package kubecost import ( "testing" "time" "github.com/kubecost/cost-model/pkg/util" ) func TestSummaryAllocation_Add(t *testing.T) { window, _ := ParseWindowUTC("yesterday") var sa1, sa2, osa1, osa2, nilsa *SummaryAllocation var err error sa1Start := *window.Start() sa1End := *window.End() sa1 = &SummaryAllocation{ Name: "cluster1/namespace1/pod1/container1", Properties: &AllocationProperties{ Cluster: "cluster1", Namespace: "namespace1", Pod: "pod1", Container: "container1", }, Start: sa1Start, End: sa1End, CPUCoreRequestAverage: 0.5, CPUCoreUsageAverage: 0.1, CPUCost: 0.2, GPUCost: 1.0, NetworkCost: 0.1, LoadBalancerCost: 0.6, PVCost: 0.005, RAMBytesRequestAverage: 50.0 * 1024.0 * 1024.0, RAMBytesUsageAverage: 10.0 * 1024.0 * 1024.0, RAMCost: 0.05, SharedCost: 1.0, ExternalCost: 1.0, } osa1 = sa1.Clone() // sa2 is just as expensive, with twice as much usage and request, and half // the time compared to sa1 sa2Start := *window.Start() sa2Start = sa2Start.Add(6 * time.Hour) sa2End := *window.End() sa2End = sa2End.Add(-6 * time.Hour) sa2 = &SummaryAllocation{ Name: "cluster1/namespace1/pod2/container2", Properties: &AllocationProperties{ Cluster: "cluster1", Namespace: "namespace1", Pod: "pod2", Container: "container2", }, Start: sa2Start, End: sa2End, CPUCoreRequestAverage: sa1.CPUCoreRequestAverage * 2.0, CPUCoreUsageAverage: sa1.CPUCoreUsageAverage * 2.0, CPUCost: sa1.CPUCost, GPUCost: sa1.GPUCost, NetworkCost: sa1.NetworkCost, LoadBalancerCost: sa1.LoadBalancerCost, PVCost: sa1.PVCost, RAMBytesRequestAverage: sa1.RAMBytesRequestAverage * 2.0, RAMBytesUsageAverage: sa1.RAMBytesUsageAverage * 2.0, RAMCost: sa1.RAMCost, SharedCost: sa1.SharedCost, ExternalCost: sa1.ExternalCost, } osa2 = sa2.Clone() // add nil to nil, expect and error t.Run("nil.Add(nil)", func(t *testing.T) { err = nilsa.Add(nilsa) if err == nil { t.Fatalf("expected error: cannot add nil SummaryAllocations") } }) // reset sa1 = osa1.Clone() sa2 = osa2.Clone() // add sa1 to nil, expect and error t.Run("nil.Add(sa1)", func(t *testing.T) { err = nilsa.Add(sa1) if err == nil { t.Fatalf("expected error: cannot add nil SummaryAllocations") } }) // reset sa1 = osa1.Clone() sa2 = osa2.Clone() // add nil to sa1, expect and error t.Run("sa1.Add(nil)", func(t *testing.T) { err = sa1.Add(nilsa) if err == nil { t.Fatalf("expected error: cannot add nil SummaryAllocations") } }) // reset sa1 = osa1.Clone() sa2 = osa2.Clone() // add sa1 to sa2 and expect same averages, but double costs t.Run("sa2.Add(sa1)", func(t *testing.T) { err = sa2.Add(sa1) if err != nil { t.Fatalf("unexpected error: %s", err) } if sa2.Properties != nil { t.Fatalf("expected properties to be nil; actual: %s", sa1.Properties) } if !util.IsApproximately(sa2.CPUCoreRequestAverage, (0.5*osa2.CPUCoreRequestAverage)+osa1.CPUCoreRequestAverage) { t.Fatalf("incorrect CPUCoreRequestAverage: expected %.5f; actual %.5f", (0.5*osa2.CPUCoreRequestAverage)+osa1.CPUCoreRequestAverage, sa2.CPUCoreRequestAverage) } if !util.IsApproximately(sa2.CPUCoreUsageAverage, (0.5*osa2.CPUCoreUsageAverage)+osa1.CPUCoreUsageAverage) { t.Fatalf("incorrect CPUCoreUsageAverage: expected %.5f; actual %.5f", (0.5*osa2.CPUCoreUsageAverage)+osa1.CPUCoreRequestAverage, sa2.CPUCoreUsageAverage) } if !util.IsApproximately(sa2.RAMBytesRequestAverage, (0.5*osa2.RAMBytesRequestAverage)+osa1.RAMBytesRequestAverage) { t.Fatalf("incorrect RAMBytesRequestAverage: expected %.5f; actual %.5f", (0.5*osa2.RAMBytesRequestAverage)+osa1.RAMBytesRequestAverage, sa2.RAMBytesRequestAverage) } if !util.IsApproximately(sa2.RAMBytesUsageAverage, (0.5*osa2.RAMBytesUsageAverage)+osa1.RAMBytesUsageAverage) { t.Fatalf("incorrect RAMBytesUsageAverage: expected %.5f; actual %.5f", (0.5*osa2.RAMBytesUsageAverage)+osa1.RAMBytesRequestAverage, sa2.RAMBytesUsageAverage) } if !util.IsApproximately(sa2.CPUCost, osa2.CPUCost+osa1.CPUCost) { t.Fatalf("incorrect CPUCost: expected %.5f; actual %.5f", osa2.CPUCost+osa1.CPUCost, sa2.CPUCost) } if !util.IsApproximately(sa2.GPUCost, osa2.GPUCost+osa1.GPUCost) { t.Fatalf("incorrect GPUCost: expected %.5f; actual %.5f", osa2.GPUCost+osa1.GPUCost, sa2.GPUCost) } if !util.IsApproximately(sa2.NetworkCost, osa2.NetworkCost+osa1.NetworkCost) { t.Fatalf("incorrect NetworkCost: expected %.5f; actual %.5f", osa2.NetworkCost+osa1.NetworkCost, sa2.NetworkCost) } if !util.IsApproximately(sa2.LoadBalancerCost, osa2.LoadBalancerCost+osa1.LoadBalancerCost) { t.Fatalf("incorrect LoadBalancerCost: expected %.5f; actual %.5f", osa2.LoadBalancerCost+osa1.LoadBalancerCost, sa2.LoadBalancerCost) } if !util.IsApproximately(sa2.PVCost, osa2.PVCost+osa1.PVCost) { t.Fatalf("incorrect PVCost: expected %.5f; actual %.5f", osa2.PVCost+osa1.PVCost, sa2.PVCost) } if !util.IsApproximately(sa2.RAMCost, osa2.RAMCost+osa1.RAMCost) { t.Fatalf("incorrect RAMCost: expected %.5f; actual %.5f", osa2.RAMCost+osa1.RAMCost, sa2.RAMCost) } if !util.IsApproximately(sa2.SharedCost, osa2.SharedCost+osa1.SharedCost) { t.Fatalf("incorrect SharedCost: expected %.5f; actual %.5f", osa2.SharedCost+osa1.SharedCost, sa2.SharedCost) } if !util.IsApproximately(sa2.ExternalCost, osa2.ExternalCost+osa1.ExternalCost) { t.Fatalf("incorrect ExternalCost: expected %.5f; actual %.5f", osa2.ExternalCost+osa1.ExternalCost, sa2.ExternalCost) } }) // reset sa1 = osa1.Clone() sa2 = osa2.Clone() // add sa2 to sa1 and expect same averages, but double costs t.Run("sa1.Add(sa2)", func(t *testing.T) { err = sa1.Add(sa2) if err != nil { t.Fatalf("unexpected error: %s", err) } if sa1.Properties != nil { t.Fatalf("expected properties to be nil; actual: %s", sa1.Properties) } if !util.IsApproximately(sa1.CPUCoreRequestAverage, (0.5*osa2.CPUCoreRequestAverage)+osa1.CPUCoreRequestAverage) { t.Fatalf("incorrect CPUCoreRequestAverage: expected %.5f; actual %.5f", (0.5*osa2.CPUCoreRequestAverage)+osa1.CPUCoreRequestAverage, sa2.CPUCoreRequestAverage) } if !util.IsApproximately(sa1.CPUCoreUsageAverage, (0.5*osa2.CPUCoreUsageAverage)+osa1.CPUCoreUsageAverage) { t.Fatalf("incorrect CPUCoreUsageAverage: expected %.5f; actual %.5f", (0.5*osa2.CPUCoreUsageAverage)+osa1.CPUCoreRequestAverage, sa2.CPUCoreUsageAverage) } if !util.IsApproximately(sa1.RAMBytesRequestAverage, (0.5*osa2.RAMBytesRequestAverage)+osa1.RAMBytesRequestAverage) { t.Fatalf("incorrect RAMBytesRequestAverage: expected %.5f; actual %.5f", (0.5*osa2.RAMBytesRequestAverage)+osa1.RAMBytesRequestAverage, sa2.RAMBytesRequestAverage) } if !util.IsApproximately(sa1.RAMBytesUsageAverage, (0.5*osa2.RAMBytesUsageAverage)+osa1.RAMBytesUsageAverage) { t.Fatalf("incorrect RAMBytesUsageAverage: expected %.5f; actual %.5f", (0.5*osa2.RAMBytesUsageAverage)+osa1.RAMBytesRequestAverage, sa2.RAMBytesUsageAverage) } if !util.IsApproximately(sa1.CPUCost, osa2.CPUCost+osa1.CPUCost) { t.Fatalf("incorrect CPUCost: expected %.5f; actual %.5f", osa2.CPUCost+osa1.CPUCost, sa2.CPUCost) } if !util.IsApproximately(sa1.GPUCost, osa2.GPUCost+osa1.GPUCost) { t.Fatalf("incorrect GPUCost: expected %.5f; actual %.5f", osa2.GPUCost+osa1.GPUCost, sa2.GPUCost) } if !util.IsApproximately(sa1.NetworkCost, osa2.NetworkCost+osa1.NetworkCost) { t.Fatalf("incorrect NetworkCost: expected %.5f; actual %.5f", osa2.NetworkCost+osa1.NetworkCost, sa2.NetworkCost) } if !util.IsApproximately(sa1.LoadBalancerCost, osa2.LoadBalancerCost+osa1.LoadBalancerCost) { t.Fatalf("incorrect LoadBalancerCost: expected %.5f; actual %.5f", osa2.LoadBalancerCost+osa1.LoadBalancerCost, sa2.LoadBalancerCost) } if !util.IsApproximately(sa1.PVCost, osa2.PVCost+osa1.PVCost) { t.Fatalf("incorrect PVCost: expected %.5f; actual %.5f", osa2.PVCost+osa1.PVCost, sa2.PVCost) } if !util.IsApproximately(sa1.RAMCost, osa2.RAMCost+osa1.RAMCost) { t.Fatalf("incorrect RAMCost: expected %.5f; actual %.5f", osa2.RAMCost+osa1.RAMCost, sa2.RAMCost) } if !util.IsApproximately(sa1.SharedCost, osa2.SharedCost+osa1.SharedCost) { t.Fatalf("incorrect SharedCost: expected %.5f; actual %.5f", osa2.SharedCost+osa1.SharedCost, sa2.SharedCost) } if !util.IsApproximately(sa1.ExternalCost, osa2.ExternalCost+osa1.ExternalCost) { t.Fatalf("incorrect ExternalCost: expected %.5f; actual %.5f", osa2.ExternalCost+osa1.ExternalCost, sa2.ExternalCost) } }) }