Observability · Cluster
Metrics
Counters, histograms, and aggregation.
- 01 Counter Resets and the Extrapolation Inside rate() Why a monotonic counter loses its meaning when a process restarts, how reset detection reconstructs the increment, and what the edge extrapolation in a rate query assumes.
- 02 Scrape Interval, Lookback Delta, and the Resolution of a Rate How sampling period sets the highest frequency a rate graph can show, why aliasing turns a steady signal into a beat pattern, and what lookback staleness does at the edges.
- 03 Histogram Buckets, the +Inf Bucket, and How Quantiles Are Interpolated Why histograms store counts per bucket rather than values, how cumulative bucket counts make merging trivial, and what linear interpolation inside a bucket assumes about the distribution.
- 04 Aggregation Laws: Which Metric Operations Commute Why sums, counts, minimums and maximums survive regrouping while averages and percentiles do not, and how the order of rate and sum changes the answer.
- 05 Cardinality Explosion and Where It Comes From How label combinations multiply into series count, why an unbounded label value destroys an index, and which containment measures actually bound the growth.
- 06 Exponential Histograms and the Mergeable Bucket Layout How boundaries derived from a growth factor give uniform relative error, why an offset and a scale factor are enough to merge two histograms, and where the resolution limits sit.
- 07 Delta and Cumulative Temporality in Collection Pipelines How the two ways of reporting a sum interact with resets, why one is cheaper to transmit and the other cheaper to align, and how a pipeline converts between them without losing increments.
- 08 Recording Rules, Pre-Aggregation, and the Cost of Evaluating at Read Time Why the same query evaluated per-panel at render time multiplies work by viewers, how a pre-aggregated rule trades flexibility for a bounded cost, and what staleness the rule introduces.
- 09 Delta-of-Delta Timestamps and XOR Float Encoding on Disk How a time series block compresses to roughly two bytes per sample using a predictable timestamp pattern and the leading zeros of consecutive floats.
- 10 Label Matchers, Posting Lists, and How a Series Is Selected How the inverted index maps label pairs to series, why equality matchers intersect cheaply while regex matchers degrade to scans, and what the index cannot answer.