Design a Rate Limiter
A distributed service that decides, in under a millisecond, whether a request from a client is allowed under its quota.
6 questions on this site are reported in Datadog software engineer interviews. Each has a full reference design (requirements, back-of-envelope numbers, components, user flows and deep dives with interviewer follow-ups). Each one can be walked through turn by turn and then sat as a mock. Patterns covered: algorithms, counters, redis, edge, stream-processing, windowing, exactly-once, olap, analytics, scheduling, leases, idempotency, queues, fault-tolerance, time-series, compression, cardinality, downsampling, alerting, workflow-orchestration, event-sourcing, durable-timers, sharding, log-aggregation, inverted-index, tiered-storage, backpressure, multi-tenancy.
Run an AI mock Datadog interview →One of these questions, run as a live round in that style, with a debrief at the end.
Attribution comes from public interview guides and candidate reports, not from Datadog. It indicates where a question has been asked, nothing more.
A distributed service that decides, in under a millisecond, whether a request from a client is allowed under its quota.
Count a million ad clicks a second, show advertisers a dashboard that is seconds behind, stop a campaign the moment its budget runs out, and be exactly right when the invoice is cut.
Run millions of cron jobs and one-off tasks on time across a fleet, exactly once each, and keep going when a worker dies halfway through one.
Ingest 10 million samples a second from 100,000 hosts, keep them queryable for a year at shrinking resolution, draw dashboards in under a second, and page the right person within a minute.
A managed workflow engine that runs 200 M state-machine executions a day, some lasting a year, applying every transition exactly once.
Collect 10 million log lines a second from 100,000 hosts, make them searchable within seconds, stream them live, and keep a year affordably.
45–60 minutes in a drawing tool of your choice, often on high-volume data close to what the company runs: metrics or log ingestion, time-series storage, alerting. Some candidates report a general product prompt instead.
Reaching for a generic web-app template. On the data-shaped prompts, throughput, storage and query speed need to be in the design from the start, not added once the boxes are drawn.
From public interview guides and candidate reports, and Datadog’s own interview guidance where it publishes any. Not endorsed by Datadog. Formats change; treat it as a prior, not a promise.
Large-company loops run 45 to 60 minutes, expect numbers, and spend most of the time on deep dives. Walk through a question to see how a strong candidate paces the hour, sit the same question as a mock until you can produce the requirements, the estimates and the design without looking, then read the interview framework guide for how to structure the hour. The other questions on the site teach patterns that show up in Datadog interviews under different names.
Questions reported in Datadog system design interviews include Rate Limiter, Ad Click Aggregator, Distributed Job Scheduler, Metrics and Monitoring System, AWS Step Functions and Distributed Logging System. Between them they test algorithms, counters, redis, edge, stream processing and windowing. The reports come from public interview guides and candidate accounts, not from Datadog, so practise the patterns rather than memorising one list.
45–60 minutes in a drawing tool of your choice, often on high-volume data close to what the company runs: metrics or log ingestion, time-series storage, alerting. Some candidates report a general product prompt instead.
Reports say the Datadog round weighs 3 things. 1. Write-heavy ingestion: sustained throughput and what happens when traffic spikes. 2. Storage efficiency and query speed for time-series data. 3. Backpressure and failure handling along the pipeline. Reaching for a generic web-app template. On the data-shaped prompts, throughput, storage and query speed need to be in the design from the start, not added once the boxes are drawn.
Practise the questions reported there out loud, under a 45-minute clock: requirements with numbers first, then estimates, a high-level design, and deep dives into the two or three hardest parts. Start with Rate Limiter: watch a strong candidate answer it turn by turn, then sit it yourself. Then cover the patterns the round leans on (algorithms, counters, redis and edge) with one more question each.