Search the practice set
126 questions, 454 terms and 400 topics in 20 areas.
60 results for “API Error Handling”
API Gateway
A single entry point in front of a set of services that handles authentication, rate limiting, routing and protocol translation.
Error Budget
The amount of unreliability an SLO permits, treated as a resource that feature velocity spends.
Error Budget Policy
The written agreement about what happens when the error budget is exhausted, which is what turns an SLO from a number into a control.
Semantic Diffing of API Schemas
Comparing the published contract between builds and failing the build on a breaking change, so compatibility is mechanical rather than remembered.
Stripe's API Versioning
Stripe pins each account to the API version current when it integrated and transforms requests and responses between versions internally, so integrations never break and the core …
Backend for Frontend
A separate, narrow backend per client experience, which aggregates and reshapes downstream services for exactly that client's needs.
Backfill
Re-running a pipeline over historical periods to populate new data or correct a past error, and the operation that proves whether a pipeline is well designed.
Backward Compatibility
The property that a new version of a producer continues to work with clients written against the old version.
Burn Rate Alerting
Paging when the error budget is being consumed fast enough to matter, rather than when a component crosses a threshold.
Contract Testing
Verifying that a provider satisfies the expectations each of its consumers actually relies on, without running all the services together.
Dead Letter Queue
A separate queue that receives messages which could not be processed after a set number of attempts, so they neither block the consumer nor disappear.
Deadline Exceeded
The error returned when a request's overall budget expires — semantically distinct from a per-hop timeout, and a signal that must not be retried blindly.
Enterprise Integration Patterns
A catalogue of named, composable messaging patterns — router, translator, aggregator, splitter, filter, dead letter channel — that gives integration work a shared vocabulary.
Event-Driven Integration
Systems integrating by publishing and consuming events rather than by calling each other's APIs.
GraphQL
A query language and runtime where the client specifies exactly which fields it needs, against a typed schema, usually via a single endpoint.
Idempotency
The property that performing an operation many times has the same effect as performing it once.
Idempotency Key
A client-generated unique value sent with a request so the server can recognise a retry and return the original result instead of acting twice.
Immutable Backup
A backup that cannot be modified or deleted for a defined retention period, even by an administrator — the control that makes backups survive ransomware and insider error.
LinkedIn and the Origin of Kafka
Kafka was built to replace point-to-point data integration between many systems with a single durable log that any system could publish to and any number could read.
Mass Assignment
A vulnerability where a request body is bound directly to an internal object, allowing a caller to set fields the API never intended to expose.
OAuth 2.0
An authorisation framework that lets an application obtain scoped, delegated access to a resource without handling the user's credentials.
OpenAPI
A machine-readable specification format for HTTP APIs, from which documentation, clients, servers, mocks and validation can be generated.
REST
An architectural style for APIs built on resources identified by URLs, manipulated with uniform HTTP methods, and stateless requests.
Rate Limiting
Bounding how many requests a caller may make in a window, to protect capacity and enforce fair use.
A finance report double-counts revenue after a new fact table is added. What is the likely modelling error?
The likely error: a fan out join between fact tables at different grains The classic mechanism. You have an order lines fact at line grain and a shipments fact
A serverless API works in testing and fails under load with connection errors. The database is at 5% CPU. Explain and fix.
The mechanism Serverless functions scale by creating independent execution environments , each with its own process and its own connection pool. Two hundred con
A team proposes storing the customer's address on every order row "so order history is accurate". Is that denormalisation or a modelling error?
The distinction that matters It is neither, quite — it is a temporal modelling requirement being solved by accident. Denormalisation duplicates a fact for perfo
A team wants to build a new internal API on serverless functions. It will serve steady traffic of about 200 requests per second during business hours. What do you advise?
What the interviewer is testing Whether you can apply the serverless trade off to a specific workload rather than treating it as a default good or a default bad
Design a URL shortener handling 100 million new links per month and 10 billion redirects. Where is the real difficulty?
What the interviewer is testing The classic warm up. What is being assessed is not whether you can shorten a URL — it is whether you do capacity arithmetic befo
Design an order submission API that is safe when the client cannot tell whether its request succeeded. What exactly do you store, and when?
What the interviewer is testing Whether you know that "make it idempotent" is a design with specific failure modes, not a checkbox. The core design The client g
Design the audit logging for a system handling financial transactions. What is logged, where does it go, and what makes it hold up?
What is logged Significant actions only , defined explicitly rather than logging everything — an audit trail nobody can search is not usable evidence: Authentic
You are reviewing a new public API before launch. What do you check, in priority order?
1. Object level authorization — check this first, on every endpoint The most common serious API vulnerability. For each endpoint accepting an identifier, verify
A team is launching a new service and asks what its SLO should be. How do you help them decide, and why is "99.99%" usually the wrong first answer?
What the interviewer is testing Whether you treat reliability as a cost benefit decision with a budget, or as a virtue to maximise. Why not four nines It costs
API Error Handling
Error shapes, retryability signals and machine-readable causes.
Secure API Design
Object-level authorisation, input validation and safe error responses.
API & Integration
General material on integrating systems through contracts.
API Documentation
OpenAPI as a machine-checked contract rather than as prose.
API Gateway
A single entry point for policy, routing and protocol translation.
API Gateways
The single entry point, and the business logic that must stay out of it.
API Versioning
URL, header and account-pinned versioning, and who carries the burden.
Error Budgets
Unreliability as a resource that feature velocity spends.
Handling Ambiguity
Making progress when the requirements are not yet knowable.
Handling Disagreement
Arguing from consequences, and escalating in the room.
APIs as Products
Ownership, lifecycle, deprecation policy and developer experience.
Backward Compatibility
Which changes are safe, and how to make breakage a build failure.
Business Metrics
Orders per minute alongside error rate, because healthy is not enough.
Contract Testing
Verifying what consumers actually rely on, without a shared environment.
Contract Tests
Capturing what consumers actually use, not what the API documents.
Event-Driven Integration
Publishing facts rather than commands, and versioning event schemas.
GraphQL
Client-specified queries, N+1 resolution and query-cost control.
Idempotency Keys
Client-generated keys stored atomically with the operation they guard.
Integration Patterns
Routers, translators, splitters, aggregators and dead letter channels.
Legacy Integration
Reaching systems that cannot change, without importing their model.
Message Formats
JSON, Protobuf, Avro — schema evolution and payload economics.
OWASP Risks
The recurring web and API risk classes, several of which are design flaws.
Pagination & Filtering
Offset versus cursor, stable ordering and unbounded result sets.
Partner & B2B Integration
External contracts, onboarding, sandboxes and long deprecation windows.
REST Design
Resources, uniform methods, status codes and statelessness.
Rate Limiting
Algorithms, shared counters, and signalling rejection properly.