Move to ClusterModel

6 files changed, 131 insertions, 140 deletions

diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/Autoscaler.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/Autoscaler.java
index 9834f898113..9791aabf7b4 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/Autoscaler.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/Autoscaler.java
@@ -59,9 +59,9 @@ public class Autoscaler {
     }
 
     private Advice autoscale(Application application, Cluster cluster, NodeList clusterNodes, Limits limits) {
-        ClusterModel clusterModel = new ClusterModel(application, cluster, clusterNodes, metricsDb, nodeRepository);
+        ClusterModel clusterModel = new ClusterModel(application, cluster, clusterNodes, metricsDb, nodeRepository.clock());
 
-        if ( ! clusterModel.isStable())
+        if ( ! clusterIsStable(clusterNodes, nodeRepository))
             return Advice.none("Cluster change in progress");
 
         if (scaledIn(clusterModel.scalingDuration(), cluster))
@@ -77,12 +77,7 @@ public class Autoscaler {
                                " nodes, but require from " + clusterNodes.size());
 
         var currentAllocation = new AllocatableClusterResources(clusterNodes.asList(), nodeRepository, cluster.exclusive());
-        var target = ResourceTarget.idealLoad(clusterModel.scalingDuration(),
-                                              clusterModel.clusterTimeseries(),
-                                              clusterModel.nodeTimeseries(),
-                                              currentAllocation,
-                                              application,
-                                              nodeRepository.clock());
+        var target = ResourceTarget.idealLoad(clusterModel, currentAllocation);
 
         Optional<AllocatableClusterResources> bestAllocation =
                 allocationOptimizer.findBestAllocation(target, currentAllocation, limits);
@@ -99,6 +94,20 @@ public class Autoscaler {
         return Advice.scaleTo(bestAllocation.get().advertisedResources());
     }
 
+    public static boolean clusterIsStable(NodeList clusterNodes, NodeRepository nodeRepository) {
+        // The cluster is processing recent changes
+        if (clusterNodes.stream().anyMatch(node -> node.status().wantToRetire() ||
+                                                   node.allocation().get().membership().retired() ||
+                                                   node.allocation().get().isRemovable()))
+            return false;
+
+        // A deployment is ongoing
+        if (nodeRepository.nodes().list(Node.State.reserved).owner(clusterNodes.first().get().allocation().get().owner()).size() > 0)
+            return false;
+
+        return true;
+    }
+
     /** Returns true if both total real resources and total cost are similar */
     public static boolean similar(ClusterResources a, ClusterResources b) {
         return similar(a.cost(), b.cost(), costDifferenceWorthReallocation) &&
diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
index 32ddd52ca40..98955848d2d 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java
@@ -1,14 +1,14 @@
 // Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 package com.yahoo.vespa.hosted.provision.autoscale;
 
-import com.yahoo.vespa.hosted.provision.Node;
 import com.yahoo.vespa.hosted.provision.NodeList;
-import com.yahoo.vespa.hosted.provision.NodeRepository;
 import com.yahoo.vespa.hosted.provision.applications.Application;
 import com.yahoo.vespa.hosted.provision.applications.Cluster;
 import com.yahoo.vespa.hosted.provision.applications.ScalingEvent;
 
+import java.time.Clock;
 import java.time.Duration;
+import java.util.OptionalDouble;
 
 /**
  * A cluster with its associated metrics which allows prediction about its future behavior.
@@ -22,7 +22,8 @@ public class ClusterModel {
     private final Cluster cluster;
     private final NodeList nodes;
     private final MetricsDb metricsDb;
-    private final NodeRepository nodeRepository;
+    private final Clock clock;
+    private final Duration scalingDuration;
 
     // Lazily initialized members
     private ClusterNodesTimeseries nodeTimeseries = null;
@@ -32,14 +33,34 @@ public class ClusterModel {
                         Cluster cluster,
                         NodeList clusterNodes,
                         MetricsDb metricsDb,
-                        NodeRepository nodeRepository) {
+                        Clock clock) {
         this.application = application;
         this.cluster = cluster;
         this.nodes = clusterNodes;
         this.metricsDb = metricsDb;
-        this.nodeRepository = nodeRepository;
+        this.clock = clock;
+        this.scalingDuration = computeScalingDuration(cluster, clusterNodes);
     }
 
+    /** For testing */
+    ClusterModel(Application application,
+                 Cluster cluster,
+                 Clock clock,
+                 Duration scalingDuration,
+                 ClusterTimeseries clusterTimeseries) {
+        this.application = application;
+        this.cluster = cluster;
+        this.nodes = null;
+        this.metricsDb = null;
+        this.clock = clock;
+
+        this.scalingDuration = scalingDuration;
+        this.clusterTimeseries = clusterTimeseries;
+    }
+
+    /** Returns the predicted duration of a rescaling of this cluster */
+    public Duration scalingDuration() { return scalingDuration; }
+
     public ClusterNodesTimeseries nodeTimeseries() {
         if (nodeTimeseries != null) return nodeTimeseries;
         return nodeTimeseries = new ClusterNodesTimeseries(scalingDuration(), cluster, nodes, metricsDb);
@@ -50,26 +71,63 @@ public class ClusterModel {
         return clusterTimeseries = metricsDb.getClusterTimeseries(application.id(), cluster.id());
     }
 
-    public boolean isStable() {
-        return isStable(nodes, nodeRepository);
+    public double averageLoad(Resource resource) { return nodeTimeseries().averageLoad(resource); }
+
+    public double idealLoad(Resource resource) {
+        switch (resource) {
+            case cpu : return idealCpuLoad();
+            default : return resource.idealAverageLoad(); // TODO: Move here
+        }
     }
 
-    public static boolean isStable(NodeList clusterNodes, NodeRepository nodeRepository) {
-        // The cluster is processing recent changes
-        if (clusterNodes.stream().anyMatch(node -> node.status().wantToRetire() ||
-                                            node.allocation().get().membership().retired() ||
-                                            node.allocation().get().isRemovable()))
-            return false;
+    /** Ideal cpu load must take the application traffic fraction into account */
+    private double idealCpuLoad() {
+        double queryCpuFraction = queryCpuFraction();
+
+        // What's needed to have headroom for growth during scale-up as a fraction of current resources?
+        double maxGrowthRate = clusterTimeseries().maxQueryGrowthRate(scalingDuration(), clock); // in fraction per minute of the current traffic
+        double growthRateHeadroom = 1 + maxGrowthRate * scalingDuration().toMinutes();
+        // Cap headroom at 10% above the historical observed peak
+        double fractionOfMax = clusterTimeseries().queryFractionOfMax(scalingDuration(), clock);
+        if (fractionOfMax != 0)
+            growthRateHeadroom = Math.min(growthRateHeadroom, 1 / fractionOfMax + 0.1);
+
+        // How much headroom is needed to handle sudden arrival of additional traffic due to another zone going down?
+        double maxTrafficShiftHeadroom = 10.0; // Cap to avoid extreme sizes from a current very small share
+        double trafficShiftHeadroom;
+        if (application.status().maxReadShare() == 0) // No traffic fraction data
+            trafficShiftHeadroom = 2.0; // assume we currently get half of the global share of traffic
+        else if (application.status().currentReadShare() == 0)
+            trafficShiftHeadroom = maxTrafficShiftHeadroom;
+        else
+            trafficShiftHeadroom = application.status().maxReadShare() / application.status().currentReadShare();
+        trafficShiftHeadroom = Math.min(trafficShiftHeadroom, maxTrafficShiftHeadroom);
+
+        // Assumptions: 1) Write load is not organic so we should not grow to handle more.
+        //                 (TODO: But allow applications to set their target write rate and size for that)
+        //              2) Write load does not change in BCP scenarios.
+        return queryCpuFraction * 1 / growthRateHeadroom * 1 / trafficShiftHeadroom * idealQueryCpuLoad() +
+               (1 - queryCpuFraction) * idealWriteCpuLoad();
+    }
 
-        // A deployment is ongoing
-        if (nodeRepository.nodes().list(Node.State.reserved).owner(clusterNodes.first().get().allocation().get().owner()).size() > 0)
-            return false;
+    private double queryCpuFraction() {
+        OptionalDouble queryRate = clusterTimeseries().queryRate(scalingDuration(), clock);
+        OptionalDouble writeRate = clusterTimeseries().writeRate(scalingDuration(), clock);
+        if (queryRate.orElse(0) == 0 && writeRate.orElse(0) == 0) return queryCpuFraction(0.5);
+        return queryCpuFraction(queryRate.orElse(0) / (queryRate.orElse(0) + writeRate.orElse(0)));
+    }
 
-        return true;
+    private double queryCpuFraction(double queryFraction) {
+        double relativeQueryCost = 9; // How much more expensive are queries than writes? TODO: Measure
+        double writeFraction = 1 - queryFraction;
+        return queryFraction * relativeQueryCost / (queryFraction * relativeQueryCost + writeFraction);
     }
 
-    /** The predicted duration of a rescaling of this cluster */
-    public Duration scalingDuration() {
+    public static double idealQueryCpuLoad() { return Resource.cpu.idealAverageLoad(); }
+
+    public static double idealWriteCpuLoad() { return 0.95; }
+
+    private static Duration computeScalingDuration(Cluster cluster, NodeList nodes) {
         int completedEventCount = 0;
         Duration totalDuration = Duration.ZERO;
         for (ScalingEvent event : cluster.scalingEvents()) {
diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/MetricsResponse.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/MetricsResponse.java
index b6208cedc5e..b3cf6c1e962 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/MetricsResponse.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/MetricsResponse.java
@@ -103,7 +103,7 @@ public class MetricsResponse {
 
     private boolean clusterIsStable(Node node, NodeList applicationNodes, NodeRepository nodeRepository) {
         ClusterSpec cluster = node.allocation().get().membership().cluster();
-        return ClusterModel.isStable(applicationNodes.cluster(cluster.id()), nodeRepository);
+        return Autoscaler.clusterIsStable(applicationNodes.cluster(cluster.id()), nodeRepository);
     }
 
     public static MetricsResponse empty() { return new MetricsResponse(List.of()); }
diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTarget.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTarget.java
index 9f6a4fc77cd..b1a1e86b08d 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTarget.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTarget.java
@@ -51,18 +51,14 @@ public class ResourceTarget {
     }
 
     /** Create a target of achieving ideal load given a current load */
-    public static ResourceTarget idealLoad(Duration scalingDuration,
-                                           ClusterTimeseries clusterTimeseries,
-                                           ClusterNodesTimeseries clusterNodesTimeseries,
-                                           AllocatableClusterResources current,
-                                           Application application,
-                                           Clock clock) {
-        return new ResourceTarget(nodeUsage(Resource.cpu, clusterNodesTimeseries.averageLoad(Resource.cpu), current)
-                                  / idealCpuLoad(scalingDuration, clusterTimeseries, application, clock),
-                                  nodeUsage(Resource.memory, clusterNodesTimeseries.averageLoad(Resource.memory), current)
-                                  / Resource.memory.idealAverageLoad(),
-                                  nodeUsage(Resource.disk, clusterNodesTimeseries.averageLoad(Resource.disk), current)
-                                  / Resource.disk.idealAverageLoad(),
+    public static ResourceTarget idealLoad(ClusterModel clusterModel,
+                                           AllocatableClusterResources current) {
+        return new ResourceTarget(nodeUsage(Resource.cpu, clusterModel.averageLoad(Resource.cpu), current)
+                                  / clusterModel.idealLoad(Resource.cpu),
+                                  nodeUsage(Resource.memory, clusterModel.averageLoad(Resource.memory), current)
+                                  / clusterModel.idealLoad(Resource.memory),
+                                  nodeUsage(Resource.disk, clusterModel.averageLoad(Resource.disk), current)
+                                  / clusterModel.idealLoad(Resource.disk),
                                   true);
     }
 
@@ -74,58 +70,4 @@ public class ResourceTarget {
                                   false);
     }
 
-    /** Ideal cpu load must take the application traffic fraction into account */
-    public static double idealCpuLoad(Duration scalingDuration,
-                                      ClusterTimeseries clusterTimeseries,
-                                      Application application,
-                                      Clock clock) {
-        double queryCpuFraction = queryCpuFraction(clusterTimeseries, scalingDuration, clock);
-
-        // What's needed to have headroom for growth during scale-up as a fraction of current resources?
-        double maxGrowthRate = clusterTimeseries.maxQueryGrowthRate(scalingDuration, clock); // in fraction per minute of the current traffic
-        double growthRateHeadroom = 1 + maxGrowthRate * scalingDuration.toMinutes();
-        // Cap headroom at 10% above the historical observed peak
-        double fractionOfMax = clusterTimeseries.queryFractionOfMax(scalingDuration, clock);
-        if (fractionOfMax != 0)
-            growthRateHeadroom = Math.min(growthRateHeadroom, 1 / fractionOfMax + 0.1);
-
-        // How much headroom is needed to handle sudden arrival of additional traffic due to another zone going down?
-        double maxTrafficShiftHeadroom = 10.0; // Cap to avoid extreme sizes from a current very small share
-        double trafficShiftHeadroom;
-        if (application.status().maxReadShare() == 0) // No traffic fraction data
-            trafficShiftHeadroom = 2.0; // assume we currently get half of the global share of traffic
-        else if (application.status().currentReadShare() == 0)
-            trafficShiftHeadroom = maxTrafficShiftHeadroom;
-        else
-            trafficShiftHeadroom = application.status().maxReadShare() / application.status().currentReadShare();
-        trafficShiftHeadroom = Math.min(trafficShiftHeadroom, maxTrafficShiftHeadroom);
-
-        // Assumptions: 1) Write load is not organic so we should not grow to handle more.
-        //                 (TODO: But allow applications to set their target write rate and size for that)
-        //              2) Write load does not change in BCP scenarios.
-        return queryCpuFraction * 1 / growthRateHeadroom * 1 / trafficShiftHeadroom * idealQueryCpuLoad() +
-               (1 - queryCpuFraction) * idealWriteCpuLoad();
-    }
-    
-    private static double queryCpuFraction(ClusterTimeseries clusterTimeseries, Duration scalingDuration, Clock clock) {
-        OptionalDouble queryRate = clusterTimeseries.queryRate(scalingDuration, clock);
-        OptionalDouble writeRate = clusterTimeseries.writeRate(scalingDuration, clock);
-        if (queryRate.orElse(0) == 0 && writeRate.orElse(0) == 0) return queryCpuFraction(0.5);
-        return queryCpuFraction(queryRate.orElse(0) / (queryRate.orElse(0) + writeRate.orElse(0)));
-    }
-
-    private static double queryCpuFraction(double queryFraction) {
-        double relativeQueryCost = 9; // How much more expensive are queries than writes? TODO: Measure
-        double writeFraction = 1 - queryFraction;
-        return queryFraction * relativeQueryCost / (queryFraction * relativeQueryCost + writeFraction);
-    }
-
-    public static double idealQueryCpuLoad() { return Resource.cpu.idealAverageLoad(); }
-
-    public static double idealWriteCpuLoad() { return 0.95; }
-
-    public static double idealMemoryLoad() { return Resource.memory.idealAverageLoad(); }
-
-    public static double idealDiskLoad() { return Resource.disk.idealAverageLoad(); }
-
 }
diff --git a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/restapi/ApplicationSerializer.java b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/restapi/ApplicationSerializer.java
index af2f8d0c239..93d760fe00e 100644
--- a/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/restapi/ApplicationSerializer.java
+++ b/node-repository/src/main/java/com/yahoo/vespa/hosted/provision/restapi/ApplicationSerializer.java
@@ -69,9 +69,7 @@ public class ApplicationSerializer {
         NodeList nodes = applicationNodes.not().retired().cluster(cluster.id());
         if (nodes.isEmpty()) return;
         ClusterResources currentResources = nodes.toResources();
-        ClusterModel clusterModel = new ClusterModel(application, cluster, nodes, metricsDb, nodeRepository);
-        var clusterNodesTimeseries = new ClusterNodesTimeseries(Duration.ofHours(1), cluster, nodes, metricsDb);
-        var clusterTimeseries = metricsDb.getClusterTimeseries(application.id(), cluster.id());
+        ClusterModel clusterModel = new ClusterModel(application, cluster, nodes, metricsDb, nodeRepository.clock());
 
         Cursor clusterObject = clustersObject.setObject(cluster.id().value());
         clusterObject.setString("type", nodes.clusterSpec().type().name());
@@ -81,12 +79,12 @@ public class ApplicationSerializer {
         if (cluster.shouldSuggestResources(currentResources))
             cluster.suggestedResources().ifPresent(suggested -> toSlime(suggested.resources(), clusterObject.setObject("suggested")));
         cluster.targetResources().ifPresent(target -> toSlime(target, clusterObject.setObject("target")));
-        clusterUtilizationToSlime(application, clusterModel.scalingDuration(), clusterTimeseries, clusterNodesTimeseries, metricsDb.clock(), clusterObject.setObject("utilization"));
+        clusterUtilizationToSlime(clusterModel, clusterObject.setObject("utilization"));
         scalingEventsToSlime(cluster.scalingEvents(), clusterObject.setArray("scalingEvents"));
         clusterObject.setString("autoscalingStatus", cluster.autoscalingStatus());
         clusterObject.setLong("scalingDuration", clusterModel.scalingDuration().toMillis());
-        clusterObject.setDouble("maxQueryGrowthRate", clusterTimeseries.maxQueryGrowthRate(clusterModel.scalingDuration(), metricsDb.clock()));
-        clusterObject.setDouble("currentQueryFractionOfMax", clusterTimeseries.queryFractionOfMax(clusterModel.scalingDuration(), metricsDb.clock()));
+        clusterObject.setDouble("maxQueryGrowthRate", clusterModel.clusterTimeseries().maxQueryGrowthRate(clusterModel.scalingDuration(), metricsDb.clock()));
+        clusterObject.setDouble("currentQueryFractionOfMax", clusterModel.clusterTimeseries().queryFractionOfMax(clusterModel.scalingDuration(), metricsDb.clock()));
     }
 
     private static void toSlime(ClusterResources resources, Cursor clusterResourcesObject) {
@@ -95,18 +93,13 @@ public class ApplicationSerializer {
         NodeResourcesSerializer.toSlime(resources.nodeResources(), clusterResourcesObject.setObject("resources"));
     }
 
-    private static void clusterUtilizationToSlime(Application application,
-                                                  Duration scalingDuration,
-                                                  ClusterTimeseries clusterTimeseries,
-                                                  ClusterNodesTimeseries clusterNodesTimeseries,
-                                                  Clock clock,
-                                                  Cursor utilizationObject) {
-        utilizationObject.setDouble("cpu", clusterNodesTimeseries.averageLoad(Resource.cpu));
-        utilizationObject.setDouble("idealCpu", ResourceTarget.idealCpuLoad(scalingDuration, clusterTimeseries, application, clock));
-        utilizationObject.setDouble("memory", clusterNodesTimeseries.averageLoad(Resource.memory));
-        utilizationObject.setDouble("idealMemory", ResourceTarget.idealMemoryLoad());
-        utilizationObject.setDouble("disk", clusterNodesTimeseries.averageLoad(Resource.disk));
-        utilizationObject.setDouble("idealDisk", ResourceTarget.idealDiskLoad());
+    private static void clusterUtilizationToSlime(ClusterModel clusterModel, Cursor utilizationObject) {
+        utilizationObject.setDouble("cpu", clusterModel.averageLoad(Resource.cpu));
+        utilizationObject.setDouble("idealCpu", clusterModel.idealLoad(Resource.cpu));
+        utilizationObject.setDouble("memory", clusterModel.averageLoad(Resource.memory));
+        utilizationObject.setDouble("idealMemory", clusterModel.idealLoad(Resource.memory));
+        utilizationObject.setDouble("disk", clusterModel.averageLoad(Resource.disk));
+        utilizationObject.setDouble("idealDisk", clusterModel.idealLoad(Resource.disk));
     }
 
     private static void scalingEventsToSlime(List<ScalingEvent> scalingEvents, Cursor scalingEventsArray) {
diff --git a/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTargetTest.java b/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java
index 6f60de62f1f..70550b0a7c3 100644
--- a/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ResourceTargetTest.java
+++ b/node-repository/src/test/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModelTest.java
@@ -22,7 +22,7 @@ import static org.junit.Assert.assertEquals;
 /**
  * @author bratseth
  */
-public class ResourceTargetTest {
+public class ClusterModelTest {
 
     private static final double delta = 0.001;
 
@@ -34,22 +34,16 @@ public class ResourceTargetTest {
         application = application.with(cluster);
 
         // No current traffic share: Ideal load is low but capped
-        application = application.with(new Status(0.0, 1.0));
-        assertEquals(0.131,
-                     ResourceTarget.idealCpuLoad(Duration.ofMinutes(10),
-                                                 timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
-                                                 application,
-                                                 clock),
-                     delta);
+        var model1 = new ClusterModel(application.with(new Status(0.0, 1.0)),
+                                      cluster, clock, Duration.ofMinutes(10),
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+        assertEquals(0.131, model1.idealLoad(Resource.cpu), delta);
 
         // Almost no current traffic share: Ideal load is low but capped
-        application = application.with(new Status(0.0001, 1.0));
-        assertEquals(0.131,
-                     ResourceTarget.idealCpuLoad(Duration.ofMinutes(10),
-                                                 timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
-                                                 application,
-                                                 clock),
-                     delta);
+        var model2 = new ClusterModel(application.with(new Status(0.0001, 1.0)),
+                                      cluster, clock, Duration.ofMinutes(10),
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+        assertEquals(0.131, model2.idealLoad(Resource.cpu), delta);
     }
 
     @Test
@@ -61,21 +55,16 @@ public class ResourceTargetTest {
         application = application.with(cluster);
 
         // No current traffic: Ideal load is low but capped
-        assertEquals(0.275,
-                     ResourceTarget.idealCpuLoad(Duration.ofMinutes(10),
-                                                 timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock),
-                                                 application,
-                                                 clock),
-                     delta);
+        var model1 = new ClusterModel(application,
+                                      cluster, clock, Duration.ofMinutes(10),
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0, t -> 0.0, clock));
+        assertEquals(0.275, model1.idealLoad(Resource.cpu), delta);
 
         // Almost current traffic: Ideal load is low but capped
-        application = application.with(new Status(0.0001, 1.0));
-        assertEquals(0.04,
-                     ResourceTarget.idealCpuLoad(Duration.ofMinutes(10),
-                                                 timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0001, t -> 0.0, clock),
-                                                 application,
-                                                 clock),
-                     delta);
+        var model2 = new ClusterModel(application.with(new Status(0.0001, 1.0)),
+                                      cluster, clock, Duration.ofMinutes(10),
+                                      timeseries(cluster,100, t -> t == 0 ? 10000.0 : 0.0001, t -> 0.0, clock));
+        assertEquals(0.275, model1.idealLoad(Resource.cpu), delta);
     }
 
     private Cluster cluster(NodeResources resources) {