Merge branch 'theodolite-kotlin' of git.se.informatik.uni-kiel.de:she/spesb...

Merge branch 'theodolite-kotlin' of git.se.informatik.uni-kiel.de:she/spesb into 144-document-image-build

.gitlab-ci.yml

@@ -242,6 +242,7 @@ build-theodolite-native:
   script:
     - gu install native-image # TODO move to image
     - ./gradlew --build-cache assemble -Dquarkus.package.type=native
+  when: manual
   artifacts:
     paths:
       - "theodolite-quarkus/build/*-runner"
@@ -252,7 +253,7 @@ test-theodolite:
   extends: .theodolite
   needs:
     - build-theodolite-jvm
-    - build-theodolite-native
+    #- build-theodolite-native
   script: ./gradlew test --stacktrace
 
 # Disabled for now
@@ -279,12 +280,13 @@ deploy-theodolite:
     - .theodolite
     - .dind
   needs:
-    - build-theodolite-native
+    #- build-theodolite-native
+    - build-theodolite-jvm
     - test-theodolite
   script:
     - DOCKER_TAG_NAME=$(echo $CI_COMMIT_REF_SLUG- | sed 's/^master-$//')
-    - docker build -f src/main/docker/Dockerfile.native -t theodolite .
-    #- docker build -f src/main/docker/Dockerfile.jvm -t theodolite .
+    #- docker build -f src/main/docker/Dockerfile.native -t theodolite .
+    - docker build -f src/main/docker/Dockerfile.jvm -t theodolite .
     - "[ ! $CI_COMMIT_TAG ] && docker tag theodolite $CR_HOST/$CR_ORG/theodolite:${DOCKER_TAG_NAME}latest"
     - "[ ! $CI_COMMIT_TAG ] && docker tag theodolite $CR_HOST/$CR_ORG/theodolite:$DOCKER_TAG_NAME$CI_COMMIT_SHORT_SHA"
     - "[ $CI_COMMIT_TAG ] && docker tag theodolite $CR_HOST/$CR_ORG/theodolite:$CI_COMMIT_TAG"
@@ -309,6 +311,7 @@ deploy-slo-checker-lag-trend:
   stage: deploy
   extends:
     - .dind
+  needs: []
   script:
     - DOCKER_TAG_NAME=$(echo $CI_COMMIT_REF_SLUG- | sed 's/^master-$//')
     - docker build --pull -t theodolite-slo-checker-lag-trend slope-evaluator
@@ -335,6 +338,7 @@ deploy-random-scheduler:
   stage: deploy
   extends:
     - .dind
+  needs: []
   script:
     - DOCKER_TAG_NAME=$(echo $CI_COMMIT_REF_SLUG- | sed 's/^master-$//')
     - docker build --pull -t theodolite-random-scheduler execution/infrastructure/random-scheduler

execution/README.md

@@ -225,7 +225,17 @@ Theodolite locally on your machine see the description below.
 see the [Configuration](#configuration) section below. Note, that you might uncomment the `serviceAccountName` line if
 RBAC is enabled on your cluster (see installation of [Theodolite RBAC](#Theodolite-RBAC)).
 
-To start the execution of a benchmark run (with `<your-theodolite-yaml>` being your job definition):
+To start the execution of a benchmark create a ConfigMap which containts all required Kubernetes resource files for the SUT and the load generator, a ConfigMap for the execution and a ConfigMap for the benchmark.
+
+```sh
+kubectl create configmap app-resources-configmap --from-file=<folder-with-all-required-k8s-resources>
+kubectl create configmap execution-configmap --from-file=<execution.yaml>
+kubectl create configmap benchmark-configmap --from-file=<benchmark.yaml>
+```
+
+This will create three ConfigMaps. You can verify this via `kubectl get configmaps`.
+
+Start the Theodolite job (with `<your-theodolite-yaml>` being your job definition):
 
 ```sh
 kubectl create -f <your-theodolite-yaml>
@@ -241,24 +251,7 @@ Kubernetes volume.
 
 ### Configuration
 
-| Command line         | Kubernetes          | Description                                                  |
-| -------------------- | ------------------- | ------------------------------------------------------------ |
-| --uc                 | UC                  | **[Mandatory]** Stream processing use case to be benchmarked. Has to be one of `1`, `2`, `3` or `4`. |
-| --loads              | LOADS               | **[Mandatory]** Values for the workload generator to be tested, should be sorted in ascending order. |
-| --instances          | INSTANCES           | **[Mandatory]** Numbers of instances to be benchmarked, should be sorted in ascending order. |
-| --duration           | DURATION            | Duration in minutes subexperiments should be executed for. *Default:* `5`. |
-| --partitions         | PARTITIONS          | Number of partitions for Kafka topics. *Default:* `40`.      |
-| --cpu-limit          | CPU_LIMIT           | Kubernetes CPU limit for a single Pod.  *Default:* `1000m`.  |
-| --memory-limit       | MEMORY_LIMIT        | Kubernetes memory limit for a single Pod. *Default:* `4Gi`.  |
-| --domain-restriction | DOMAIN_RESTRICTION  | A flag that indiciates domain restriction should be used. *Default:* not set. For more details see Section [Domain Restriction](#domain-restriction). |
-| --search-strategy    | SEARCH_STRATEGY     | The benchmarking search strategy. Can be set to `check-all`, `linear-search` or `binary-search`. *Default:* `check-all`. For more details see Section [Benchmarking Search Strategies](#benchmarking-search-strategies). |
-| --reset              | RESET               | Resets the environment before each subexperiment. Useful if execution was aborted and just one experiment should be executed. |
-| --reset-only         | RESET_ONLY          | Only resets the environment. Ignores all other parameters. Useful if execution was aborted and one want a clean state for new executions. |
-| --namespace          | NAMESPACE        | Kubernetes namespace. *Default:* `default`.  |
-| --prometheus         | PROMETHEUS_BASE_URL | Defines where to find the prometheus instance. *Default:* `http://localhost:9090` |
-| --path               | RESULT_PATH         | A directory path for the results. Relative to the Execution folder. *Default:* `results` |
-| --configurations     | CONFIGURATIONS      | Defines environment variables for the use cases and, thus, enables further configuration options. |
-| --threshold          | THRESHOLD           | The threshold for the trend slop that the search strategies use to determine that a load could be handled. *Default:* `2000` |
+Be sure, that the names of the configmap corresponds correctly to the specifications of the mounted `configmaps`, `volumes`, `mountPath`. In particular: The name of the execution file and the benchmark file must match the value of the corresponding environment variable.
 
 ### Domain Restriction
 

execution/theodolite.yaml

@@ -5,47 +5,60 @@ metadata:
 spec:
   template:
     spec:
-      volumes:
-      - name: theodolite-pv-storage
-        persistentVolumeClaim:
-          claimName: theodolite-pv-claim
+      securityContext:
+        runAsUser: 0 # Set the permissions for write access to the volumes.
       containers:
+        - name: lag-analysis
+          image: ghcr.io/cau-se/theodolite-slo-checker-lag-trend:theodolite-kotlin-latest
+          ports:
+          - containerPort: 80
+            name: analysis
         - name: theodolite
-          image: ghcr.io/cau-se/theodolite:latest
-          # imagePullPolicy: Never # Used to pull "own" local image
+          image: ghcr.io/cau-se/theodolite:theodolite-kotlin-latest
+          imagePullPolicy: Always
           env:
-            - name: UC # mandatory
-              value: "1"
-            - name: LOADS # mandatory
-              value: "100000, 200000"
-            - name: INSTANCES # mandatory
-              value: "1, 2, 3"
-            # - name: DURATION
-            #   value: "5"
-            # - name: PARTITIONS
-            #   value: "40"
-            # - name: DOMAIN_RESTRICTION
-            #   value: "True"
-            # - name: SEARCH_STRATEGY
-            #   value: "linear-search"
-            # - name: CPU_LIMIT
-            #   value: "1000m"
-            # - name: MEMORY_LIMIT
-            #   value: "4Gi"
-            - name: PROMETHEUS_BASE_URL
-              value: "http://prometheus-operated:9090"
-            # - name: NAMESPACE
-            #   value: "default"
-            # - name: CONFIGURATIONS
-            #   value: "COMMIT_INTERVAL_MS=100, NUM_STREAM_THREADS=1"
-            - name: RESULT_PATH
-              value: "results"
-            - name: PYTHONUNBUFFERED # Enable logs in Kubernetes
-              value: "1"
+            - name: NAMESPACE
+              valueFrom:
+                fieldRef:
+                  fieldPath: metadata.namespace
+
+            # - name: MODE
+            #   value: yaml-executor # Default is `yaml-executor`
+            - name: THEODOLITE_EXECUTION
+              value: /etc/execution/example-execution-yaml-resource.yaml # The name of this file must correspond to the filename of the execution, from which the config map is created.
+            - name: THEODOLITE_BENCHMARK
+              value: /etc/benchmark/example-benchmark-yaml-resource.yaml # The name of this file must correspond to the filename of the benchmark, from which the config map is created.
+            - name: THEODOLITE_APP_RESOURCES
+              value: /etc/app-resources
+            - name: RESULTS_FOLDER # Folder for saving results
+              value: results # Default is the pwd (/deployments)
+            # - name: CREATE_RESULTS_FOLDER # Specify whether the specified result folder should be created if it does not exist.
+            #   value: "false" # Default is false.
           volumeMounts:
-            - mountPath: "/app/results"
+            - mountPath: "/deployments/results" # the mounted path must corresponds to the value of `RESULT_FOLDER`.
               name: theodolite-pv-storage
+            - mountPath: "/etc/app-resources" # must be corresponds to the value of `THEODOLITE_APP_RESOURCES`.
+              name: app-resources
+            - mountPath: "/etc/benchmark"  # must be corresponds to the value of `THEODOLITE_BENCHMARK`.
+              name: benchmark
+            - mountPath: "/etc/execution" # must be corresponds to the value of `THEODOLITE_EXECUTION`.
+              name: execution
       restartPolicy: Never
       # Uncomment if RBAC is enabled and configured
-      # serviceAccountName: theodolite
-  backoffLimit: 4
+      serviceAccountName: theodolite
+      # Multiple volumes are needed to provide the corresponding files.
+      # The names must correspond to the created configmaps and the volumeMounts.
+      volumes:
+        - name: theodolite-pv-storage
+          persistentVolumeClaim:
+            claimName: theodolite-pv-claim
+        - name: app-resources
+          configMap:
+            name: app-resources-configmap
+        - name: benchmark
+          configMap:
+            name: benchmark-configmap
+        - name: execution
+          configMap:
+            name: execution-configmap
+  backoffLimit: 4
\ No newline at end of file

slope-evaluator/README.md

@@ -17,10 +17,43 @@ docker build . -t theodolite-evaluator
 Run the Docker image:
 
 ```sh
- docker run -p 80:80 theodolite-evaluator
+docker run -p 80:80 theodolite-evaluator
 ```
 
 ## Configuration
 
 You can set the `HOST` and the `PORT` (and a lot of more parameters) via environment variables. Default is `0.0.0.0:80`.
-For more information see [here](https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker#advanced-usage).
+For more information see the [Gunicorn/FastAPI Docker docs](https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker#advanced-usage).
+
+## API Documentation
+
+The running webserver provides a REST API with the following route:
+
+* /evaluate-slope
+    * Method: POST
+    * Body:
+        * total_lag
+        * threshold
+        * warmup
+
+The body of the request must be a JSON string that satisfies the following conditions:
+
+* **total_lag**: This property is based on the [Range Vector type](https://www.prometheus.io/docs/prometheus/latest/querying/api/#range-vectors) from Prometheus and must have the following JSON structure:
+    ```
+        {
+            "metric": {
+                "group": "<label_value>"
+            },
+            "values": [
+                [
+                    <unix_timestamp>,
+                    "<sample_value>"
+                ]
+            ]
+        }
+    ```
+    * The `<label_value>` provided in "metric.group" must be equal to the id of the Kafka consumer group.
+    * The `<unix_timestamp>` provided as the first element of each element in the "values" array must be the timestamp of the measurement value in seconds (with optional decimal precision)
+    * The `<sample_value>` must be the measurement value as string.
+* **threshold**: Must be an unsigned integer that specifies the threshold for the SLO evaluation. The SLO is considered fulfilled, if the result value is below the threshold. If the result value is equal or above the threshold, the SLO is considered not fulfilled.
+* **warmup**: Specifieds the warmup time in seconds that are ignored for evaluating the SLO.
\ No newline at end of file

slope-evaluator/app/main.py

@@ -18,7 +18,7 @@ if os.getenv('LOG_LEVEL') == 'INFO':
 elif os.getenv('LOG_LEVEL') == 'WARNING':
     logger.setLevel(logging.WARNING)
 elif os.getenv('LOG_LEVEL') == 'DEBUG':
-    logger.setLevel((logging.DEBUG))
+    logger.setLevel(logging.DEBUG)
 
 def execute(results, threshold, warmup):
     d = []
@@ -30,18 +30,18 @@ def execute(results, threshold, warmup):
 
     df = pd.DataFrame(d)
 
-    logger.info(df)
+    logger.info("Calculating trend slope with warmup of %s seconds for data frame:\n %s", warmup, df)
     try:
         trend_slope = trend_slope_computer.compute(df, warmup)
     except Exception as e:
-        err_msg = 'Computing trend slope failed'
+        err_msg = 'Computing trend slope failed.'
         logger.exception(err_msg)
-        logger.error('Mark this subexperiment as not successful and continue benchmark')
+        logger.error('Mark this subexperiment as not successful and continue benchmark.')
         return False
 
-    logger.info("Trend Slope: %s", trend_slope)
-
-    return trend_slope < threshold
+    result = trend_slope < threshold
+    logger.info("Computed lag trend slope is '%s'. Result is: %s", trend_slope, result)
+    return result
 
 @app.post("/evaluate-slope",response_model=bool)
 async def evaluate_slope(request: Request):

slope-evaluator/app/trend_slope_computer.py

@@ -2,13 +2,12 @@ from sklearn.linear_model import LinearRegression
 import pandas as pd
 import os
 
-def compute(x, warmup_sec):
-    input = x
-    input['sec_start'] = input.loc[0:, 'timestamp'] - input.iloc[0]['timestamp']
-    regress = input.loc[input['sec_start'] >= warmup_sec] # Warm-Up
+def compute(data, warmup_sec):
+    data['sec_start'] = data.loc[0:, 'timestamp'] - data.iloc[0]['timestamp']
+    regress = data.loc[data['sec_start'] >= warmup_sec] # Warm-Up
 
-    X = regress.iloc[:, 2].values.reshape(-1, 1)  # values converts it into a numpy array
-    Y = regress.iloc[:, 3].values.reshape(-1, 1)  # -1 means that calculate the dimension of rows, but have 1 column
+    X = regress.iloc[:, 1].values.reshape(-1, 1)  # values converts it into a numpy array
+    Y = regress.iloc[:, 2].values.reshape(-1, 1)  # -1 means that calculate the dimension of rows, but have 1 column
     linear_regressor = LinearRegression()  # create object for the class
     linear_regressor.fit(X, Y)  # perform linear regression
     Y_pred = linear_regressor.predict(X)  # make predictions

theodolite-quarkus/build.gradle

@@ -18,20 +18,20 @@ dependencies {
     implementation 'org.jetbrains.kotlin:kotlin-stdlib-jdk8'
     implementation 'io.quarkus:quarkus-arc'
     implementation 'io.quarkus:quarkus-resteasy'
-    testImplementation 'io.quarkus:quarkus-junit5'
-    testImplementation 'io.rest-assured:rest-assured'
     implementation 'com.google.code.gson:gson:2.8.5'
-
     implementation 'org.slf4j:slf4j-simple:1.7.29'
     implementation 'io.github.microutils:kotlin-logging:1.12.0'
     implementation 'io.fabric8:kubernetes-client:5.0.0-alpha-2'
     implementation 'io.quarkus:quarkus-kubernetes-client'
     implementation 'org.apache.kafka:kafka-clients:2.7.0'
     implementation 'khttp:khttp:1.0.0'
+
+    testImplementation 'io.quarkus:quarkus-junit5'
+    testImplementation 'io.rest-assured:rest-assured'
 }
 
 group 'theodolite'
-version '1.0.0-SNAPSHOT'
+version '0.5.0-SNAPSHOT'
 
 java {
     sourceCompatibility = JavaVersion.VERSION_11

theodolite-quarkus/config/example-benchmark-yaml-resource.yaml

@@ -19,9 +19,13 @@ loadTypes:
         resource: "uc1-load-generator-deployment.yaml"
         container: "workload-generator"
         variableName: "NUM_SENSORS"
+      - type: "NumSensorsLoadGeneratorReplicaPatcher"
+        resource: "uc1-load-generator-deployment.yaml"
 kafkaConfig:
   bootstrapServer: "theodolite-cp-kafka:9092"
   topics:
     - name: "input"
       numPartitions: 40
-      replicationFactor: 1
\ No newline at end of file
+      replicationFactor: 1
+    - name: "theodolite-.*"
+      removeOnly: True
\ No newline at end of file

theodolite-quarkus/config/example-operator-benchmark.yaml

@@ -23,9 +23,13 @@ loadTypes:
         resource: "uc1-load-generator-deployment.yaml"
         container: "workload-generator"
         variableName: "NUM_SENSORS"
+      - type: "NumSensorsLoadGeneratorReplicaPatcher"
+        resource: "uc1-load-generator-deployment.yaml"
 kafkaConfig:
   bootstrapServer: "theodolite-cp-kafka:9092"
   topics:
     - name: "input"
       numPartitions: 40
-      replicationFactor: 1
\ No newline at end of file
+      replicationFactor: 1
+    - name: "theodolite-.*"
+      removeOnly: True
\ No newline at end of file

theodolite-quarkus/src/main/docker/Dockerfile.native

@@ -15,12 +15,12 @@
 #
 ###
 FROM registry.access.redhat.com/ubi8/ubi-minimal:8.3
-WORKDIR /work/
-RUN chown 1001 /work \
-    && chmod "g+rwX" /work \
-    && chown 1001:root /work
-COPY --chown=1001:root build/*-runner /work/application
-COPY config/ /work/config/
+WORKDIR /deployments
+RUN chown 1001 /deployments \
+    && chmod "g+rwX" /deployments \
+    && chown 1001:root /deployments
+COPY --chown=1001:root build/*-runner /deployments/application
+COPY config/ /deployments/config/
 
 EXPOSE 8080
 USER 1001

theodolite-quarkus/src/main/kotlin/theodolite/benchmark/KubernetesBenchmark.kt

@@ -96,7 +96,7 @@ class KubernetesBenchmark : Benchmark, CustomResource(), Namespaced {
             namespace = namespace,
             resources = resources.map { r -> r.second },
             kafkaConfig = hashMapOf("bootstrap.servers" to kafkaConfig.bootstrapServer),
-            topics = kafkaConfig.getKafkaTopics(),
+            topics = kafkaConfig.topics,
             client = DefaultKubernetesClient().inNamespace(namespace)
         )
     }

theodolite-quarkus/src/main/kotlin/theodolite/benchmark/KubernetesBenchmarkDeployment.kt

@@ -3,9 +3,13 @@ package theodolite.benchmark
 import io.fabric8.kubernetes.api.model.KubernetesResource
 import io.fabric8.kubernetes.client.NamespacedKubernetesClient
 import io.quarkus.runtime.annotations.RegisterForReflection
+import mu.KotlinLogging
 import org.apache.kafka.clients.admin.NewTopic
 import theodolite.k8s.K8sManager
 import theodolite.k8s.TopicManager
+import theodolite.util.KafkaConfig
+
+private val logger = KotlinLogging.logger {}
 
 /**
  * Organizes the deployment of benchmarks in Kubernetes.
@@ -20,12 +24,13 @@ class KubernetesBenchmarkDeployment(
     val namespace: String,
     val resources: List<KubernetesResource>,
     private val kafkaConfig: HashMap<String, Any>,
-    private val topics: Collection<NewTopic>,
+    private val topics: List<KafkaConfig.TopicWrapper>,
     private val client: NamespacedKubernetesClient
 ) : BenchmarkDeployment {
     private val kafkaController = TopicManager(this.kafkaConfig)
     private val kubernetesManager = K8sManager(client)
-    private val LABEL = "app.kubernetes.io/name=kafka-lag-exporter"
+    private val LAG_EXPORTER_POD_LABEL = "app.kubernetes.io/name=kafka-lag-exporter"
+    private val SLEEP_AFTER_TEARDOWN = 5000L
 
     /**
      * Setup a [KubernetesBenchmark] using the [TopicManager] and the [K8sManager]:
@@ -33,10 +38,10 @@ class KubernetesBenchmarkDeployment(
      *  - Deploy the needed resources.
      */
     override fun setup() {
-        kafkaController.createTopics(this.topics)
-        resources.forEach {
-            kubernetesManager.deploy(it)
-        }
+        val kafkaTopics = this.topics.filter { !it.removeOnly }
+            .map{ NewTopic(it.name, it.numPartitions, it.replicationFactor) }
+        kafkaController.createTopics(kafkaTopics)
+        resources.forEach { kubernetesManager.deploy(it) }
     }
 
     /**
@@ -46,10 +51,12 @@ class KubernetesBenchmarkDeployment(
      *  - Remove the [KubernetesResource]s.
      */
     override fun teardown() {
-        KafkaLagExporterRemover(client).remove(LABEL)
-        kafkaController.removeTopics(this.topics.map { topic -> topic.name() })
         resources.forEach {
             kubernetesManager.remove(it)
         }
+        kafkaController.removeTopics(this.topics.map { topic -> topic.name })
+        KafkaLagExporterRemover(client).remove(LAG_EXPORTER_POD_LABEL)
+        logger.info { "Teardown complete. Wait $SLEEP_AFTER_TEARDOWN ms to let everything come down." }
+        Thread.sleep(SLEEP_AFTER_TEARDOWN)
     }
 }

theodolite-quarkus/src/main/kotlin/theodolite/evaluation/AnalysisExecutor.kt

@@ -4,8 +4,11 @@ import mu.KotlinLogging
 import theodolite.benchmark.BenchmarkExecution
 import theodolite.util.LoadDimension
 import theodolite.util.Resource
+import java.text.Normalizer
 import java.time.Duration
 import java.time.Instant
+import java.util.*
+import java.util.regex.Pattern
 
 private val logger = KotlinLogging.logger {}
 
@@ -41,7 +44,15 @@ class AnalysisExecutor(
                 query = "sum by(group)(kafka_consumergroup_group_lag >= 0)"
             )
 
-            CsvExporter().toCsv(name = "$executionId-${load.get()}-${res.get()}-${slo.sloType}", prom = prometheusData)
+            var resultsFolder: String = System.getenv("RESULTS_FOLDER")
+            if (resultsFolder.isNotEmpty()){
+                resultsFolder += "/"
+            }
+
+            CsvExporter().toCsv(
+                name = "${resultsFolder}exp${executionId}_${load.get()}_${res.get()}_${slo.sloType.toSlug()}",
+                prom = prometheusData
+            )
             val sloChecker = SloCheckerFactory().create(
                 sloType = slo.sloType,
                 externalSlopeURL = slo.externalSloUrl,
@@ -55,8 +66,18 @@ class AnalysisExecutor(
             )
 
         } catch (e: Exception) {
-            logger.error { "Evaluation failed for resource: ${res.get()} and load: ${load.get()} error: $e" }
+            logger.error { "Evaluation failed for resource '${res.get()}' and load '${load.get()}'. Error: $e" }
         }
         return result
     }
+
+    private val NONLATIN: Pattern = Pattern.compile("[^\\w-]")
+    private val WHITESPACE: Pattern = Pattern.compile("[\\s]")
+
+    fun String.toSlug(): String {
+        val noWhitespace: String = WHITESPACE.matcher(this).replaceAll("-")
+        val normalized: String = Normalizer.normalize(noWhitespace, Normalizer.Form.NFD)
+        val slug: String = NONLATIN.matcher(normalized).replaceAll("")
+        return slug.toLowerCase(Locale.ENGLISH)
+    }
 }

theodolite-quarkus/src/main/kotlin/theodolite/evaluation/CsvExporter.kt

@@ -24,12 +24,12 @@ class CsvExporter {
         val csvOutputFile = File("$name.csv")
 
         PrintWriter(csvOutputFile).use { pw ->
-            pw.println(listOf("name", "time", "value").joinToString())
+            pw.println(listOf("group", "timestamp", "value").joinToString(separator=","))
             responseArray.forEach {
-                pw.println(it.joinToString())
+                pw.println(it.joinToString(separator=","))
             }
         }
-        logger.info { "Wrote csv file: $name to ${csvOutputFile.absolutePath}" }
+        logger.info { "Wrote CSV file: $name to ${csvOutputFile.absolutePath}." }
     }
 
     /**
@@ -41,9 +41,11 @@ class CsvExporter {
         val dataList = mutableListOf<List<String>>()
 
         if (values != null) {
-            for (x in values) {
-                val y = x as List<*>
-                dataList.add(listOf(name, "${y[0]}", "${y[1]}"))
+            for (maybeValuePair in values) {
+                val valuePair = maybeValuePair as List<*>
+                val timestamp = (valuePair[0] as Double).toLong().toString()
+                val value = valuePair[1].toString()
+                dataList.add(listOf(name, timestamp, value))
             }
         }
         return Collections.unmodifiableList(dataList)

theodolite-quarkus/src/main/kotlin/theodolite/evaluation/ExternalSloChecker.kt

@@ -17,8 +17,7 @@ class ExternalSloChecker(
     private val externalSlopeURL: String,
     private val threshold: Int,
     private val warmup: Int
-) :
-    SloChecker {
+) : SloChecker {
 
     private val RETRIES = 2
     private val TIMEOUT = 60.0
@@ -38,19 +37,23 @@ class ExternalSloChecker(
      */
     override fun evaluate(start: Instant, end: Instant, fetchedData: PrometheusResponse): Boolean {
         var counter = 0
-        val data =
-            Gson().toJson(mapOf("total_lag" to fetchedData.data?.result, "threshold" to threshold, "warmup" to warmup))
+        val data = Gson().toJson(mapOf(
+            "total_lag" to fetchedData.data?.result,
+            "threshold" to threshold,
+            "warmup" to warmup))
 
         while (counter < RETRIES) {
             val result = post(externalSlopeURL, data = data, timeout = TIMEOUT)
             if (result.statusCode != 200) {
                 counter++
-                logger.error { "Could not reach external slope analysis" }
+                logger.error { "Could not reach external SLO checker" }
             } else {
-                return result.text.toBoolean()
+                val booleanResult = result.text.toBoolean()
+                logger.info { "SLO checker result is: $booleanResult" }
+                return booleanResult
             }
         }
 
-        throw ConnectException("Could not reach slope evaluation")
+        throw ConnectException("Could not reach external SLO checker")
     }
 }

theodolite-quarkus/src/main/kotlin/theodolite/evaluation/MetricFetcher.kt

@@ -48,18 +48,18 @@ class MetricFetcher(private val prometheusURL: String, private val offset: Durat
             val response = get("$prometheusURL/api/v1/query_range", params = parameter, timeout = TIMEOUT)
             if (response.statusCode != 200) {
                 val message = response.jsonObject.toString()
-                logger.warn { "Could not connect to Prometheus: $message, retrying now" }
+                logger.warn { "Could not connect to Prometheus: $message. Retrying now." }
                 counter++
             } else {
                 val values = parseValues(response)
                 if (values.data?.result.isNullOrEmpty()) {
-                    logger.error { "Empty query result: $values between $start and $end for querry $query" }
+                    logger.error { "Empty query result: $values between $start and $end for query $query." }
                     throw NoSuchFieldException()
                 }
                 return parseValues(response)
             }
         }
-        throw ConnectException("No answer from Prometheus received")
+        throw ConnectException("No answer from Prometheus received.")
     }
 
     /**

theodolite-quarkus/src/main/kotlin/theodolite/execution/BenchmarkExecutor.kt

@@ -47,7 +47,7 @@ abstract class BenchmarkExecutor(
      *
      */
     fun waitAndLog() {
-        logger.info { "Execution of a new benchmark started." }
+        logger.info { "Execution of a new experiment started." }
 
         var secondsRunning = 0L
 

theodolite-quarkus/src/main/kotlin/theodolite/execution/BenchmarkExecutorImpl.kt

@@ -29,8 +29,8 @@ class BenchmarkExecutorImpl(
         try {
             benchmarkDeployment.setup()
             this.waitAndLog()
-        } catch(e: Exception) {
-            logger.error { "Error while setup experiment." }
+        } catch (e: Exception) {
+            logger.error { "Error while setting up experiment with id ${this.executionId}." }
             logger.error { "Error is: $e" }
             this.run.set(false)
         }
@@ -39,11 +39,20 @@ class BenchmarkExecutorImpl(
          * Analyse the experiment, if [run] is true, otherwise the experiment was canceled by the user.
          */
         if (this.run.get()) {
-            result =
-                AnalysisExecutor(slo = slo, executionId = executionId).analyze(load = load, res = res, executionDuration = executionDuration)
+            result = AnalysisExecutor(slo = slo, executionId = executionId).analyze(
+                load = load,
+                res = res,
+                executionDuration = executionDuration
+            )
             this.results.setResult(Pair(load, res), result)
         }
-        benchmarkDeployment.teardown()
+
+        try {
+            benchmarkDeployment.teardown()
+        } catch (e: Exception) {
+            logger.warn { "Error while tearing down the benchmark deployment." }
+            logger.debug { "Teardown failed, caused by: $e" }
+        }
 
         return result
     }

theodolite-quarkus/src/main/kotlin/theodolite/execution/Main.kt

@@ -13,13 +13,17 @@ object Main {
     @JvmStatic
     fun main(args: Array<String>) {
 
-        val mode = System.getenv("MODE") ?: "yaml-executor"
+        val mode = System.getenv("MODE") ?: "standalone"
         logger.info { "Start Theodolite with mode $mode" }
 
         when(mode) {
-           "yaml-executor" -> TheodoliteYamlExecutor().start()
+            "standalone" -> TheodoliteYamlExecutor().start()
+            "yaml-executor" -> TheodoliteYamlExecutor().start() // TODO remove (#209)
             "operator" -> TheodoliteOperator().start()
-            else ->  {logger.error { "MODE $mode not found" }; exitProcess(1)}
+            else ->  {
+                logger.error { "MODE $mode not found" }
+                exitProcess(1)
+            }
         }
     }
 }
\ No newline at end of file

theodolite-quarkus/src/main/kotlin/theodolite/execution/Shutdown.kt

@@ -5,6 +5,7 @@ import theodolite.benchmark.BenchmarkExecution
 import theodolite.benchmark.KubernetesBenchmark
 import theodolite.util.LoadDimension
 import theodolite.util.Resource
+import java.lang.Exception
 
 private val logger = KotlinLogging.logger {}
 
@@ -23,6 +24,7 @@ class Shutdown(private val benchmarkExecution: BenchmarkExecution, private val b
      */
     override fun run() {
         // Build Configuration to teardown
+        try {
         logger.info { "Received shutdown signal -> Shutting down" }
         val deployment =
             benchmark.buildDeployment(
@@ -30,8 +32,13 @@ class Shutdown(private val benchmarkExecution: BenchmarkExecution, private val b
                 res = Resource(0, emptyList()),
                 configurationOverrides = benchmarkExecution.configOverrides
             )
+            deployment.teardown()
+        } catch (e: Exception) {
+            logger.warn { "Could not delete all specified resources from Kubernetes. " +
+                    "This could be the case, if not all resources are deployed and running." }
+
+        }
         logger.info { "Teardown everything deployed" }
-        deployment.teardown()
         logger.info { "Teardown completed" }
     }
 }