How do you protect a GraphQL endpoint from abusive queries?
Assesses fundamental understanding of GraphQL conventions, runtime behavior, and memory/performance considerations.
Hiring managers look for precision, avoidance of ambiguous jargon, and ability to explain trade-offs under real production conditions.
Because clients can compose arbitrarily deep and wide queries, a single request can exhaust the database.
Defences:
- Limit query depth, for example reject anything deeper than ten levels.
- Assign a cost to each field and reject queries whose total exceeds a budget, charging more for list fields and expensive joins.
- Require persisted queries so only pre-approved operations run in production, which also shrinks payloads.
- Disable or restrict introspection in production, and apply per-client rate limits and timeouts.
- Cap pagination arguments and reject requests without a limit.
const server = new ApolloServer({
validationRules: [depthLimit(10), createComplexityLimitRule(1000)],
});
Combine these with database query timeouts and monitoring so a bad query is cut off before it degrades shared resources. Depth alone is insufficient because a shallow query can still request huge lists.
Candidate Response Strategy & Interview Tips
- Start with a concise one-sentence summary: Deliver a direct, confident answer first before expanding into nuances.
- Demonstrate real-world trade-offs: Discuss where this approach excels and when you would avoid it in production systems.
- Discuss complexity & edge cases: Proactively explain time/space complexity or boundary conditions (null values, scale limits).
- Prepare for interviewer follow-ups: Technical hiring panels frequently probe deeper into concurrency, backward compatibility, or alternative libraries.