Most volume is placed programmatically, and the operational realities of that access are worth understanding before relying on it.
Authentication
Keys with defined permissions — read, trade, withdraw.
Which should be scoped to the minimum needed.
A trading key without withdrawal permission cannot drain an account if compromised, which is the single most important configuration choice.
IP restrictions
Limiting key use to specified addresses.
Which substantially reduces the value of a stolen key.
This is offered by most venues and enabled by a minority of users.
Rate limits
Venues cap request frequency by endpoint and by account.
Which requires client-side management to avoid being throttled or banned.
Weighted limits, where different endpoints consume different amounts, are common and are documented.
Websocket versus polling
Streaming connections deliver updates as they occur.
Which is both faster and lighter than repeated polling.
Connection management, including reconnection and gap recovery, is where most implementation bugs occur.
Order state management
Tracking what orders exist and their status.
Which must handle network failures, duplicate submissions and partial fills.
Client order identifiers allow deduplication and are essential for reliable operation.
Reconciliation
Comparing local state against the venue's record periodically.
Which catches divergence caused by missed messages.
Systems that assume their local state is correct eventually act on a stale picture.
Testing environments
Most venues provide sandbox environments.
Which behave similarly and not identically to production.
Testing with small real amounts before scaling is the practical approach.
Failure handling
What the system does when the venue is unreachable, when an order rejects, or when a position exists that should not.
Which should be decided deliberately rather than emerging from whatever the code happens to do.
Automatic position flattening on disconnection is a common safety measure.
Security practice
Keys in environment variables or secret managers rather than in code, rotated periodically, with withdrawal permission never enabled.
Time synchronisation
Requests are typically signed with a timestamp and rejected outside a window.
Which means clock drift causes authentication failures.
Synchronised time is a basic requirement that catches out new implementations regularly.
Precision and rounding
Venues specify tick sizes and minimum quantities per instrument.
Which cause rejections when not respected.
Floating point handling of quantities is a recurring source of subtle errors.
Fee accounting
Fees may be charged in the traded asset or in a separate token.
Which affects position calculation if not handled explicitly.
Reconciling against the venue's reported balances catches these discrepancies.
Monitoring your own system
Latency, error rates, order rejection rates and position divergence.
Which should alert rather than being reviewed after the fact.
The realistic assessment
Most losses in automated trading come from implementation errors and operational failures rather than from strategy.
This describes engineering practice and is not trading advice.
Backtesting limitations
Historical simulation cannot reproduce market impact or fill probability accurately.
Which is why backtested results systematically overstate live performance.
Conservative assumptions about fills and slippage narrow the gap.
Data quality
Historical data from venues contains gaps, revisions and inconsistencies.
Which propagates into any analysis built on it.
Validating data before relying on it is unglamorous and necessary.
Deployment practice
Staged rollout with size limits, kill switches and monitoring.
Which is standard engineering practice applied to a context where errors cost money immediately.
Regulatory considerations
Automated trading may fall within specific rules depending on jurisdiction and activity.
Which is worth establishing rather than assuming.
The honest framing
Building reliable automation is an engineering problem, and most failures are engineering failures.
Where to start
Venue documentation, a read-only key, and a system that observes before it acts.
Which surfaces most integration problems before any capital is at risk.
Enabling trading permissions should be the last step rather than the first.
Operational discipline
Version control, staged deployment, monitoring, alerting and a documented procedure for stopping everything.
Which is ordinary software engineering practice applied in a context where a bug spends money continuously until someone notices.
The systems that survive are the boring ones with good observability rather than the clever ones.
Position and risk limits
Hard limits enforced in code rather than intended in strategy.
Which is the difference between a bug costing a bounded amount and an unbounded one.
Maximum position size, maximum daily loss and maximum order rate are the standard three.
Logging
Recording every decision and every venue response.
Which is the only way to reconstruct what happened after an incident.
Systems without adequate logs produce arguments rather than explanations.
A last note
A trading key without withdrawal permission, restricted to a known address, is a five-minute configuration that has saved a great many accounts. It is also the setting most people never open.
Summary
Scope keys narrowly, restrict by address, enforce limits in code and log everything.
Which covers the operational failures that account for most losses in automated systems.
Strategy is the part everyone discusses and rarely the part that causes the damage.