mexporter ai 장착 1차 - ai server, models

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,10 @@
+### Description
+
+> 한줄요약
+
+<br>
+
+### Changes
+
+- changes
+-

README.md

@@ -1,7 +1,7 @@
-## monilab-exporter-ex
+## mexporter
 
-monilab exporter ex는 exporter 개발 이전 
+> made by intelliegence-lab
 
-exporter의 요구사항을 파악하기 위한, (+알아야할 범위를 좁히기 위한) 예제 서버입니다.
+monilab - jvm exporter service
 
-차후 예제 서버 결과를 토대로 별도의 exporter를 개발하고 ga할 예정
+(jvm monitoring, ai agent)

ai/build.gradle.kts

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+plugins {
+    kotlin("jvm")
+    kotlin("plugin.spring")
+    id("org.springframework.boot") version "3.5.5"
+    id("io.spring.dependency-management") version "1.1.7"
+    id("org.jlleitschuh.gradle.ktlint") version "12.1.0"
+    application
+}
+
+java {
+    toolchain {
+        languageVersion.set(JavaLanguageVersion.of(17))
+    }
+}
+
+dependencies {
+    implementation("org.springframework.boot:spring-boot-starter-web")
+    implementation("org.springframework.boot:spring-boot-starter-actuator")
+    implementation("com.fasterxml.jackson.module:jackson-module-kotlin:2.18.2")
+    implementation("org.jetbrains.kotlin:kotlin-reflect")
+    implementation("org.jetbrains.kotlinx:kotlinx-coroutines-core:1.8.1")
+
+    implementation(project(":exporter"))
+
+    implementation("com.github.haifengl:smile-core:2.6.0")
+    implementation("com.github.haifengl:smile-plot:2.6.0")
+
+    testImplementation("org.springframework.boot:spring-boot-starter-test")
+    testImplementation("org.jetbrains.kotlin:kotlin-test-junit5")
+    testRuntimeOnly("org.junit.platform:junit-platform-launcher")
+}
+
+tasks.withType<Test> {
+    useJUnitPlatform()
+}
+
+ktlint {
+    filter {
+        exclude { entry -> entry.file.path.contains("src/test/") }
+    }
+}
+
+tasks.withType<org.jlleitschuh.gradle.ktlint.tasks.GenerateReportsTask> {
+    if (name.contains("TestSourceSet")) {
+        enabled = false
+    }
+}
+
+tasks.named("ktlintCheck") {
+    enabled = false
+}
+tasks.named("ktlintMainSourceSetCheck") {
+    enabled = false
+}

ai/src/main/kotlin/lab/Application.kt

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+package lab
+
+import org.springframework.boot.autoconfigure.SpringBootApplication
+import org.springframework.boot.runApplication
+
+@SpringBootApplication
+class Application
+
+fun main(args: Array<String>) {
+    runApplication<Application>(*args)
+}
+

ai/src/main/kotlin/lab/ai-model/gc/GcFeatureExtractor.kt

@@ -0,0 +1,22 @@
+package lab.`ai-model`.gc
+
+
+object GcFeatureExtractor {
+    private val gcStrategyMap = mapOf(
+        "G1" to 0.0,
+        "Parallel" to 1.0,
+        "Serial" to 2.0,
+        "ZGC" to 3.0
+    )
+
+    fun extract(gc: GcTrainData): DoubleArray {
+        return doubleArrayOf(
+            gc.count.toDouble(),
+            gc.time.toDouble(),
+            gc.pause.toDouble(),
+            gc.allocationRate,
+            gc.liveDataSize.toDouble(),
+            gcStrategyMap[gc.gcStrategy] ?: -1.0
+        )
+    }
+}

ai/src/main/kotlin/lab/ai-model/gc/GcTrainData.kt

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+package lab.`ai-model`.gc
+
+data class GcTrainData(
+    val count: Long,
+    val time: Long,
+    val pause: Long,
+    val allocationRate: Double,
+    val liveDataSize: Long,
+    val gcStrategy: String,
+    val label: Int // 1 정상, 0 비정상
+)

ai/src/main/kotlin/lab/ai-model/gc/GcTrainer.kt

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+package lab.`ai-model`.gc
+
+import org.slf4j.LoggerFactory
+import org.springframework.stereotype.Component
+import smile.classification.LogisticRegression
+import smile.data.DataFrame
+import smile.data.formula.Formula
+import smile.data.vector.DoubleVector
+import smile.data.vector.IntVector
+import java.io.File
+import java.io.ObjectOutputStream
+
+@Component
+class GcTrainer {
+    private val extractor: GcFeatureExtractor by lazy { GcFeatureExtractor }
+    private var model: LogisticRegression? = null
+    private val log = LoggerFactory.getLogger(GcTrainer::class.java)
+
+    private val projectRootDir: String = System.getProperty("user.dir")
+    private val modelDir = File("$projectRootDir/ai-models/gc-model").apply { mkdirs() }
+
+    fun train() {
+        log.info("Start GcTrainer training...")
+        val dataList = getDataList()
+        if (dataList.isEmpty()) {
+            log.warn("No data available for training.")
+            return
+        }
+
+        log.info("Training data size: ${dataList.size}")
+        log.info("Sample training data: ${dataList.take(3)}")
+
+        val features = dataList.map { extractor.extract(it) }.toTypedArray()
+        val labels = dataList.map { it.label }.toIntArray()
+        val df = DataFrame.of(
+            DoubleVector.of("count", features.map { it[0] }.toDoubleArray()),
+            DoubleVector.of("time", features.map { it[1] }.toDoubleArray()),
+            DoubleVector.of("pause", features.map { it[2] }.toDoubleArray()),
+            DoubleVector.of("allocationRate", features.map { it[3] }.toDoubleArray()),
+            DoubleVector.of("liveDataSize", features.map { it[4] }.toDoubleArray()),
+            DoubleVector.of("gcStrategy", features.map { it[5] }.toDoubleArray()),
+            IntVector.of("label", labels)
+        )
+
+        val formula = Formula.lhs("label")
+        model = LogisticRegression.fit(formula, df)
+        log.info("GcTrainer training completed.")
+
+        saveModel("train")
+        saveModel("test")
+    }
+
+    private fun saveModel(key: String) {
+        val m = model ?: run {
+            log.error("Model not trained. Cannot save [$key].")
+            return
+        }
+
+        val file = File(modelDir, "gc_$key.model")
+
+        ObjectOutputStream(file.outputStream().buffered()).use { oos ->
+            oos.writeObject(m)
+        }
+
+        log.info("💾 Saved model [$key] → ${file.absolutePath}")
+    }
+
+    private fun getDataList(): List<GcTrainData> {
+        // TODO - khope heesung이 만들어준 data get에서 가져와쓰는걸로 수정
+        return listOf(
+            GcTrainData(100, 400, 30, 1.2, 300_000, "G1", label = 1),
+            GcTrainData(150, 700, 300, 3.8, 1_000_000, "G1", label = 0),
+            GcTrainData(80, 250, 15, 0.8, 200_000, "Parallel", label = 1),
+            GcTrainData(400, 1200, 700, 6.2, 2_000_000, "G1", label = 0),
+            GcTrainData(90, 320, 20, 1.5, 350_000, "Serial", label = 1)
+        )
+    }
+}

ai/src/main/kotlin/lab/api/ApiController.kt

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+package lab.api
+
+import lab.`ai-model`.gc.GcTrainer
+import org.springframework.web.bind.annotation.GetMapping
+import org.springframework.web.bind.annotation.RestController
+
+@RestController
+class ApiController(
+    private val gcTrainer: GcTrainer
+) {
+
+    @GetMapping("/api/train")
+    fun train() {
+        gcTrainer.train()
+    }
+}

cli/build.gradle.kts

@@ -8,7 +8,7 @@ plugins {
 
 java {
     toolchain {
-        languageVersion = JavaLanguageVersion.of(17)
+        languageVersion.set(JavaLanguageVersion.of(17))
     }
 }
 

exporter/build.gradle.kts

@@ -7,7 +7,7 @@ plugins {
 
 java {
     toolchain {
-        languageVersion = JavaLanguageVersion.of(17)
+        languageVersion.set(JavaLanguageVersion.of(17))
     }
 }
 

settings.gradle.kts

@@ -1,3 +1,4 @@
 rootProject.name = "monilab-exporter-ex"
 include(":exporter")
 include(":cli")
+include(":ai")