Time series anomaly detection for total volume of traffic

Original query, unchanged.

let starttime = 14d;
let endtime = 1d;
let timeframe = 1h;
let scorethreshold = 5;
let percentotalthreshold = 50;
let TimeSeriesData = CommonSecurityLog
| where isnotempty(DestinationIP) and isnotempty(SourceIP)
| where TimeGenerated between (startofday(ago(starttime))..startofday(ago(endtime)))
| project TimeGenerated,SourceIP, DestinationIP, DeviceVendor
| make-series Total=count() on TimeGenerated from startofday(ago(starttime)) to startofday(ago(endtime)) step timeframe by DeviceVendor;
// Filtering specific records associated with spikes as outliers
let TimeSeriesAlerts=materialize(TimeSeriesData
| extend (anomalies, score, baseline) = series_decompose_anomalies(Total, scorethreshold, -1, 'linefit')
| mv-expand Total to typeof(double), TimeGenerated to typeof(datetime), anomalies to typeof(double),score to typeof(double), baseline to typeof(long)
| where anomalies > 0 | extend score = round(score,2), AnomalyHour = TimeGenerated
| project DeviceVendor,AnomalyHour, TimeGenerated, Total, baseline, anomalies, score);
let AnomalyHours = materialize(TimeSeriesAlerts  | where TimeGenerated > ago(2d) | project TimeGenerated);
// Join anomalies with Base Data to popalate associated records for investigation - Results sorted by score in descending order
TimeSeriesAlerts
| where TimeGenerated > ago(2d)
| join (
    CommonSecurityLog
| where isnotempty(DestinationIP) and isnotempty(SourceIP)
| where TimeGenerated > ago(2d)
| extend DateHour = bin(TimeGenerated, 1h) // create a new column and round to hour
| where DateHour in ((AnomalyHours)) //filter the dataset to only selected anomaly hours
| summarize HourlyCount = count(), TimeGeneratedMax = arg_max(TimeGenerated, *), DestinationIPlist = make_set(DestinationIP, 100), DestinationPortlist = make_set(DestinationPort, 100) by DeviceVendor, SourceIP, TimeGeneratedHour= bin(TimeGenerated, 1h)
| extend AnomalyHour = TimeGeneratedHour
) on AnomalyHour, DeviceVendor
| extend PercentTotal = round((HourlyCount / Total) * 100, 3)
| where PercentTotal > percentotalthreshold
| project DeviceVendor , AnomalyHour, TimeGeneratedMax, SourceIP, DestinationIPlist, DestinationPortlist, HourlyCount, PercentTotal, Total, baseline, score, anomalies
| summarize HourlyCount=sum(HourlyCount), StartTimeUtc=min(TimeGeneratedMax), EndTimeUtc=max(TimeGeneratedMax), SourceIPlist = make_set(SourceIP, 100), SourceIPMax= arg_max(SourceIP, *), DestinationIPlist = make_set(DestinationIPlist, 100), DestinationPortlist = make_set(DestinationPortlist, 100) by DeviceVendor , AnomalyHour, Total, baseline, score, anomalies
| project DeviceVendor , AnomalyHour, EndTimeUtc, SourceIPMax ,SourceIPlist, DestinationIPlist, DestinationPortlist, HourlyCount, Total, baseline, score, anomalies