Telemetry & Time Series interview questions

High-cardinality sensor data, downsampling, retention and edge buffering.

3 questions in Manufacturing & Industrial IoT.

Manufacturing and Industrial IoTA 21-minute read on how the topic fits together, before the questions.Manufacturing and industrial IoT fundamentals58 short answers on one page, for revising rather than studying.

hard3

hardDesign

Design the ingestion path for sensor telemetry from a few hundred machines. Which decisions matter most?

Size the stream from stated assumptions, keep series identity narrow so cardinality stays bounded, choose sampling deliberately and downsample keeping min, max and count rather than means alone, tier retention, and buffer at the edge with a bounded queue and a rate-limited drain. Use this time series answer to show the decision, trade-off, and evidence rather than a memorised definition.

6 minmid, senior, staff

hardDesignScenario

Five months after a machine failure, an engineer asks you for the high-rate data around it. Was your retention policy right?

Retention is a bet about which questions get asked later, and averaging is the bet that loses, because the transient that explains a failure disappears into a mean. Keep min, max and count per bucket rather than an average, and let events freeze a window of full-rate data at the edge.

7 minmid, senior, staff

hardScenarioDesign

One machine's clock is ninety seconds ahead of the rest of the plant. Which of your numbers are wrong, and how would you have found out?

Every derived figure that joins on time is affected, and none of them error. Duration and attribution metrics take the skew directly, so a shift with twelve stops mis-measures availability by nearly four points, and only storing both event time and ingestion time makes the offset visible.

7 minmid, senior, staff