot quota", "hubspot 429", "hubspot batch API", "hubspot token bucket", "hubspot throttle", "hubspot daily limit exhausted", "hubspot Ops Hub rate limit".
Allowed Tools
Provided by Plugin
hubspot-pack
Claude Code skill pack for HubSpot (10 production-engineer skills)
Installation
This skill is included in the hubspot-pack plugin:
/plugin install hubspot-pack@claude-code-plugins-plus
Click to copy
Instructions
HubSpot Rate Limit Survival
Overview
Rate-limit your HubSpot integration so it survives production volume without burning the portal's daily quota before lunch. This skill covers the six failure modes that take down integrations at scale and gives you the code to prevent each one.
Key invariant: HubSpot rate limits are portal-scoped, not app-scoped. Every private app and OAuth app in the same portal shares the same daily and per-10s buckets. There is no per-app isolation.
The six production failures this skill prevents:
- Daily quota burnout — a naive sync of 5M contacts at 100 records/call requires 50,000 API calls. A misconfigured parallel worker pool exhausts the 500K/day quota in under 90 minutes, leaving the portal dark for 22 hours.
- Burst limit ignorance — parallelizing 20 concurrent requests saturates the 100 req/10s window instantly. The 429 retry storm then burns the daily budget too. The burst limit and daily quota are two independent counters.
- Ignoring batch APIs —
GET /contacts/{id}costs 1 quota unit and returns 1 record.POST /contacts/batch/readwith 100 IDs costs 1 unit and returns 100 records. Single-record reads waste 99% of available throughput. - Retry-After ignored — a 429 includes
Retry-After: N. Backing off by 1s when N=30 produces 29 consecutive failures. Backing off by 30s when N=1 adds unnecessary latency. Always parse and honor the header exactly. - Daily limit vs per-10s confusion — these are two independent systems. Burning the burst window does not decrement the daily counter. Exhausting the daily counter does not care about the per-10s rate. Conflating them breaks rate-limit logic.
- Operations Hub Enterprise gating — the 100 req/s sustained rate is gated on Ops Hub Enterprise. A Starter account assuming that throughput gets 429s at 10x the expected rate with no clear signal that the limit tier is wrong.
Prerequisites
- Node.js 18+ or Python 3.10+
- HubSpot private app token or OAuth access token
@hubspot/api-client(npm) orhubspot(pip) for SDK-based integrations- For queue-based architecture: Redis 6+ with
bullmq(npm) orcelery+redis-py(Python) - Portal Settings → Integrations → Private Apps to confirm the plan tier
Auth: Every API call requires Authorization: Bearer {token}. For token acquisition and caching, see hubspot-auth skill. This skill assumes a valid token is already available.
Instructions
Build in this order. Steps 1–3 are mandatory. Steps 4–6 apply when volume exceeds ~50,000 calls/day or when multiple apps share the portal.
Step 1: Read rate-limit headers on every response
Every HubSpot response carries both bucket states. Never fly blind.
interface RateLimitState {
dailyLimit: number;
dailyRemaining: number;
windowMs: number;
windowMax: number;
windowRemaining: number;
}
let rl: RateLimitState = {
dailyLimit: 500_000, dailyRemaining: 500_000,
windowMs: 10_000, windowMax: 100, windowRemaining: 100,
};
function updateRateLimitState(headers: Headers): void {
if (headers.get("X-HubSpot-RateLimit-Daily"))
rl.dailyLimit = parseInt(headers.get("X-HubSpot-RateLimit-Daily")!, 10);
if (headers.get("X-HubSpot-RateLimit-Daily-Remaining"))
rl.dailyRemaining = parseInt(headers.get("X-HubSpot-RateLimit-Daily-Remaining")!, 10);
if (headers.get("X-HubSpot-RateLimit-Max"))
rl.windowMax = parseInt(headers.get("X-HubSpot-RateLimit-Max")!, 10);
if (headers.get("X-HubSpot-RateLimit-Remaining"))
rl.windowRemaining = parseInt(headers.get("X-HubSpot-RateLimit-Remaining")!, 10);
const pctUsed = 1 - rl.dailyRemaining / rl.dailyLimit;
console.log(JSON.stringify({
event: "hubspot_rate_limit_state",
daily_remaining: rl.dailyRemaining,
daily_pct_used: parseFloat(pctUsed.toFixed(4)),
window_remaining: rl.windowRemaining,
}));
}
Step 2: Token bucket (neutralizes burst limit ignorance)
A token bucket is the correct primitive for the per-10s burst limit. Callers block until a slot is available instead of firing and failing.
class TokenBucket {
private tokens: number;
private lastRefillAt: number;
constructor(
private readonly capacity: number,
private readonly refillRatePerMs: number,
) {
this.tokens = capacity;
this.lastRefillAt = Date.now();
}
consume(count = 1): number { // returns ms to wait; 0 = immediate
const now = Date.now();
this.tokens = Math.min(
this.capacity,
this.tokens + (now - this.lastRefillAt) * this.refillRatePerMs,
);
this.lastRefillAt = now;
if (this.tokens >= count) { this.tokens -= count; return 0; }
return Math.ceil((count - this.tokens) / this.refillRatePerMs);
}
}
// Private app, standard plan: 100 req/10s = 0.01 req/ms
// Ops Hub Enterprise: 100 req/s = 0.1 req/ms
const BUCKETS = {
starter: new TokenBucket(100, 10 / 10_000),
professional: new TokenBucket(150, 15 / 10_000),
ops_hub_enterprise: new TokenBucket(1000, 100 / 10_000),
};
type PlanTier = keyof typeof BUCKETS;
let activeBucket: TokenBucket = BUCKETS.starter;
export function configurePlanTier(tier: PlanTier): void {
activeBucket = BUCKETS[tier];
}
export async function acquireToken(): Promise<void> {
const waitMs = activeBucket.consume();
if (waitMs > 0) await new Promise((r) => setTimeout(r, waitMs));
}
Step 3: Retry-After parser and hubspotFetch (neutralizes ignored 429s)
Honor the exact backoff value HubSpot specifies. Full implementation with mock-server test harness in implementation-guide.md.
function parseRetryAfterMs(headers: Headers): number | null {
const raw = headers.get("Retry-After");
if (!raw) return null;
const s = parseInt(raw, 10);
return isNaN(s) ? null : s * 1_000;
}
export async function hubspotFetch(
path: string,
init: RequestInit = {},
maxAttempts = 5,
): Promise<Response> {
for (let attempt = 1; attempt <= maxAttempts; attempt++) {
await acquireToken();
const res = await fetch(`https://api.hubapi.com${path}`, {
...init,
headers: {
Authorization: `Bearer ${process.env.HUBSPOT_ACCESS_TOKEN!}`,
"Content-Type": "application/json",
...init.headers,
},
});
updateRateLimitState(res.headers);
if (res.ok) return res;
const retryable = res.status === 429 || (res.status >= 500 && res.status < 600);
if (!retryable || attempt === maxAttempts) throw new Error(`HubSpot ${res.status}: ${path}`);
const delayMs = parseRetryAfterMs(res.headers)
?? Math.random() * Math.min(60_000, 500 * 2 ** attempt);
await new Promise((r) => setTimeout(r, delayMs));
}
throw new Error("unreachable");
}
Step 4: Batch API wrapper (neutralizes single-record waste)
Auto-chunk any array of IDs into groups of 100. Each chunk costs 1 quota unit.
const BATCH_SIZE = 100; // HubSpot hard limit
function chunk<T>(arr: T[], size = BATCH_SIZE): T[][] {
const chunks: T[][] = [];
for (let i = 0; i < arr.length; i += size) chunks.push(arr.slice(i, i + size));
return chunks;
}
export async function batchRead(
objectType: "contacts" | "companies" | "deals" | "tickets",
ids: string[],
properties: string[],
): Promise<{ results: unknown[]; errors: unknown[] }> {
const results: unknown[] = [];
const errors: unknown[] = [];
for (const batch of chunk(ids)) {
const res = await hubspotFetch(`/crm/v3/objects/${objectType}/batch/read`, {
method: "POST",
body: JSON.stringify({ inputs: batch.map((id) => ({ id })), properties }),
});
const body = await res.json() as { results: unknown[]; errors?: unknown[] };
results.push(...body.results);
if (body.errors) errors.push(...body.errors);
}
return { results, errors };
}
Step 5: Daily quota shutoff valve (neutralizes quota burnout)
Halt lower-priority work before the portal goes dark.
type Priority = "critical" | "high" | "normal" | "low";
const SHUTOFF: Record<Priority, number> = {
critical: 0.99, high: 0.95, normal: 0.90, low: 0.80,
};
export function assertDailyQuotaAvailable(priority: Priority): void {
const pctConsumed = 1 - rl.dailyRemaining / rl.dailyLimit;
if (pctConsumed >= SHUTOFF[priority]) {
throw new Error(
`Daily quota shutoff: ${(pctConsumed * 100).toFixed(1)}% consumed — ` +
`${priority} priority requests halted`,
);
}
}
Step 6: Plan-tier auto-detection at startup
Read X-HubSpot-RateLimit-Max from the first response instead of hard-coding the tier.
export async function detectAndConfigurePlanTier(): Promise<PlanTier> {
const res = await fetch(
"https://api.hubapi.com/crm/v3/objects/contacts?limit=1",
{ headers: { Authorization: `Bearer ${process.env.HUBSPOT_ACCESS_TOKEN!}` } },
);
const max = parseInt(res.headers.get("X-HubSpot-RateLimit-Max") ?? "100", 10);
const tier: PlanTier =
max >= 1000 ? "ops_hub_enterprise" :
max >= 150 ? "professional" :
"starter";
configurePlanTier(tier);
console.log(`HubSpot plan tier: ${tier} (window max: ${max})`);
return tier;
}
Error Handling
| HTTP Status | Error Code | Root Cause | Action |
|---|---|---|---|
429 |
RATE_LIMIT / policyName: SECONDLY |
Per-10s burst window exhausted | Read Retry-After; wait exactly that many seconds |
429 |
RATE_LIMIT / policyName: DAILY |
500K/day quota exhausted | Stop all non-critical calls; resume after midnight UTC |
400 |
BATCHSIZEEXCEEDED |
More than 100 IDs in batch payload | Chunk inputs to max 100; batchRead wrapper handles this |
400 |
INVALIDBATCHREQUEST |
Malformed batch payload | Verify inputs is [{id: string}]; properties is an array |
403 |
MISSING_SCOPES |
Token lacks scope for the object type | Add required scope in HubSpot Settings → Private Apps |
403 |
PORTALNOTALLOWED |
Ops Hub Enterprise feature on lower-tier plan | Reduce throughput target; verify plan tier via X-HubSpot-RateLimit-Max |
5xx |
INTERNAL_ERROR |
HubSpot transient error | Retry with exponential backoff; typically resolves within 60s |
Diagnose daily vs burst 429:
curl -sv "https://api.hubapi.com/crm/v3/objects/contacts?limit=1" \
-H "Authorization: Bearer $HUBSPOT_ACCESS_TOKEN" 2>&1 \
| grep -E "< (X-HubSpot|Retry-After|HTTP)"
# Retry-After 1-30s + Daily-Remaining > 0 → burst window
# Daily-Remaining = 0 → daily quota
Examples
Baseline rate-limit health check
curl -sI "https://api.hubapi.com/crm/v3/objects/contacts?limit=1" \
-H "Authorization: Bearer $HUBSPOT_ACCESS_TOKEN" \
| grep -i "X-HubSpot-RateLimit\|Retry-After"
Batch read 500 contacts (5 quota units instead of 500)
curl -s "https://api.hubapi.com/crm/v3/objects/contacts/batch/read" \
-H "Authorization: Bearer $HUBSPOT_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"inputs":[{"id":"1"},{"id":"2"},{"id":"3"}],"properties":["email","firstname"]}' \
| jq '{count: (.results | length), errors: (.errors | length)}'
Python quota monitor (cron-safe, 1 quota unit per run)
import os, json, requests
def check_quota() -> dict:
r = requests.get(
"https://api.hubapi.com/crm/v3/objects/contacts",
headers={"Authorization": f"Bearer {os.environ['HUBSPOT_ACCESS_TOKEN']}"},
params={"limit": 1},
)
daily = int(r.headers.get("X-HubSpot-RateLimit-Daily", 500_000))
rem = int(r.headers.get("X-HubSpot-RateLimit-Daily-Remaining", daily))
pct = 1 - rem / daily
return {"daily_remaining": rem, "pct_consumed": round(pct, 4),
"shutoff_active": pct >= 0.90,
"window_remaining": int(r.headers.get("X-HubSpot-RateLimit-Remaining", 0))}
print(json.dumps(check_quota(), indent=2))
Output
- Token bucket module calibrated to portal plan tier; callers block rather than fire-and-fail
hubspotFetchwrapper parsingRetry-Afteron every 429 and backing off by the server-specified duration- Batch read wrapper auto-chunking any array into groups of 100, reducing quota consumption up to 100x
- Structured log events for every rate-limit state update, suitable for Datadog / Prometheus / CloudWatch
- Priority-tiered shutoff valve halting background jobs at 80% and critical jobs at 99%
- Plan-tier auto-detection from response headers so the correct burst limit is applied without hard-coding
Resources
- HubSpot API Usage and Rate Limits
- CRM Batch APIs Reference
- HubSpot API Error Handling
- Operations Hub Overview
- HubSpot Status Page
APIREFERENCE.md— all rate-limit headers, limit tiers by plan, batch endpoint signatures, 429 response shapesimplementation-guide.md— Python token bucket, Bull/Redis queue worker, daily quota dashboard metrics, Retry-After parser, batch chunker, mock-server test harness