alpaca-broker-rate-limits-resilience

Alpaca — Rate Limits & Resilience

Alpaca's APIs are rate-limited and occasionally flaky under load. Any client that does more than a handful of calls — especially bulk jobs, backfills, and reconciliation sweeps — needs disciplined retry, backoff, and concurrency control. These patterns are transport-level and apply in any language.

Read alpaca-broker-integration first.

1. Rate-limit headers — read them on every response

Alpaca returns standard headers:

Header	Meaning
X-RateLimit-Limit	requests allowed in the window
X-RateLimit-Remaining	requests left in the current window
X-RateLimit-Reset	unix timestamp (seconds) when the window resets

Parse them on every response, not just on errors. Two uses:

• Proactive: slow down as Remaining falls toward zero, rather than waiting to be throttled. Any warning threshold you pick is your own starting point, derived from Limit — Alpaca publishes none.
• Reactive: on 429, use Reset to wait exactly until the window opens.

Broker limits are applied at the correspondent level — across your whole integration, not per end-user account, so every process you run shares one budget. They're set per partner and not published; react to the headers.

Sandbox limits are significantly lower than production and are not a reliable signal of production headroom. Alpaca explicitly says not to load-test against sandbox — mock the Alpaca calls instead and have the stub simulate latencies sampled from real production calls.

2. The retry loop (pseudocode)

MAX_ATTEMPTS = 10
INITIAL_DELAY_MS = 1000
MAX_DELAY_MS = 60000
backoff(n) = min(INITIAL_DELAY_MS * 2^(n-1), MAX_DELAY_MS) + random(0, 500)

for attempt in 1..MAX_ATTEMPTS:
    res = http(request)                      # with a sane timeout (see §5)
    limit, remaining, reset_at = parse_rate_headers(res.headers)
    if remaining < low_water(limit): log_warn("approaching rate limit", reset_at)

    if res.status == 429:
        # wait until the window resets, plus a small buffer
        wait = (reset_at - now()) if reset_at else backoff(attempt)
        sleep(max(0, wait) + 1000 + random(0, 500))
        continue

    if res.status in (500, 502, 503, 504) or network_error:
        sleep(backoff(attempt))
        continue

    return res                                # success or non-retryable 4xx
raise last_error

Key points:

• On 429, wait until X-RateLimit-Reset + a ~1s buffer, then keep exponential backoff underneath — Reset says when the window rolls, not whether the herd behind you re-saturates it.
• Exponential backoff (base * 2^(attempt-1)) for network errors and 5xx, capped (the docs' example caps at 60s). With base 1s and 10 attempts the tail is minutes — fine for background jobs, too slow for user-facing calls (use fewer attempts there).
• Jitter every wait. It's part of the documented recommendation, not an extra: a correspondent-wide limit means all your workers are throttled together and would otherwise retry in lockstep.
• Don't retry non-retryable 4xx (400/403/422) — those won't fix themselves; surface them.

3. Bounded concurrency

Parallelism speeds bulk jobs but is the fastest way to hit limits. Use a fixed worker pool, not unbounded fan-out.

• Size the pool from X-RateLimit-Limit, not from a fixed number, and remember the limit is correspondent-level: every worker, cron job, and web process you run draws on the same budget. Tune down from observed Remaining; your own downstream store is often the tighter constraint.
• Cache per-entity reads within a run (e.g. an account's buying power, or a per-account transfer list) so you don't refetch the same thing across items in a batch.
• For per-item throttling, a small fixed sleep between calls (e.g. 100ms) is a crude-but-effective floor when you can't easily coordinate a pool.

4. Pagination loops

List endpoints page forward with a token — never assume one response is complete.

• Activities (/v1/accounts/activities): the response is a bare JSON array with no pagination header — pass the id of the last activity in the page back as page_token and stop when a page comes back short. page_size defaults to and maxes at 100 (no maximum when date is set — it returns everything); direction is asc/desc, default desc.
• Market-data bars (/v2/stocks/bars): page via next_page_token in the body → pass back as page_token. Remember limit counts across all symbols and results sort by symbol-then-time, so a single page may contain only the first symbol(s) — keep paging.
• Wrap each page fetch in the retry loop from §2.

token = null
loop:
    page = fetch(url + (token ? "&page_token="+token : ""))   # via retry loop
    accumulate(page.items)
    if body_token_endpoint:
        token = page.next_page_token
        if not token: break
    else:                              # activities: bare array, no token
        if len(page.items) < page_size: break
        token = page.items[-1].id

5. Timeouts & batch sizing

• Always set an HTTP timeout (15–30s is a reasonable starting point, not an Alpaca number). A hung connection without a timeout stalls a whole worker pool. (SSE streams are the exception — they're meant to stay open; see alpaca-broker-sse-events.)
• Use a shared HTTP client / connection pool rather than constructing one per request, so keep-alive and connection reuse work.
• Detect silence on the market-data WebSocket and reconnect + resubscribe. A slow client is disconnected, and the 407 slow client error is "not guaranteed to arrive before you are disconnected" — so a dead socket can look identical to a quiet one (see alpaca-broker-market-data).
• When writing reconciliation results to your own store, chunk bulk inserts to stay under DB statement-size limits and keep transactions reasonable; pick the chunk size from your own database's behavior.

6. Resilience checklist for a bulk/cron job

• Rate-limit headers parsed every response; proactive warn near the limit.
• 429 → wait until X-RateLimit-Reset + buffer.
• Exponential backoff with jitter for 5xx/network; capped delay and capped attempts.
• Non-retryable 4xx surfaced, not retried.
• Bounded worker pool; per-run caching of repeated reads.
• Pagination loop until the token is empty.
• HTTP timeout on every call; shared client.
• Bulk DB writes chunked and idempotent (upsert) — see alpaca-broker-reconciliation-idempotency.
• Structured logging with a trace/correlation ID per item for debugging partial failures.

Related skills: safe re-runs of jobs → alpaca-broker-reconciliation-idempotency; the heal/poll jobs that use these patterns → alpaca-broker-reconciliation-idempotency; market-data pagination specifics → alpaca-broker-market-data.