diff --git a/pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go b/pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go
index eec4248ec7..68f78ffc6c 100644
--- a/pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go
+++ b/pkg/types/querybuildertypes/querybuildertypesv5/builder_elements.go
@@ -207,7 +207,7 @@ type SecondaryAggregation struct {
 
 type Function struct {
 	// name of the function
-	Name string `json:"name"`
+	Name FunctionName `json:"name"`
 
 	// args is the arguments to the function
 	Args []struct {
diff --git a/pkg/types/querybuildertypes/querybuildertypesv5/functions.go b/pkg/types/querybuildertypes/querybuildertypesv5/functions.go
index a3c58349c6..679e7c9095 100644
--- a/pkg/types/querybuildertypes/querybuildertypesv5/functions.go
+++ b/pkg/types/querybuildertypes/querybuildertypesv5/functions.go
@@ -1,27 +1,489 @@
 package querybuildertypesv5
 
-import "github.com/SigNoz/signoz/pkg/valuer"
+import (
+	"math"
+	"sort"
+	"strconv"
+
+	"github.com/SigNoz/signoz/pkg/valuer"
+)
 
 type FunctionName struct {
 	valuer.String
 }
 
 var (
-	FunctionNameCutOffMin   = FunctionName{valuer.NewString("cutOffMin")}
-	FunctionNameCutOffMax   = FunctionName{valuer.NewString("cutOffMax")}
-	FunctionNameClampMin    = FunctionName{valuer.NewString("clampMin")}
-	FunctionNameClampMax    = FunctionName{valuer.NewString("clampMax")}
-	FunctionNameAbsolute    = FunctionName{valuer.NewString("absolute")}
-	FunctionNameRunningDiff = FunctionName{valuer.NewString("runningDiff")}
-	FunctionNameLog2        = FunctionName{valuer.NewString("log2")}
-	FunctionNameLog10       = FunctionName{valuer.NewString("log10")}
-	FunctionNameCumSum      = FunctionName{valuer.NewString("cumSum")}
-	FunctionNameEWMA3       = FunctionName{valuer.NewString("ewma3")}
-	FunctionNameEWMA5       = FunctionName{valuer.NewString("ewma5")}
-	FunctionNameEWMA7       = FunctionName{valuer.NewString("ewma7")}
-	FunctionNameMedian3     = FunctionName{valuer.NewString("median3")}
-	FunctionNameMedian5     = FunctionName{valuer.NewString("median5")}
-	FunctionNameMedian7     = FunctionName{valuer.NewString("median7")}
-	FunctionNameTimeShift   = FunctionName{valuer.NewString("timeShift")}
-	FunctionNameAnomaly     = FunctionName{valuer.NewString("anomaly")}
+	FunctionNameCutOffMin     = FunctionName{valuer.NewString("cutoff_min")}
+	FunctionNameCutOffMax     = FunctionName{valuer.NewString("cutoff_max")}
+	FunctionNameClampMin      = FunctionName{valuer.NewString("clamp_min")}
+	FunctionNameClampMax      = FunctionName{valuer.NewString("clamp_max")}
+	FunctionNameAbsolute      = FunctionName{valuer.NewString("absolute")}
+	FunctionNameRunningDiff   = FunctionName{valuer.NewString("running_diff")}
+	FunctionNameLog2          = FunctionName{valuer.NewString("log2")}
+	FunctionNameLog10         = FunctionName{valuer.NewString("log10")}
+	FunctionNameCumulativeSum = FunctionName{valuer.NewString("cumulative_sum")}
+	FunctionNameEWMA3         = FunctionName{valuer.NewString("ewma3")}
+	FunctionNameEWMA5         = FunctionName{valuer.NewString("ewma5")}
+	FunctionNameEWMA7         = FunctionName{valuer.NewString("ewma7")}
+	FunctionNameMedian3       = FunctionName{valuer.NewString("median3")}
+	FunctionNameMedian5       = FunctionName{valuer.NewString("median5")}
+	FunctionNameMedian7       = FunctionName{valuer.NewString("median7")}
+	FunctionNameTimeShift     = FunctionName{valuer.NewString("time_shift")}
+	FunctionNameAnomaly       = FunctionName{valuer.NewString("anomaly")}
 )
+
+// ApplyFunction applies the given function to the result data
+func ApplyFunction(fn Function, result *Result) *Result {
+	// Extract the function name and arguments
+	name := fn.Name
+	args := fn.Args
+
+	switch name {
+	case FunctionNameCutOffMin, FunctionNameCutOffMax, FunctionNameClampMin, FunctionNameClampMax:
+		if len(args) == 0 {
+			return result
+		}
+		threshold, err := parseFloat64Arg(args[0].Value)
+		if err != nil {
+			return result
+		}
+		switch name {
+		case FunctionNameCutOffMin:
+			return funcCutOffMin(result, threshold)
+		case FunctionNameCutOffMax:
+			return funcCutOffMax(result, threshold)
+		case FunctionNameClampMin:
+			return funcClampMin(result, threshold)
+		case FunctionNameClampMax:
+			return funcClampMax(result, threshold)
+		}
+	case FunctionNameAbsolute:
+		return funcAbsolute(result)
+	case FunctionNameRunningDiff:
+		return funcRunningDiff(result)
+	case FunctionNameLog2:
+		return funcLog2(result)
+	case FunctionNameLog10:
+		return funcLog10(result)
+	case FunctionNameCumulativeSum:
+		return funcCumulativeSum(result)
+	case FunctionNameEWMA3, FunctionNameEWMA5, FunctionNameEWMA7:
+		alpha := getEWMAAlpha(name, args)
+		return funcEWMA(result, alpha)
+	case FunctionNameMedian3:
+		return funcMedian3(result)
+	case FunctionNameMedian5:
+		return funcMedian5(result)
+	case FunctionNameMedian7:
+		return funcMedian7(result)
+	case FunctionNameTimeShift:
+		if len(args) == 0 {
+			return result
+		}
+		shift, err := parseFloat64Arg(args[0].Value)
+		if err != nil {
+			return result
+		}
+		return funcTimeShift(result, shift)
+	case FunctionNameAnomaly:
+		// Placeholder for anomaly detection - would need more sophisticated implementation
+		return result
+	}
+	return result
+}
+
+// parseFloat64Arg parses a string argument to float64
+func parseFloat64Arg(value string) (float64, error) {
+	return strconv.ParseFloat(value, 64)
+}
+
+// getEWMAAlpha calculates the alpha value for EWMA functions
+func getEWMAAlpha(name FunctionName, args []struct {
+	Name  string `json:"name,omitempty"`
+	Value string `json:"value"`
+}) float64 {
+	// Try to get alpha from arguments first
+	if len(args) > 0 {
+		if alpha, err := parseFloat64Arg(args[0].Value); err == nil {
+			return alpha
+		}
+	}
+
+	// Default alpha values: alpha = 2 / (n + 1) where n is the window size
+	switch name {
+	case FunctionNameEWMA3:
+		return 0.5 // 2 / (3 + 1)
+	case FunctionNameEWMA5:
+		return 1.0 / 3.0 // 2 / (5 + 1)
+	case FunctionNameEWMA7:
+		return 0.25 // 2 / (7 + 1)
+	}
+	return 0.5 // default
+}
+
+// funcCutOffMin cuts off values below the threshold and replaces them with NaN
+func funcCutOffMin(result *Result, threshold float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				if point.Value < threshold {
+					point.Value = math.NaN()
+				}
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcCutOffMax cuts off values above the threshold and replaces them with NaN
+func funcCutOffMax(result *Result, threshold float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				if point.Value > threshold {
+					point.Value = math.NaN()
+				}
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcClampMin cuts off values below the threshold and replaces them with the threshold
+func funcClampMin(result *Result, threshold float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				if point.Value < threshold {
+					point.Value = threshold
+				}
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcClampMax cuts off values above the threshold and replaces them with the threshold
+func funcClampMax(result *Result, threshold float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				if point.Value > threshold {
+					point.Value = threshold
+				}
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcAbsolute returns the absolute value of each point
+func funcAbsolute(result *Result) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				point.Value = math.Abs(point.Value)
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcRunningDiff returns the running difference of each point
+func funcRunningDiff(result *Result) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			// iterate over the points in reverse order
+			for idx := len(series.Values) - 1; idx >= 0; idx-- {
+				if idx > 0 {
+					series.Values[idx].Value = series.Values[idx].Value - series.Values[idx-1].Value
+				}
+			}
+			// remove the first point
+			if len(series.Values) > 0 {
+				series.Values = series.Values[1:]
+			}
+		}
+	}
+	return result
+}
+
+// funcLog2 returns the log2 of each point
+func funcLog2(result *Result) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				point.Value = math.Log2(point.Value)
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcLog10 returns the log10 of each point
+func funcLog10(result *Result) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				point.Value = math.Log10(point.Value)
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcCumulativeSum returns the cumulative sum for each point in a series
+func funcCumulativeSum(result *Result) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			var sum float64
+			for idx, point := range series.Values {
+				if !math.IsNaN(point.Value) {
+					sum += point.Value
+				}
+				point.Value = sum
+				series.Values[idx] = point
+			}
+		}
+	}
+	return result
+}
+
+// funcEWMA calculates the Exponentially Weighted Moving Average
+func funcEWMA(result *Result, alpha float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			var ewma float64
+			var initialized bool
+
+			for i, point := range series.Values {
+				if !initialized {
+					if !math.IsNaN(point.Value) {
+						// Initialize EWMA with the first non-NaN value
+						ewma = point.Value
+						initialized = true
+					}
+					// Continue until the EWMA is initialized
+					continue
+				}
+
+				if !math.IsNaN(point.Value) {
+					// Update EWMA with the current value
+					ewma = alpha*point.Value + (1-alpha)*ewma
+				}
+				// Set the EWMA value for the current point
+				series.Values[i].Value = ewma
+			}
+		}
+	}
+	return result
+}
+
+// funcMedian3 returns the median of 3 points for each point in a series
+func funcMedian3(result *Result) *Result {
+	return funcMedianN(result, 3)
+}
+
+// funcMedian5 returns the median of 5 points for each point in a series
+func funcMedian5(result *Result) *Result {
+	return funcMedianN(result, 5)
+}
+
+// funcMedian7 returns the median of 7 points for each point in a series
+func funcMedian7(result *Result) *Result {
+	return funcMedianN(result, 7)
+}
+
+// funcMedianN returns the median of N points for each point in a series
+func funcMedianN(result *Result, n int) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	halfWindow := n / 2
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			medianValues := make([]*TimeSeriesValue, 0)
+
+			for i := halfWindow; i < len(series.Values)-halfWindow; i++ {
+				values := make([]float64, 0, n)
+
+				// Add non-NaN values to the slice
+				for j := -halfWindow; j <= halfWindow; j++ {
+					if !math.IsNaN(series.Values[i+j].Value) {
+						values = append(values, series.Values[i+j].Value)
+					}
+				}
+
+				// Create a new point with median value
+				newPoint := &TimeSeriesValue{
+					Timestamp: series.Values[i].Timestamp,
+				}
+
+				// Handle the case where there are not enough values to calculate a median
+				if len(values) == 0 {
+					newPoint.Value = math.NaN()
+				} else {
+					newPoint.Value = median(values)
+				}
+
+				medianValues = append(medianValues, newPoint)
+			}
+
+			// Replace the series values with median values
+			// Keep the original edge points unchanged
+			for i := halfWindow; i < len(series.Values)-halfWindow; i++ {
+				series.Values[i] = medianValues[i-halfWindow]
+			}
+		}
+	}
+	return result
+}
+
+// median calculates the median of a slice of float64 values
+func median(values []float64) float64 {
+	if len(values) == 0 {
+		return math.NaN()
+	}
+
+	sort.Float64s(values)
+	medianIndex := len(values) / 2
+	if len(values)%2 == 0 {
+		return (values[medianIndex-1] + values[medianIndex]) / 2
+	}
+	return values[medianIndex]
+}
+
+// funcTimeShift shifts all timestamps by the given amount (in seconds)
+func funcTimeShift(result *Result, shift float64) *Result {
+	if result.Type != RequestTypeTimeSeries {
+		return result
+	}
+
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok {
+		return result
+	}
+
+	shiftMs := int64(shift * 1000) // Convert seconds to milliseconds
+
+	for _, aggregation := range timeSeriesData.Aggregations {
+		for _, series := range aggregation.Series {
+			for idx, point := range series.Values {
+				series.Values[idx].Timestamp = point.Timestamp + shiftMs
+			}
+		}
+	}
+	return result
+}
+
+// ApplyFunctions applies a list of functions sequentially to the result
+func ApplyFunctions(functions []Function, result *Result) *Result {
+	for _, fn := range functions {
+		result = ApplyFunction(fn, result)
+	}
+	return result
+}
diff --git a/pkg/types/querybuildertypes/querybuildertypesv5/functions_test.go b/pkg/types/querybuildertypes/querybuildertypesv5/functions_test.go
new file mode 100644
index 0000000000..c1faea09b2
--- /dev/null
+++ b/pkg/types/querybuildertypes/querybuildertypesv5/functions_test.go
@@ -0,0 +1,712 @@
+package querybuildertypesv5
+
+import (
+	"math"
+	"testing"
+)
+
+// Helper function to create test time series data
+func createTestTimeSeriesData(values []float64) *Result {
+	timeSeriesValues := make([]*TimeSeriesValue, len(values))
+	for i, val := range values {
+		timeSeriesValues[i] = &TimeSeriesValue{
+			Timestamp: int64(i + 1),
+			Value:     val,
+		}
+	}
+
+	series := &TimeSeries{
+		Values: timeSeriesValues,
+	}
+
+	aggregation := &AggregationBucket{
+		Index:  0,
+		Alias:  "test",
+		Series: []*TimeSeries{series},
+	}
+
+	timeSeriesData := &TimeSeriesData{
+		QueryName:    "test",
+		Aggregations: []*AggregationBucket{aggregation},
+	}
+
+	return &Result{
+		Type:  RequestTypeTimeSeries,
+		Value: timeSeriesData,
+	}
+}
+
+// Helper function to extract values from result for comparison
+func extractValues(result *Result) []float64 {
+	timeSeriesData, ok := result.Value.(*TimeSeriesData)
+	if !ok || len(timeSeriesData.Aggregations) == 0 || len(timeSeriesData.Aggregations[0].Series) == 0 {
+		return nil
+	}
+
+	series := timeSeriesData.Aggregations[0].Series[0]
+	values := make([]float64, len(series.Values))
+	for i, point := range series.Values {
+		values[i] = point.Value
+	}
+	return values
+}
+
+func TestFuncCutOffMin(t *testing.T) {
+	tests := []struct {
+		name      string
+		values    []float64
+		threshold float64
+		want      []float64
+	}{
+		{
+			name:      "test funcCutOffMin",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0.3,
+			want:      []float64{0.5, 0.4, 0.3, math.NaN(), math.NaN()},
+		},
+		{
+			name:      "test funcCutOffMin with threshold 0",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0,
+			want:      []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcCutOffMin(result, tt.threshold)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcCutOffMin() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(got[i]) {
+						t.Errorf("funcCutOffMin() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				} else {
+					if got[i] != tt.want[i] {
+						t.Errorf("funcCutOffMin() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestFuncCutOffMax(t *testing.T) {
+	tests := []struct {
+		name      string
+		values    []float64
+		threshold float64
+		want      []float64
+	}{
+		{
+			name:      "test funcCutOffMax",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0.3,
+			want:      []float64{math.NaN(), math.NaN(), 0.3, 0.2, 0.1},
+		},
+		{
+			name:      "test funcCutOffMax with threshold 0",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0,
+			want:      []float64{math.NaN(), math.NaN(), math.NaN(), math.NaN(), math.NaN()},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcCutOffMax(result, tt.threshold)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcCutOffMax() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(got[i]) {
+						t.Errorf("funcCutOffMax() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				} else {
+					if got[i] != tt.want[i] {
+						t.Errorf("funcCutOffMax() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestCutOffMinCumSum(t *testing.T) {
+	tests := []struct {
+		name      string
+		values    []float64
+		threshold float64
+		want      []float64
+	}{
+		{
+			name:      "test funcCutOffMin followed by funcCumulativeSum",
+			values:    []float64{0.5, 0.2, 0.1, 0.4, 0.3},
+			threshold: 0.3,
+			want:      []float64{0.5, 0.5, 0.5, 0.9, 1.2},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcCutOffMin(result, tt.threshold)
+			newResult = funcCumulativeSum(newResult)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("CutOffMin+CumSum got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(got[i]) {
+						t.Errorf("CutOffMin+CumSum at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				} else {
+					if got[i] != tt.want[i] {
+						t.Errorf("CutOffMin+CumSum at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestFuncMedian3(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "Values",
+			values: []float64{5, 3, 8, 2, 7},
+			want:   []float64{5, 5, 3, 7, 7}, // edge values unchanged, middle values are median of 3
+		},
+		{
+			name:   "NaNHandling",
+			values: []float64{math.NaN(), 3, math.NaN(), 7, 9},
+			want:   []float64{math.NaN(), 3, 5, 8, 9}, // median of available values
+		},
+		{
+			name:   "UniformValues",
+			values: []float64{7, 7, 7, 7, 7},
+			want:   []float64{7, 7, 7, 7, 7},
+		},
+		{
+			name:   "SingleValueSeries",
+			values: []float64{9},
+			want:   []float64{9},
+		},
+		{
+			name:   "EmptySeries",
+			values: []float64{},
+			want:   []float64{},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			got := funcMedian3(result)
+			gotValues := extractValues(got)
+
+			if len(gotValues) != len(tt.want) {
+				t.Errorf("funcMedian3() got length %d, want length %d", len(gotValues), len(tt.want))
+				return
+			}
+
+			for i := range gotValues {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(gotValues[i]) {
+						t.Errorf("funcMedian3() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
+					}
+				} else {
+					if gotValues[i] != tt.want[i] {
+						t.Errorf("funcMedian3() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestFuncMedian5(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "Values",
+			values: []float64{5, 3, 8, 2, 7, 9, 1, 4, 6, 10},
+			want:   []float64{5, 3, 5, 7, 7, 4, 6, 6, 6, 10}, // edge values unchanged
+		},
+		{
+			name:   "NaNHandling",
+			values: []float64{math.NaN(), 3, math.NaN(), 7, 9, 1, 4, 6, 10, 2},
+			want:   []float64{math.NaN(), 3, 7, 5, 5.5, 6, 6, 4, 10, 2}, // median of available values
+		},
+		{
+			name:   "UniformValues",
+			values: []float64{7, 7, 7, 7, 7},
+			want:   []float64{7, 7, 7, 7, 7},
+		},
+		{
+			name:   "SingleValueSeries",
+			values: []float64{9},
+			want:   []float64{9},
+		},
+		{
+			name:   "EmptySeries",
+			values: []float64{},
+			want:   []float64{},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			got := funcMedian5(result)
+			gotValues := extractValues(got)
+
+			if len(gotValues) != len(tt.want) {
+				t.Errorf("funcMedian5() got length %d, want length %d", len(gotValues), len(tt.want))
+				return
+			}
+
+			for i := range gotValues {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(gotValues[i]) {
+						t.Errorf("funcMedian5() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
+					}
+				} else {
+					if gotValues[i] != tt.want[i] {
+						t.Errorf("funcMedian5() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestFuncRunningDiff(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "test funcRunningDiff",
+			values: []float64{1, 2, 3},
+			want:   []float64{1, 1}, // diff removes first element
+		},
+		{
+			name:   "test funcRunningDiff with start number as 8",
+			values: []float64{8, 8, 8},
+			want:   []float64{0, 0},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			got := funcRunningDiff(result)
+			gotValues := extractValues(got)
+
+			if len(gotValues) != len(tt.want) {
+				t.Errorf("funcRunningDiff() got length %d, want length %d", len(gotValues), len(tt.want))
+				return
+			}
+
+			for i := range gotValues {
+				if gotValues[i] != tt.want[i] {
+					t.Errorf("funcRunningDiff() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncClampMin(t *testing.T) {
+	tests := []struct {
+		name      string
+		values    []float64
+		threshold float64
+		want      []float64
+	}{
+		{
+			name:      "test funcClampMin",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0.3,
+			want:      []float64{0.5, 0.4, 0.3, 0.3, 0.3},
+		},
+		{
+			name:      "test funcClampMin with threshold 0",
+			values:    []float64{-0.5, -0.4, 0.3, 0.2, 0.1},
+			threshold: 0,
+			want:      []float64{0, 0, 0.3, 0.2, 0.1},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcClampMin(result, tt.threshold)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcClampMin() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if got[i] != tt.want[i] {
+					t.Errorf("funcClampMin() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncClampMax(t *testing.T) {
+	tests := []struct {
+		name      string
+		values    []float64
+		threshold float64
+		want      []float64
+	}{
+		{
+			name:      "test funcClampMax",
+			values:    []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			threshold: 0.3,
+			want:      []float64{0.3, 0.3, 0.3, 0.2, 0.1},
+		},
+		{
+			name:      "test funcClampMax with threshold 1.0",
+			values:    []float64{2.5, 0.4, 1.3, 0.2, 0.1},
+			threshold: 1.0,
+			want:      []float64{1.0, 0.4, 1.0, 0.2, 0.1},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcClampMax(result, tt.threshold)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcClampMax() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if got[i] != tt.want[i] {
+					t.Errorf("funcClampMax() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncAbsolute(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "test funcAbsolute",
+			values: []float64{-0.5, 0.4, -0.3, 0.2, -0.1},
+			want:   []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+		},
+		{
+			name:   "test funcAbsolute with all positive",
+			values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			want:   []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcAbsolute(result)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcAbsolute() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if got[i] != tt.want[i] {
+					t.Errorf("funcAbsolute() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncLog2(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "test funcLog2",
+			values: []float64{1, 2, 4, 8, 16},
+			want:   []float64{0, 1, 2, 3, 4},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcLog2(result)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcLog2() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.Abs(got[i]-tt.want[i]) > 1e-10 {
+					t.Errorf("funcLog2() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncLog10(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "test funcLog10",
+			values: []float64{1, 10, 100, 1000},
+			want:   []float64{0, 1, 2, 3},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcLog10(result)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcLog10() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.Abs(got[i]-tt.want[i]) > 1e-10 {
+					t.Errorf("funcLog10() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncCumSum(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		want   []float64
+	}{
+		{
+			name:   "test funcCumSum",
+			values: []float64{1, 2, 3, 4, 5},
+			want:   []float64{1, 3, 6, 10, 15},
+		},
+		{
+			name:   "test funcCumSum with NaN",
+			values: []float64{1, math.NaN(), 3, 4, 5},
+			want:   []float64{1, 1, 4, 8, 13}, // NaN is ignored
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcCumulativeSum(result)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcCumSum() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if got[i] != tt.want[i] {
+					t.Errorf("funcCumSum() at index %d = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestFuncTimeShift(t *testing.T) {
+	tests := []struct {
+		name   string
+		values []float64
+		shift  float64
+		want   []int64 // expected timestamps
+	}{
+		{
+			name:   "test funcTimeShift positive",
+			values: []float64{1, 2, 3},
+			shift:  5.0,                       // 5 seconds
+			want:   []int64{6000, 7000, 8000}, // original timestamps (1,2,3) + 5000ms
+		},
+		{
+			name:   "test funcTimeShift negative",
+			values: []float64{1, 2, 3},
+			shift:  -2.0,                    // -2 seconds
+			want:   []int64{-1000, 0, 1000}, // original timestamps (1,2,3) - 2000ms
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := funcTimeShift(result, tt.shift)
+
+			timeSeriesData, ok := newResult.Value.(*TimeSeriesData)
+			if !ok {
+				t.Errorf("funcTimeShift() failed to get time series data")
+				return
+			}
+
+			series := timeSeriesData.Aggregations[0].Series[0]
+			got := make([]int64, len(series.Values))
+			for i, point := range series.Values {
+				got[i] = point.Timestamp
+			}
+
+			if len(got) != len(tt.want) {
+				t.Errorf("funcTimeShift() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if got[i] != tt.want[i] {
+					t.Errorf("funcTimeShift() at index %d timestamp = %v, want %v", i, got[i], tt.want[i])
+				}
+			}
+		})
+	}
+}
+
+func TestApplyFunction(t *testing.T) {
+	tests := []struct {
+		name     string
+		function Function
+		values   []float64
+		want     []float64
+	}{
+		{
+			name: "cutOffMin function",
+			function: Function{
+				Name: FunctionNameCutOffMin,
+				Args: []struct {
+					Name  string `json:"name,omitempty"`
+					Value string `json:"value"`
+				}{
+					{Value: "0.3"},
+				},
+			},
+			values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+			want:   []float64{0.5, 0.4, 0.3, math.NaN(), math.NaN()},
+		},
+		{
+			name: "absolute function",
+			function: Function{
+				Name: FunctionNameAbsolute,
+			},
+			values: []float64{-0.5, 0.4, -0.3, 0.2, -0.1},
+			want:   []float64{0.5, 0.4, 0.3, 0.2, 0.1},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := createTestTimeSeriesData(tt.values)
+			newResult := ApplyFunction(tt.function, result)
+			got := extractValues(newResult)
+
+			if len(got) != len(tt.want) {
+				t.Errorf("ApplyFunction() got length %d, want length %d", len(got), len(tt.want))
+				return
+			}
+
+			for i := range got {
+				if math.IsNaN(tt.want[i]) {
+					if !math.IsNaN(got[i]) {
+						t.Errorf("ApplyFunction() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				} else {
+					if got[i] != tt.want[i] {
+						t.Errorf("ApplyFunction() at index %d = %v, want %v", i, got[i], tt.want[i])
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestApplyFunctions(t *testing.T) {
+	functions := []Function{
+		{
+			Name: FunctionNameCutOffMin,
+			Args: []struct {
+				Name  string `json:"name,omitempty"`
+				Value string `json:"value"`
+			}{
+				{Value: "0.3"},
+			},
+		},
+		{
+			Name: FunctionNameCumulativeSum,
+		},
+	}
+
+	values := []float64{0.5, 0.2, 0.1, 0.4, 0.3}
+	want := []float64{0.5, 0.5, 0.5, 0.9, 1.2}
+
+	result := createTestTimeSeriesData(values)
+	newResult := ApplyFunctions(functions, result)
+	got := extractValues(newResult)
+
+	if len(got) != len(want) {
+		t.Errorf("ApplyFunctions() got length %d, want length %d", len(got), len(want))
+		return
+	}
+
+	for i := range got {
+		if got[i] != want[i] {
+			t.Errorf("ApplyFunctions() at index %d = %v, want %v", i, got[i], want[i])
+		}
+	}
+}
diff --git a/pkg/types/querybuildertypes/querybuildertypesv5/req_test.go b/pkg/types/querybuildertypes/querybuildertypesv5/req_test.go
index 60dc24b825..176b34b8f4 100644
--- a/pkg/types/querybuildertypes/querybuildertypesv5/req_test.go
+++ b/pkg/types/querybuildertypes/querybuildertypesv5/req_test.go
@@ -249,7 +249,7 @@ func TestQueryRangeRequest_UnmarshalJSON(t *testing.T) {
 							Name:       "error_rate",
 							Expression: "A / B * 100",
 							Functions: []Function{{
-								Name: "absolute",
+								Name: FunctionNameAbsolute,
 								Args: []struct {
 									Name  string `json:"name,omitempty"`
 									Value string `json:"value"`