Observability · Prometheus/Grafana interview questions

1. A.a Grafana view composed of panels visualizing metrics
2. B.the component that deduplicates, groups, and routes Prometheus alerts to receivers
3. C.a Service Level Objective, a target value or range for an SLI over a period
4. D.a numeric measurement of a system captured over time

Answer + AI explanation with Pro

1. A.Error budget
2. B.Metric
3. C.Counter
4. D.SLI

Answer + AI explanation with Pro

1. A.Metric — a Grafana view composed of panels visualizing metrics
2. B.Metric — a numeric measurement of a system captured over time
3. C.Metric — Prometheus's query language for selecting and aggregating time-series data
4. D.Metric — the allowed amount of unreliability derived from an SLO, spent before action is required

Answer + AI explanation with Pro

1. A.an excessive number of unique label-value combinations that overwhelms a metrics store
2. B.Prometheus pulling metrics from a target's HTTP endpoint at an interval
3. C.Prometheus's query language for selecting and aggregating time-series data
4. D.a metric type that can go up or down, like memory in use

Answer + AI explanation with Pro

1. A.Cardinality explosion
2. B.Error budget
3. C.Exporter
4. D.PromQL

Answer + AI explanation with Pro

1. A.PromQL — a Service Level Indicator, a quantitative measure of a service aspect like latency or error rate
2. B.PromQL — a metric type that only increases, used for totals like requests served
3. C.PromQL — Prometheus's query language for selecting and aggregating time-series data
4. D.PromQL — Prometheus pulling metrics from a target's HTTP endpoint at an interval

Answer + AI explanation with Pro

1. A.the component that deduplicates, groups, and routes Prometheus alerts to receivers
2. B.a Service Level Indicator, a quantitative measure of a service aspect like latency or error rate
3. C.a metric type that can go up or down, like memory in use
4. D.a component exposing third-party system metrics in Prometheus format

Answer + AI explanation with Pro

1. A.Alertmanager
2. B.Metric
3. C.Exporter
4. D.Histogram

Answer + AI explanation with Pro

1. A.Exporter — a numeric measurement of a system captured over time
2. B.Exporter — a Service Level Objective, a target value or range for an SLI over a period
3. C.Exporter — a component exposing third-party system metrics in Prometheus format
4. D.Exporter — a metric type bucketing observations to compute quantiles like latency percentiles

Answer + AI explanation with Pro

1. A.the allowed amount of unreliability derived from an SLO, spent before action is required
2. B.the component that deduplicates, groups, and routes Prometheus alerts to receivers
3. C.a metric type that only increases, used for totals like requests served
4. D.Prometheus pulling metrics from a target's HTTP endpoint at an interval

Answer + AI explanation with Pro

1. A.Exporter
2. B.Scrape
3. C.SLO
4. D.Dashboard

Answer + AI explanation with Pro

1. A.Scrape — a precomputed PromQL expression saved as a new time series for faster queries
2. B.Scrape — Prometheus pulling metrics from a target's HTTP endpoint at an interval
3. C.Scrape — an excessive number of unique label-value combinations that overwhelms a metrics store
4. D.Scrape — the component that deduplicates, groups, and routes Prometheus alerts to receivers

Answer + AI explanation with Pro

1. A.Prometheus pulling metrics from a target's HTTP endpoint at an interval
2. B.a Grafana view composed of panels visualizing metrics
3. C.a metric type bucketing observations to compute quantiles like latency percentiles
4. D.the component that deduplicates, groups, and routes Prometheus alerts to receivers

Answer + AI explanation with Pro

1. A.Dashboard
2. B.Alertmanager
3. C.Histogram
4. D.SLI

Answer + AI explanation with Pro

1. A.Dashboard — Prometheus pulling metrics from a target's HTTP endpoint at an interval
2. B.Dashboard — an excessive number of unique label-value combinations that overwhelms a metrics store
3. C.Dashboard — a precomputed PromQL expression saved as a new time series for faster queries
4. D.Dashboard — a Grafana view composed of panels visualizing metrics

Answer + AI explanation with Pro

1. A.an excessive number of unique label-value combinations that overwhelms a metrics store
2. B.a metric type that only increases, used for totals like requests served
3. C.Prometheus's query language for selecting and aggregating time-series data
4. D.a metric type bucketing observations to compute quantiles like latency percentiles

Answer + AI explanation with Pro

1. A.Counter
2. B.Cardinality explosion
3. C.Error budget
4. D.Exporter

Answer + AI explanation with Pro

1. A.Counter — the component that deduplicates, groups, and routes Prometheus alerts to receivers
2. B.Counter — a metric type that only increases, used for totals like requests served
3. C.Counter — a Service Level Indicator, a quantitative measure of a service aspect like latency or error rate
4. D.Counter — a component exposing third-party system metrics in Prometheus format

Answer + AI explanation with Pro

1. A.a metric type bucketing observations to compute quantiles like latency percentiles
2. B.a component exposing third-party system metrics in Prometheus format
3. C.the allowed amount of unreliability derived from an SLO, spent before action is required
4. D.a metric type that can go up or down, like memory in use

Answer + AI explanation with Pro

1. A.Histogram
2. B.Exporter
3. C.Gauge
4. D.Scrape

Answer + AI explanation with Pro

1. A.Gauge — a metric type that can go up or down, like memory in use
2. B.Gauge — the allowed amount of unreliability derived from an SLO, spent before action is required
3. C.Gauge — a component exposing third-party system metrics in Prometheus format
4. D.Gauge — a metric type that only increases, used for totals like requests served

Answer + AI explanation with Pro

1. A.Prometheus pulling metrics from a target's HTTP endpoint at an interval
2. B.a component exposing third-party system metrics in Prometheus format
3. C.a metric type bucketing observations to compute quantiles like latency percentiles
4. D.the allowed amount of unreliability derived from an SLO, spent before action is required

Answer + AI explanation with Pro

1. A.Counter
2. B.Metric
3. C.PromQL
4. D.Histogram

Answer + AI explanation with Pro

1. A.Histogram — the component that deduplicates, groups, and routes Prometheus alerts to receivers
2. B.Histogram — a metric type bucketing observations to compute quantiles like latency percentiles
3. C.Histogram — a Service Level Indicator, a quantitative measure of a service aspect like latency or error rate
4. D.Histogram — a metric type that only increases, used for totals like requests served

Answer + AI explanation with Pro

1. A.the component that deduplicates, groups, and routes Prometheus alerts to receivers
2. B.a Service Level Objective, a target value or range for an SLI over a period
3. C.a numeric measurement of a system captured over time
4. D.the allowed amount of unreliability derived from an SLO, spent before action is required

Answer + AI explanation with Pro

1. A.SLI
2. B.Alertmanager
3. C.Gauge
4. D.Counter

Answer + AI explanation with Pro

1. A.Alertmanager — a metric type bucketing observations to compute quantiles like latency percentiles
2. B.Alertmanager — the component that deduplicates, groups, and routes Prometheus alerts to receivers
3. C.Alertmanager — Prometheus's query language for selecting and aggregating time-series data
4. D.Alertmanager — an excessive number of unique label-value combinations that overwhelms a metrics store

Answer + AI explanation with Pro

1. A.a precomputed PromQL expression saved as a new time series for faster queries
2. B.an excessive number of unique label-value combinations that overwhelms a metrics store
3. C.a metric type that only increases, used for totals like requests served
4. D.a component exposing third-party system metrics in Prometheus format

Answer + AI explanation with Pro

1. A.PromQL
2. B.Recording rule
3. C.Cardinality explosion
4. D.SLI

Answer + AI explanation with Pro

1. A.Recording rule — a metric type that can go up or down, like memory in use
2. B.Recording rule — a Grafana view composed of panels visualizing metrics
3. C.Recording rule — a Service Level Objective, a target value or range for an SLI over a period
4. D.Recording rule — a precomputed PromQL expression saved as a new time series for faster queries

Answer + AI explanation with Pro