<Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>
<Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Updates the metric with the specified input.
Details
The behavior of update depends on the metric type. Counters add the input
value to the current count, gauges replace the current value with the input
value, frequencies increment the occurrence count for the input string,
histograms record the input value in the appropriate bucket, and summaries
record the input value as a new observation.
Example (Updating metric values)
import { Effect, Metric } from "effect"
const cpuUsage = Metric.gauge("cpu_usage_percent")
const httpStatus = Metric.frequency("http_status_codes")
const responseTime = Metric.histogram("response_time_ms", {
boundaries: [100, 500, 1000, 2000]
})
const program = Effect.gen(function*() {
// Update gauge to specific values
yield* Metric.update(cpuUsage, 45.2)
yield* Metric.update(cpuUsage, 67.8) // Replaces previous value
// Track HTTP status code occurrences
yield* Metric.update(httpStatus, "200")
yield* Metric.update(httpStatus, "404")
yield* Metric.update(httpStatus, "200") // Increments 200 count
// Record response times
yield* Metric.update(responseTime, 250)
yield* Metric.update(responseTime, 750)
yield* Metric.update(responseTime, 1500)
// Check current states
const cpu = yield* Metric.value(cpuUsage)
const statuses = yield* Metric.value(httpStatus)
const times = yield* Metric.value(responseTime)
console.log(`CPU Usage: ${cpu.value}%`)
console.log(`Status 200 count: ${statuses.occurrences.get("200")}`) // 2
console.log(`Response time samples: ${times.count}`) // 3
})export const const update: {
<Input>(input: Input): <State>(
self: Metric<Input, State>
) => Effect<void>
<Input, State>(
self: Metric<Input, State>,
input: Input
): Effect<void>
}
Updates the metric with the specified input.
Details
The behavior of update depends on the metric type. Counters add the input
value to the current count, gauges replace the current value with the input
value, frequencies increment the occurrence count for the input string,
histograms record the input value in the appropriate bucket, and summaries
record the input value as a new observation.
Example (Updating metric values)
import { Effect, Metric } from "effect"
const cpuUsage = Metric.gauge("cpu_usage_percent")
const httpStatus = Metric.frequency("http_status_codes")
const responseTime = Metric.histogram("response_time_ms", {
boundaries: [100, 500, 1000, 2000]
})
const program = Effect.gen(function*() {
// Update gauge to specific values
yield* Metric.update(cpuUsage, 45.2)
yield* Metric.update(cpuUsage, 67.8) // Replaces previous value
// Track HTTP status code occurrences
yield* Metric.update(httpStatus, "200")
yield* Metric.update(httpStatus, "404")
yield* Metric.update(httpStatus, "200") // Increments 200 count
// Record response times
yield* Metric.update(responseTime, 250)
yield* Metric.update(responseTime, 750)
yield* Metric.update(responseTime, 1500)
// Check current states
const cpu = yield* Metric.value(cpuUsage)
const statuses = yield* Metric.value(httpStatus)
const times = yield* Metric.value(responseTime)
console.log(`CPU Usage: ${cpu.value}%`)
console.log(`Status 200 count: ${statuses.occurrences.get("200")}`) // 2
console.log(`Response time samples: ${times.count}`) // 3
})
update: {
<function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input>(input: Inputinput: function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input): <function (type parameter) State in <State>(self: Metric<Input, State>): Effect<void>State>(self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self: interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input, function (type parameter) State in <State>(self: Metric<Input, State>): Effect<void>State>) => import EffectEffect<void>
<function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input, function (type parameter) State in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>State>(self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self: interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input, function (type parameter) State in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>State>, input: Inputinput: function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input): import EffectEffect<void>
} = import dualdual<
<function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input>(input: Inputinput: function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input) => <function (type parameter) State in <State>(self: Metric<Input, State>): Effect<void>State>(self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self: interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <Input>(input: Input): <State>(self: Metric<Input, State>) => Effect<void>Input, function (type parameter) State in <State>(self: Metric<Input, State>): Effect<void>State>) => import EffectEffect<void>,
<function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input, function (type parameter) State in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>State>(self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self: interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input, function (type parameter) State in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>State>, input: Inputinput: function (type parameter) Input in <Input, State>(self: Metric<Input, State>, input: Input): Effect<void>Input) => import EffectEffect<void>
>(
2,
(self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self, input: anyinput) =>
import InternalEffectInternalEffect.const contextWith: <R, A, E, R2>(
f: (
context: Context.Context<R>
) => Effect.Effect<A, E, R2>
) => Effect.Effect<A, E, R | R2>
contextWith((services: Context.Context<never>(parameter) services: {
mapUnsafe: ReadonlyMap<string, any>;
mutable: boolean;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
services) => import InternalEffectInternalEffect.const sync: <A>(
thunk: LazyArg<A>
) => Effect.Effect<A>
sync(() => self: Metric<Input, State>(parameter) self: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
self.updateUnsafe(input: anyinput, services: Context.Context<never>(parameter) services: {
mapUnsafe: ReadonlyMap<string, any>;
mutable: boolean;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
services)))
)