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NEW QUESTION: 1
Microsoft SQL Server 2016データベースを管理します。
ユーザーは、データベースにアクセスするアプリケーションにエラーが表示されることを報告しますが、そのエラーは意味のある情報を提供しません。
エラーに関連するSQL ServerログまたはWindowsイベントログにエントリが見つかりません。
エラーメッセージを取得して、問題の根本的な原因を特定する必要があります。
あなたは何をするべきか？
A. sp_whoを実行してください。
B. sqlserver.error_reportedイベントを使用してExtended Eventsセッションを作成します。
C. sp_recompileを使用して、すべてのストアドプロシージャに再コンパイルのフラグを付けます。
D. すべてのErrorLogイベントとEventLogイベントをキャプチャするためのSQLプロファイラセッションを作成します。
Answer: B
Explanation:
Explanation
Trapping SQL Server Errors with Extended Events
One very useful usage of Extended Events is the ability to trap SQL Server error without the need to have a server trace running (which, btw, is deprecated), with the additional feature of being able to query the data as soon as it comes in. This means that we a solution to monitor and trap errors as soon as they happen can be easily created, in order to help developers to fix problems as soon as they are detected. This is really, really, really helpful especially in very big applications, where the code base is quite old and there is no-one really knowing everything of the solution.
To start a Extended Events sessions in order to trap SQL Server errors with severity greater than 10, just run the following script:
CREATE EVENT SESSION [error_trap] ON SERVER
ADD EVENT sqlserver.error_reported
Etc.
References:
http://sqlblog.com/blogs/davide_mauri/archive/2013/03/17/trapping-sql-server-errors-with-extended-events.aspx

NEW QUESTION: 2
AWSに膨大な量のネットワークインフラストラクチャを設定したので、これらすべてを監視することを検討する必要があります。あなたはCloudWatchがあなたのニーズに最も合うと決定します、しかしあなたは価格構造とCloudWatchの限界について確信がありません。 CloudWatchの制限に関連して真実である次の文のうちどれ？
A. 1か月に無料でCloudWatchメトリックス10個、アラーム10個、APIリクエスト1,000,000個、Amazon SNS Eメール通知1,000個を受け取ります。
B. 1か月あたり100のCloudWatchメトリックス、100のアラーム、1,000,000のAPIリクエスト、1,000のAmazon SNS Eメール通知を無料で入手できます。
C. 1か月あたり100のCloudWatchメトリックス、100のアラーム、10,000,000のAPIリクエスト、および10,000のAmazon SNS Eメール通知を無料で入手できます。
D. 1カ月あたり1顧客あたり10個のCloudWatchメトリックス、10個のアラーム、1,000個のAPIリクエスト、および100個のAmazon SNS Eメール通知を無料で入手できます。
Answer: A
Explanation:
Explanation
Amazon CloudWatch monitors your Amazon Web Services (AWS) resources and the applications you run on AWS in real-time. You can use CloudWatch to collect and track metrics, which are the variables you want to measure for your resources and applications.
CloudWatch has the following limits:
You get 10 CloudWatch metrics, 10 alarms, 1,000,000 API requests, and 1,000 Amazon SNS email notifications per customer per month for free.
You can assign up to 10 dimensions per metric.
You can create up to 5000 alarms per AWS account. Metric data is kept for 2 weeks.
The size of a PutMetricData request is limited to 8KB for HTTP GET requests and 40KB for HTTP POST requests.
You can include a maximum of 20 MetricDatum items in one PutMetricData request. A MetricDatum can contain a single value or a StatisticSet representing many values.
http://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/cloudwatch_limits.html

NEW QUESTION: 3
展示を参照してください。

IPsecピアはIKEv2を使用してルートを交換していますが、ルートはRIBにインストールされていません。どの構成エラーが失敗の原因ですか？
A. IKEv2許可ポリシーは、IKEv2プロファイルで参照されていません。
B. IKEv2ルーティングには、事前共有キーではなく証明書認証が必要です。
C. match identityコマンドは、ルートのアクセスリストを参照する必要があります。
D. 無効なアドミニストレーティブディスタンス値が設定されました。
Answer: D

NEW QUESTION: 4
What are the two types of analytics processors in Oracle Internet of Things (IoT) Cloud Service?
A. Batch Analytics Processors
B. streaming Analytics Processors
C. Static Analytics Processors
D. Natural Analytics Processors
Answer: A,B
Explanation:
https://docs.oracle.com/en/cloud/paas/iot-cloud/iotgs/understanding-analytics-processors.html he type of analytics processor to use depends on the nature of your data:
* Streaming Analytics Processors
Use streaming analytics processors to analyze high volumes of rapidly changing data streamed from your sensors and devices. Streaming analytics processors are continuously running from the moment you deploy them, waiting for your devices to stream data.
See Creating Streaming Analytics Processors.
* Batch Analytics Processors
Use batch analytics processors to analyze large volumes of batch data. Typically, batch analytics processors process data stored in the Oracle NoSQL or other data sources. Unlike streaming analytics processors they are not continuously running, they only run when you call them using the REST API they expose.

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