merge: Expose metrics directly to user (#80)

This pull request adds the ability to access the metrics of resources modeled
by the OpenDC Compute, Workflow, FaaS, and TensorFlow services directly from
their corresponding interfaces. Previously, users would have to interact with
OpenTelemetry to obtain these values, which is complex and provides
significant overhead.

With this pull request, users can access the metrics of all cloud resources
modeled by OpenDC via methods such as `getSchedulerStats()`, etc.

** Breaking Changes **

- `ComputeService.hostCount` removed in favour of `ComputeService.hosts.size`

2 files changed, 19 insertions, 10 deletions

diff --git a/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/ComputeServiceHelper.kt b/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/ComputeServiceHelper.kt
index 4b0b343f..21cfdad2 100644
--- a/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/ComputeServiceHelper.kt
+++ b/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/ComputeServiceHelper.kt
@@ -26,6 +26,7 @@ import kotlinx.coroutines.coroutineScope
 import kotlinx.coroutines.delay
 import kotlinx.coroutines.launch
 import kotlinx.coroutines.yield
+import org.opendc.compute.api.Server
 import org.opendc.compute.service.ComputeService
 import org.opendc.compute.service.scheduler.ComputeScheduler
 import org.opendc.compute.simulator.SimHost
@@ -81,9 +82,19 @@ public class ComputeServiceHelper(
     }
 
     /**
-     * Converge a simulation of the [ComputeService] by replaying the workload trace given by [trace].
+     * Run a simulation of the [ComputeService] by replaying the workload trace given by [trace].
+     *
+     * @param trace The trace to simulate.
+     * @param seed The seed for the simulation.
+     * @param servers A list to which the created servers is added.
+     * @param submitImmediately A flag to indicate that the servers are scheduled immediately (so not at their start time).
      */
-    public suspend fun run(trace: List<VirtualMachine>, seed: Long, submitImmediately: Boolean = false) {
+    public suspend fun run(
+        trace: List<VirtualMachine>,
+        seed: Long,
+        servers: MutableList<Server>? = null,
+        submitImmediately: Boolean = false
+    ) {
         val random = Random(seed)
         val injector = failureModel?.createInjector(context, clock, service, random)
         val client = service.newClient()
@@ -129,12 +140,14 @@ public class ComputeServiceHelper(
                             meta = mapOf("workload" to workload)
                         )
 
+                        servers?.add(server)
+
                         // Wait for the server reach its end time
                         val endTime = entry.stopTime.toEpochMilli()
                         delay(endTime + workloadOffset - clock.millis() + 5 * 60 * 1000)
 
-                        // Delete the server after reaching the end-time of the virtual machine
-                        server.delete()
+                        // Stop the server after reaching the end-time of the virtual machine
+                        server.stop()
                     }
                 }
             }
diff --git a/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/export/parquet/ParquetComputeMetricExporter.kt b/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/export/parquet/ParquetComputeMonitor.kt
index a46885f4..6c515118 100644
--- a/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/export/parquet/ParquetComputeMetricExporter.kt
+++ b/opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/export/parquet/ParquetComputeMonitor.kt
@@ -22,8 +22,6 @@
 
 package org.opendc.compute.workload.export.parquet
 
-import io.opentelemetry.sdk.common.CompletableResultCode
-import org.opendc.telemetry.compute.ComputeMetricExporter
 import org.opendc.telemetry.compute.ComputeMonitor
 import org.opendc.telemetry.compute.table.HostTableReader
 import org.opendc.telemetry.compute.table.ServerTableReader
@@ -33,7 +31,7 @@ import java.io.File
 /**
  * A [ComputeMonitor] that logs the events to a Parquet file.
  */
-public class ParquetComputeMetricExporter(base: File, partition: String, bufferSize: Int) : ComputeMetricExporter() {
+public class ParquetComputeMonitor(base: File, partition: String, bufferSize: Int) : ComputeMonitor, AutoCloseable {
     private val serverWriter = ParquetServerDataWriter(
         File(base, "server/$partition/data.parquet").also { it.parentFile.mkdirs() },
         bufferSize
@@ -61,11 +59,9 @@ public class ParquetComputeMetricExporter(base: File, partition: String, bufferS
         serviceWriter.write(reader)
     }
 
-    override fun shutdown(): CompletableResultCode {
+    override fun close() {
         hostWriter.close()
         serviceWriter.close()
         serverWriter.close()
-
-        return CompletableResultCode.ofSuccess()
     }
 }