Broker Integrations

Broker & Exchange Integration Patterns

Connect reliably. Fail safely.

The integration layer between strategy logic and live execution venues is where most automated trading systems encounter their first production failures. This hub covers the engineering patterns that make broker connections reliable, observable, and recoverable, from adapter architecture and order type mapping to WebSocket reconnect logic, error retry policy, and contract testing.

By Swoopr Editorial Team

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What this hub covers

Broker and exchange integration is the discipline of translating high-level strategy intent, "buy 200 shares of SPY at market", into the exact wire-format messages a specific venue expects, then correctly interpreting every response, error, and state change that comes back. Every broker has a different API surface: different field names, different authentication flows, different order type enumerations, different WebSocket heartbeat requirements, and different behavior under rate limits.

This hub walks through the full lifecycle of a production broker integration: designing the adapter layer that isolates venue specifics from strategy logic, discovering what a broker actually supports vs. what its documentation claims, mapping order types and time-in-force values, handling connection failures and missed events, classifying errors by retryability, reconciling account state, respecting trading calendars, understanding sandbox vs. live differences, designing multi-broker failover, and building automated contract tests that catch API changes before they cause live trading errors.

Key principles

Curriculum: Broker & Exchange Integration Patterns

Ten guides cover the integration layer in sequence, from adapter design through contract testing, plus three interactive tools for capability comparison, contract test generation, and sandbox-to-live readiness assessment.

Guides

Interactive Tools

Frequently Asked Questions

What is a broker adapter and why does it matter?

A broker adapter is an abstraction layer that translates your strategy's generic order intent, buy 100 shares of AAPL at limit $195, into the exact API call, field names, and authentication tokens that a specific broker or exchange expects. Without one, each strategy contains hard-coded broker logic that breaks every time the broker changes its API or you add a new venue. A well-designed adapter lets you swap venues without changing strategy code.

How do I handle order types my broker doesn't support?

First, discover the gap through capability discovery, query or document which order types the broker actually accepts. Then choose a synthesis strategy: decompose the unsupported type into supported primitives (e.g., a trailing stop as a recurring limit cancel-and-replace loop), route that order type to an alternative venue that does support it, or reject the order at the adapter boundary with a clear error rather than silently modifying the order in ways the strategy didn't intend.

What causes most broker API outages and how do I design around them?

Most outages fall into three categories: planned maintenance windows (documented in advance), unplanned rate limit cascades (one client floods the endpoint and the broker throttles everyone), and infrastructure failures (database saturation, CDN issues, or upstream exchange connectivity loss). Designing around them requires circuit breakers that stop sending when error rates spike, fallback routes to a secondary broker for new orders, and position reconciliation logic to audit open trades against broker state after reconnection.

Are sandbox environments accurate enough to test production behavior?

Sandbox environments are useful for basic connectivity, authentication, and order flow testing, but they diverge from production in important ways: fill simulation is typically immediate and unrealistic, rate limits are often more lenient or differently enforced, margin and buying power calculations may not match production rules, and some endpoints (especially account-level queries) return static mock data. The sandbox validates that your code can send and receive the right message shapes; it does not validate that your logic handles realistic execution, partial fills, or market-microstructure edge cases.

What is the right retry policy for broker API errors?

Retry policy depends on error category. Network timeouts and 5xx server errors are generally safe to retry with exponential backoff (1s, 2s, 4s, up to a cap). Rate limit errors (429) require honoring the Retry-After header before retrying. Validation errors (4xx rejections for bad parameters) must never be retried, the request will always fail without changing your input. The most dangerous category is ambiguous state: if you submit an order and receive a timeout before getting an acknowledgment, query the broker for the order status before deciding whether to retry, because a duplicate submission can double your position.

How do you test that a broker adapter works correctly?

Integration contract testing verifies that the adapter correctly translates between your internal model and the broker's wire format, and that the broker's actual responses match your documented expectations. A contract test suite includes: field mapping assertions (does your 'limit' order type translate to the exact string the broker expects?), response parsing tests (does an unexpected field from the broker cause a crash or a silent ignore?), error handling tests (does a 429 trigger backoff?), and state recovery tests (does reconnection restore subscriptions after a WebSocket drop?). Run these against the sandbox and snapshot the results; any future sandbox response change that breaks a snapshot is a signal to investigate before it hits production.

References