Values.InsightRetrieves the list of performance issues which are identified.
type nonrec t = {insightId : String_.t option;The unique identifier for the insight. For example, insight-12345678901234567.
*)insightType : String_.t option;The type of insight. For example, HighDBLoad, HighCPU, or DominatingSQLs.
*)context : ContextType.t option;Indicates if the insight is causal or correlated insight.
*)startTime : ISOTimestamp.t option;The start time of the insight. For example, 2018-10-30T00:00:00Z.
*)endTime : ISOTimestamp.t option;The end time of the insight. For example, 2018-10-30T00:00:00Z.
*)severity : Severity.t option;The severity of the insight. The values are: Low, Medium, or High.
*)supportingInsights : InsightList.t option;List of supporting insights that provide additional factors for the insight.
*)description : MarkdownString.t option;Description of the insight. For example: A high severity Insight found between 02:00 to 02:30, where there was an unusually high DB load 600x above baseline. Likely performance impact.
*)recommendations : RecommendationList.t option;List of recommendations for the insight. For example, Investigate the following SQLs that contributed to 100% of the total DBLoad during that time period: sql-id.
*)insightData : DataList.t option;List of data objects containing metrics and references from the time range while generating the insight.
*)baselineData : DataList.t option;Metric names and values from the timeframe used as baseline to generate the insight.
*)}val make :
?insightId:String_.t ->
?insightType:String_.t ->
?context:ContextType.t ->
?startTime:ISOTimestamp.t ->
?endTime:ISOTimestamp.t ->
?severity:Severity.t ->
?supportingInsights:InsightList.t ->
?description:MarkdownString.t ->
?recommendations:RecommendationList.t ->
?insightData:DataList.t ->
?baselineData:DataList.t ->
unit ->
t