InsightsMetrics テーブルのクエリ

IoT Edge: デバイスがオフラインであるか、予想される速度でアップストリームにメッセージを送信しない

過去 2 日間に表示されたデバイスIoT Edge、30 分間に予想レートで D2C メッセージをIoT Hubに送信していないデバイスを特定します。

// To create an alert for this query, click '+ New alert rule'
let targetReceiver = "upstream";
InsightsMetrics
| where Origin == "iot.azm.ms" and Namespace == "metricsmodule"
| where Name == "edgehub_messages_sent_total"
| extend dimensions=parse_json(Tags)
| extend device = tostring(dimensions.edge_device)
| extend target = trim_start(@"[^/]+/", extractjson("$.to", 
tostring(dimensions), typeof(string)))
| where target contains targetReceiver
| extend source = strcat(device, "::", trim_start(@"[^/]+/", 
tostring(dimensions.from)))
| extend messages = toint(Val)
| extend timeUtc = TimeGenerated
| extend sourceTarget = strcat(source, "::", target)
| project timeUtc, source, sourceTarget, messages, device, _ResourceId
| order by device, sourceTarget, timeUtc
| serialize
| extend nextCount = next(messages, 1)
| extend nextSourceTarget= next(sourceTarget, 1)
| extend diff = iff((messages - nextCount) >= 0, messages - nextCount, 0)
| where sourceTarget == nextSourceTarget and diff >= 0
| project TimeGenerated = timeUtc, source, sourceTarget, messages, diff, 
device, _ResourceId
| make-series sum(diff) default=0 on TimeGenerated from ago(2d) to now() 
step 30m by device, _ResourceId
| mv-expand sum_diff, TimeGenerated
| project TimeGenerated=todatetime(TimeGenerated), device, 
AggregatedValue=toint(sum_diff), _ResourceId

IoT Edge: しきい値を超える Edge Hub キュー サイズ

評価期間中にデバイスの Edge Hub キュー サイズ (合計) が構成されたしきい値を超えた回数。

// To create an alert for this query, click '+ New alert' 
let qlenThreshold = 100;
InsightsMetrics
| where Origin == "iot.azm.ms" and Namespace == "metricsmodule"
| where Name == "edgehub_queue_length"
| extend dimensions=parse_json(Tags)
| extend device = tostring(dimensions.edge_device)
| extend ep = tostring(dimensions.endpoint)
| extend qlen = toint(Val)
| project device, qlen, ep, TimeGenerated, _ResourceId
| summarize sum(qlen) by TimeGenerated, device, _ResourceId
| where sum_qlen >= qlenThreshold
| project-away sum_qlen

ノード ディスクの最大数

ノード ディスクの最大使用量は、30 分間隔で平均しました。

// To create an alert for this query, click '+ New alert rule'
//InsightMetrics contains all the custom metrics for Container Insights solution
InsightsMetrics // Replace Name with your custom metric
| where Name == "used_percent" and Namespace == "container.azm.ms/disk" 
| summarize val= max(Val) by bin(TimeGenerated, 15m), _ResourceId
| render timechart

ノードあたりの 1 秒あたりの Prometheus ディスク読み取り

既定の kubernetes 名前空間から Prometheus ディスク読み取りメトリックをタイムグラフとして表示します。

// To create an alert for this query, click '+ New alert rule'
// Update TimeGenerated field for custom time range
InsightsMetrics
| where Namespace == 'container.azm.ms/diskio'
| where TimeGenerated > ago(1h)
| where Name == 'reads'
| extend Tags = todynamic(Tags)
| extend HostName = tostring(Tags.hostName), Device = Tags.name
| extend NodeDisk = strcat(Device, "/", HostName)
| order by NodeDisk asc, TimeGenerated asc
| serialize //calculating the PreVal, PrevTimeGenerated to render the chart.
| extend PrevVal = iif(prev(NodeDisk) != NodeDisk, 0.0, prev(Val)), PrevTimeGenerated = iif(prev(NodeDisk) != NodeDisk, datetime(null), prev(TimeGenerated))
| where isnotnull(PrevTimeGenerated) and PrevTimeGenerated != TimeGenerated
//Calculating the rate for disk using PreVal
| extend Rate = iif(PrevVal > Val, Val / (datetime_diff('Second', TimeGenerated, PrevTimeGenerated) * 1), iif(PrevVal == Val, 0.0, (Val - PrevVal) / (datetime_diff('Second', TimeGenerated, PrevTimeGenerated) * 1)))
| where isnotnull(Rate)
| project TimeGenerated, NodeDisk, Rate, _ResourceId
| render timechart

InsightsMetrics で検索

InsightsMetrics で検索し、InsightsMetrics テーブルで特定の値を検索します。/nNote では、結果を生成するために SeachValue> パラメーターを<更新する必要があります

// This query requires a parameter to run. Enter value in SearchValue to find in table.
let SearchValue =  "<SearchValue>";//Please update term you would like to find in the table.
InsightsMetrics
| where * contains tostring(SearchValue)
| take 1000

収集されるデータは何ですか?

収集されたパフォーマンス カウンターとオブジェクトの種類を一覧表示します。

InsightsMetrics
| where Origin == "vm.azm.ms"
| summarize by Namespace, Name

仮想マシンで使用可能なメモリ

仮想マシンで使用可能なメモリ。

InsightsMetrics
| where TimeGenerated > ago(1h)
| where Origin == "vm.azm.ms"
| where Namespace == "Memory"
| where Name == "AvailableMB"
| summarize avg(Val) by bin(TimeGenerated, 5m), Computer
| render timechart 

過去 1 時間の CPU 使用率パターンを計算し、パーセンタイルでグラフ化します。

InsightsMetrics
| where TimeGenerated > ago(1h)
| where Origin == "vm.azm.ms"
| where Namespace == "Processor"
| where Name == "UtilizationPercentage"
| summarize avg(Val) by bin(TimeGenerated, 5m), Computer //split up by computer
| render timechart

仮想マシンの空きディスク領域

インスタンスごとの空きディスク領域の最新のレポートを表示します。

InsightsMetrics
| where TimeGenerated > ago(1h)
| where Origin == "vm.azm.ms"
| where Namespace == "LogicalDisk"
| where Name == "FreeSpaceMB"
| extend t=parse_json(Tags)
| summarize arg_max(TimeGenerated, *) by tostring(t["vm.azm.ms/mountId"]), Computer // arg_max over TimeGenerated returns the latest record
| project Computer, TimeGenerated, t["vm.azm.ms/mountId"], Val

ハートビートを使用して VM の可用性を追跡する

過去 1 時間の VM の報告された可用性を表示します。

InsightsMetrics
| where TimeGenerated > ago(1h)
| where Origin == "vm.azm.ms"
| where Namespace == "Computer"
| where Name == "Heartbeat"
| summarize heartbeat_count = count() by bin(TimeGenerated, 5m), Computer
| extend alive=iff(heartbeat_count > 2, 1.0, 0.0) //computer considered "down" if it has 2 or fewer heartbeats in 5 min interval
| project TimeGenerated, alive, Computer
| render timechart with (ymin = 0, ymax = 1) 

CPU 使用率別の上位 10 Virtual Machines

CPU 使用率別の上位 10 Virtual Machines。

InsightsMetrics
| where TimeGenerated > ago(1h)
| where Origin == "vm.azm.ms"
| where Namespace == "Processor" and Name == "UtilizationPercentage"
| summarize P90 = percentile(Val, 90) by Computer
| top 10 by P90

下 10 空きディスク領域 %

下位 10 コンピューター別の空きディスク領域 %。

InsightsMetrics
| where TimeGenerated > ago(24h)
| where Origin == "vm.azm.ms"
| where Namespace == "LogicalDisk" and Name == "FreeSpacePercentage"
| summarize P90 = percentile(Val, 90) by Computer
| top 10 by P90 asc