Time-Series and Metrics Aggregation

Datadog ingests a firehose of tagged points and answers questions about time windows over it. The coding rounds mirror that work directly. Alongside the filesystem walk and the log matcher, the metrics family shows up as a small set of problems that all reduce to the same thing: group points by a key, then aggregate over a window. The reported version is a sliding-window count of events by tag, and it sits so close to the product that it is worth drilling on its own.

The code in each of these is short. What gets graded is whether you nail the contract before you type. A trailing window has a boundary you have to define, a rollup has a bucket rule that has to be exact, and a top-k has a tie-break that has to be deterministic. Commit to each one out loud, then the implementation is a single pass. This lesson works three runnable problems from that family, each an observability feature reframed as a coding prompt.

DatadogPremium lesson · Coding round

The 3 Datadog problems are below.

1. 1A Premium questionCoding · Easy
2. 2A Premium questionCoding · Medium
3. 3A Premium questionCoding · Medium

Each with hints, the follow-up and a tested solution.

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