///|
/// A named metric series with bounded event-time retention.
pub struct ProductionMetricSeries {
name : String
unit : String
window : ProductionTimeWindow
mut updates : Int
mut invalid : Int
}
///|
pub fn ProductionMetricSeries::new(
name : String,
unit? : String = "",
capacity? : Int = 512,
) -> ProductionMetricSeries {
{
name,
unit,
window: ProductionTimeWindow::new(capacity~),
updates: 0,
invalid: 0,
}
}
///|
pub fn ProductionMetricSeries::name(self : ProductionMetricSeries) -> String {
self.name
}
///|
pub fn ProductionMetricSeries::unit(self : ProductionMetricSeries) -> String {
self.unit
}
///|
pub fn ProductionMetricSeries::updates(self : ProductionMetricSeries) -> Int {
self.updates
}
///|
pub fn ProductionMetricSeries::invalid(self : ProductionMetricSeries) -> Int {
self.invalid
}
///|
pub fn ProductionMetricSeries::push(
self : ProductionMetricSeries,
sample : ProductionSample,
) -> Bool {
self.updates += 1
if !is_finite(sample.value()) {
self.invalid += 1
false
} else {
ignore(self.window.push(sample))
true
}
}
///|
pub fn ProductionMetricSeries::push_point(
self : ProductionMetricSeries,
point : SignalPoint,
) -> Bool {
self.push(
ProductionSample::new(point.timestamp, point.value, sequence=point.sequence),
)
}
///|
pub fn ProductionMetricSeries::window(
self : ProductionMetricSeries,
) -> ProductionTimeWindow {
self.window
}
///|
pub fn ProductionMetricSeries::values(
self : ProductionMetricSeries,
) -> Array[Double] {
self.window.values()
}
///|
pub fn ProductionMetricSeries::summary(
self : ProductionMetricSeries,
) -> ProductionWindowSummary {
self.window.summary()
}
///|
pub fn ProductionMetricSeries::latest(
self : ProductionMetricSeries,
) -> ProductionSample? {
self.window.last()
}
///|
pub fn ProductionMetricSeries::correlation(
self : ProductionMetricSeries,
other : ProductionMetricSeries,
) -> Double {
correlation(self.values(), other.values())
}
///|
pub fn ProductionMetricSeries::change_score(
self : ProductionMetricSeries,
split : Int,
) -> Double {
self.window.rolling_change(split)
}
///|
/// A deterministic collection of named series for multimetric monitoring.
pub struct ProductionMetricCatalog {
series : Array[ProductionMetricSeries]
mut ingested : Int
mut rejected : Int
}
///|
pub fn ProductionMetricCatalog::new() -> ProductionMetricCatalog {
{ series: [], ingested: 0, rejected: 0 }
}
///|
pub fn ProductionMetricCatalog::register(
self : ProductionMetricCatalog,
metric : ProductionMetricSeries,
) -> Bool {
for existing in self.series {
if existing.name() == metric.name() {
return false
}
}
self.series.push(metric)
true
}
///|
pub fn ProductionMetricCatalog::metric_count(
self : ProductionMetricCatalog,
) -> Int {
self.series.length()
}
///|
pub fn ProductionMetricCatalog::names(
self : ProductionMetricCatalog,
) -> Array[String] {
let result : Array[String] = []
for metric in self.series {
result.push(metric.name())
}
result
}
///|
pub fn ProductionMetricCatalog::find(
self : ProductionMetricCatalog,
name : String,
) -> ProductionMetricSeries? {
for metric in self.series {
if metric.name() == name {
return Some(metric)
}
}
None
}
///|
pub fn ProductionMetricCatalog::ingest(
self : ProductionMetricCatalog,
name : String,
sample : ProductionSample,
) -> Bool {
self.ingested += 1
match self.find(name) {
None => {
self.rejected += 1
false
}
Some(metric) => {
let accepted = metric.push(sample)
if !accepted {
self.rejected += 1
}
accepted
}
}
}
///|
pub fn ProductionMetricCatalog::ingest_point(
self : ProductionMetricCatalog,
name : String,
point : SignalPoint,
) -> Bool {
self.ingest(
name,
ProductionSample::new(point.timestamp, point.value, sequence=point.sequence),
)
}
///|
pub fn ProductionMetricCatalog::ingested(self : ProductionMetricCatalog) -> Int {
self.ingested
}
///|
pub fn ProductionMetricCatalog::rejected(self : ProductionMetricCatalog) -> Int {
self.rejected
}
///|
pub fn ProductionMetricCatalog::series(
self : ProductionMetricCatalog,
) -> Array[ProductionMetricSeries] {
let result : Array[ProductionMetricSeries] = []
for metric in self.series {
result.push(metric)
}
result
}
///|
/// Cross-series relation used to prioritize correlated incidents.
pub struct ProductionMetricRelation {
left : String
right : String
correlation : Double
distance : Double
related : Bool
}
///|
pub fn ProductionMetricRelation::left(
self : ProductionMetricRelation,
) -> String {
self.left
}
///|
pub fn ProductionMetricRelation::right(
self : ProductionMetricRelation,
) -> String {
self.right
}
///|
pub fn ProductionMetricRelation::correlation(
self : ProductionMetricRelation,
) -> Double {
self.correlation
}
///|
pub fn ProductionMetricRelation::distance(
self : ProductionMetricRelation,
) -> Double {
self.distance
}
///|
pub fn ProductionMetricRelation::related(
self : ProductionMetricRelation,
) -> Bool {
self.related
}
///|
pub fn ProductionMetricCatalog::relations(
self : ProductionMetricCatalog,
correlation_threshold? : Double = 0.7,
) -> Array[ProductionMetricRelation] {
let result : Array[ProductionMetricRelation] = []
let threshold = if correlation_threshold < 0.0 {
0.0
} else {
correlation_threshold
}
for i in 0..= threshold,
})
}
}
result
}
///|
/// A synchronized row across several metric series.
pub struct ProductionMetricFrame {
timestamp : Int64
names : Array[String]
values : Array[Double]
valid : Array[Bool]
}
///|
pub fn ProductionMetricFrame::new(
timestamp : Int64,
names : Array[String],
values : Array[Double],
) -> ProductionMetricFrame {
let valid : Array[Bool] = []
for value in values {
valid.push(is_finite(value))
}
{ timestamp, names, values, valid }
}
///|
pub fn ProductionMetricFrame::timestamp(self : ProductionMetricFrame) -> Int64 {
self.timestamp
}
///|
pub fn ProductionMetricFrame::names(
self : ProductionMetricFrame,
) -> Array[String] {
let result : Array[String] = []
for name in self.names {
result.push(name)
}
result
}
///|
pub fn ProductionMetricFrame::values(
self : ProductionMetricFrame,
) -> Array[Double] {
let result : Array[Double] = []
for value in self.values {
result.push(value)
}
result
}
///|
pub fn ProductionMetricFrame::valid_count(self : ProductionMetricFrame) -> Int {
let mut count = 0
for value in self.valid {
if value {
count += 1
}
}
count
}
///|
pub fn ProductionMetricFrame::dimension(self : ProductionMetricFrame) -> Int {
self.values.length()
}
///|
pub fn ProductionMetricFrame::is_complete(self : ProductionMetricFrame) -> Bool {
self.valid_count() == self.values.length()
}
///|
/// Builds frames by joining series at the nearest timestamp within a tolerance.
pub fn production_join_series(
series : Array[ProductionMetricSeries],
tolerance : Int64,
) -> Array[ProductionMetricFrame] {
let result : Array[ProductionMetricFrame] = []
if series.length() == 0 {
return result
}
let first = series[0].window().to_array()
let names : Array[String] = []
for metric in series {
names.push(metric.name())
}
for anchor in first {
let values : Array[Double] = [anchor.value()]
for i in 1.. values.push(0.0)
Some(sample) => values.push(sample.value())
}
}
result.push(ProductionMetricFrame::new(anchor.timestamp(), names, values))
}
result
}
///|
fn production_nearest_sample(
samples : Array[ProductionSample],
timestamp : Int64,
tolerance : Int64,
) -> ProductionSample? {
let mut result : ProductionSample? = None
let mut best_distance = 9223372036854775807L
for sample in samples {
let distance = absolute((sample.timestamp() - timestamp).to_double()).to_int64()
if distance <= tolerance && distance < best_distance {
best_distance = distance
result = Some(sample)
}
}
result
}
///|
/// Computes vector-level changes over synchronized frames.
pub fn production_frame_change_score(
before : ProductionMetricFrame,
after : ProductionMetricFrame,
) -> Double {
let left = before.values()
let right = after.values()
let n = if left.length() < right.length() {
left.length()
} else {
right.length()
}
if n == 0 {
return 0.0
}
let mut total = 0.0
for i in 0.. ProductionCatalogSummary {
let names : Array[String] = []
let means : Array[Double] = []
let variances : Array[Double] = []
let counts : Array[Int] = []
let quality : Array[Double] = []
for metric in self.series {
let summary = metric.summary()
names.push(metric.name())
means.push(summary.mean())
variances.push(summary.variance())
counts.push(summary.count())
quality.push(summary.quality_ratio())
}
{ names, means, variances, counts, quality }
}
///|
pub fn ProductionCatalogSummary::names(
self : ProductionCatalogSummary,
) -> Array[String] {
let result : Array[String] = []
for name in self.names {
result.push(name)
}
result
}
///|
pub fn ProductionCatalogSummary::means(
self : ProductionCatalogSummary,
) -> Array[Double] {
let result : Array[Double] = []
for value in self.means {
result.push(value)
}
result
}
///|
pub fn ProductionCatalogSummary::variances(
self : ProductionCatalogSummary,
) -> Array[Double] {
let result : Array[Double] = []
for value in self.variances {
result.push(value)
}
result
}
///|
pub fn ProductionCatalogSummary::counts(
self : ProductionCatalogSummary,
) -> Array[Int] {
let result : Array[Int] = []
for value in self.counts {
result.push(value)
}
result
}
///|
pub fn ProductionCatalogSummary::quality(
self : ProductionCatalogSummary,
) -> Array[Double] {
let result : Array[Double] = []
for value in self.quality {
result.push(value)
}
result
}
///|
pub fn ProductionCatalogSummary::markdown(
self : ProductionCatalogSummary,
) -> String {
let mut output = "| metric | count | mean | variance | quality |\n|---|---:|---:|---:|---:|\n"
for i in 0.. Double {
if snapshots.length() == 0 {
return 1.0
}
let mut total = 0.0
for snapshot in snapshots {
let state_score = match snapshot.state() {
ColdStart => 0.5
Healthy => 1.0
DegradedQuality => 0.4
AlertingState => 0.2
RecoveringState => 0.6
DisabledState => 0.0
}
total += state_score * snapshot.quality_ratio()
}
total / snapshots.length().to_double()
}
///|
pub fn production_fleet_health_label(score : Double) -> String {
if score >= 0.9 {
"healthy"
} else if score >= 0.6 {
"watch"
} else {
"at-risk"
}
}