Kotlin Application Monitoring: Libraries and Tools for Performance Tracking

Kotlin Application Monitoring: A Complete Overview of Libraries and Tools

Modern Kotlin applications require constant monitoring of performance, availability, and stability. Monitoring allows you to timely identify bottlenecks, prevent failures, and optimize resources. In this article, we will review key libraries and tools for monitoring Kotlin applications, including Micrometer, Kotlin Metrics, and OpenTelemetry, with practical code examples.

Why Monitor Kotlin Applications?

Monitoring provides answers to critically important questions:

• Performance: request execution time, CPU load, memory usage.
• Availability: error rate, service uptime.
• Load: number of active sessions, RPS (requests per second).
• Business metrics: number of registrations, conversions, orders.

Without monitoring, you risk learning about a problem only from users — and by then it's already too late.

Key Monitoring Libraries

1. Micrometer

Micrometer is the de facto standard for collecting metrics in the JVM ecosystem. It supports Kotlin through Java interop and provides a unified API for sending metrics to Prometheus, Datadog, Graphite, New Relic, and other systems.

Installation (Gradle):

dependencies {    implementation("io.micrometer:micrometer-core:1.12.0")    implementation("io.micrometer:micrometer-registry-prometheus:1.12.0")}

Usage example in Kotlin:

import io.micrometer.core.instrument.MeterRegistryimport io.micrometer.core.instrument.simple.SimpleMeterRegistry

val registry: MeterRegistry = SimpleMeterRegistry()

// Counterval requestCounter = registry.counter("api.requests", "endpoint", "/users")requestCounter.increment()

// Timerval requestTimer = registry.timer("api.response.time", "endpoint", "/users")requestTimer.record {    // code measuring execution time    Thread.sleep(100)}

// Hybrid approach with Prometheus// PrometheusMeterRegistry prometheusRegistry = new PrometheusMeterRegistry(...)

Micrometer integrates with Spring Boot, Ktor, and other frameworks, making it a versatile choice.

2. Kotlin Metrics

Kotlin Metrics is a lightweight library written in Kotlin from scratch. It offers DSL syntax familiar to Kotlin developers and does not require Java dependencies.

Installation:

dependencies {    implementation("com.github.kshired:kotlin-metrics:1.0.0")}

Example:

import com.github.kshired.metrics.*

val metrics = Metrics()

// Counterval counter = metrics.counter("errors.total")counter.inc()

// Tagged counterval taggedCounter = metrics.counter("db.queries", "type" to "select")taggedCounter.inc()

// Timerval timer = metrics.timer("request.latency")timer.record {    // business logic}

The library supports export to Prometheus and JSON, which is convenient for microservices.

3. OpenTelemetry

OpenTelemetry is a powerful tool for tracing and monitoring distributed systems. It includes collection of metrics, logs, and traces. The Kotlin SDK for OpenTelemetry allows easy integration into Ktor and Spring applications.

Installation:

dependencies {    implementation("io.opentelemetry:opentelemetry-api:1.35.0")    implementation("io.opentelemetry:opentelemetry-sdk:1.35.0")    implementation("io.opentelemetry:opentelemetry-exporter-otlp:1.35.0")}

Example of creating a metric:

import io.opentelemetry.api.OpenTelemetryimport io.opentelemetry.api.metrics.Meter

val openTelemetry: OpenTelemetry = OpenTelemetry.