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NEW QUESTION: 1
Google Kubernetes Engine(GKE)の上に製品を構築しています。 GKEクラスタが1つあります。顧客ごとに、そのクラスターでポッドが実行されており、顧客はポッド内で任意のコードを実行できます。顧客のポッド間の分離を最大化したい。あなたは何をするべきか?
A. Container Analysis APIを使用して、顧客のポッドが使用するコンテナーの脆弱性を検出します。
B. gvisorに構成されたサンドボックスタイプでGKEノードプールを作成します。パラメータruntimeClassName:gvisorを顧客のポッドの仕様に追加します。
C. GKEノードにcos_containerdイメージを使用します。 cloud.google.com/gke-os-distribution:cos_containerdという値を持つnodeSelectorを顧客のポッドの仕様に追加します。
D. バイナリ認証を使用し、顧客のポッドで使用されるコンテナーイメージのみをホワイトリストに登録します。
Answer: B
Explanation:
https://cloud.google.com/blog/products/containers-kubernetes/gke-sandbox-bring-defense-in- depth-to-your-pods
NEW QUESTION: 2
Where would a payroll flow task retrieve its parameter information when selecting "Bind to
Flow Parameter"?
A. Derives the value from one of the task parameter values
B. Derives the value from the output of the previous task
C. Derives the value from one of the flow pattern parameter values
D. Derives the value from the context of the current flow instance
Answer: C
NEW QUESTION: 3
ソリューションアーキテクトは、可用性、データの耐久性、およびスケーラビリティを改善するために、レガシーJavaアプリケーションを再設計する責任があります。現在、アプリケーションは単一の高メモリAmazon EC2インスタンスで実行されます。アップストリームクライアントからのHTTP要求を受け入れ、それらをメモリ内キューに追加し、200ステータスで応答します。別のアプリケーションスレッドがキューから項目を読み取り、処理し、結果をAmazon RDS MySQLインスタンスに永続化します。各アイテムの処理時間は平均で90秒かかります。そのほとんどは外部サービスコールの待機に費やされますが、アプリケーションは複数のアイテムを並行して処理するように記述されています。
このサービスへのトラフィックは予測不能です。高負荷の期間中、アプリケーションがバッキングを処理している間、アイテムが1時間以上内部キューに置かれることがあります。さらに、単一のアプリケーションノードに障害が発生した場合、現在のシステムには可用性とデータに関する問題があります。
このサービスにアクセスするクライアントは変更できません。タイムアウトしてリクエストを再試行する前に、送信する各HTTPリクエストに対する応答を10秒以内に受信することを期待しています。
どのアプローチがシステムの可用性と耐久性を向上させ、処理のレイテンシを削減し、コストを最小限に抑えますか?
A. Amazon RDSの代わりにAmazon DynamoDBを使用するようにアプリケーションを変更します。 DynamoDBテーブルのAuto Scalingを構成します。 CPU使用率に基づくスケーリングポリシーを使用して、Auto Scalingグループ内にアプリケーションをデプロイします。メモリマップファイルを使用してインメモリキューをインスタンスストアボリュームに戻し、そのファイルを定期的にAmazon S3に書き込みます。
B. サービスプロキシを使用してAmazon SQSキューにアイテムを配置するAmazon API Gateway REST APIを作成します。既存のアプリケーションからコア処理コードを抽出して更新し、Amazon SQSキューからアイテムをプルします。既存のアプリケーションからコア処理コードを抽出し、それを更新して、インメモリキューではなくAmazon SQSからアイテムをプルします。 Amazon SQSキュー内のメッセージの概数に基づいて動的にスケーリングするAuto Scalingグループ内のより小さいEC2インスタンスに新しい処理アプリケーションをデプロイします。
C. インメモリキューの代わりにRedisタスクキューを使用するようにアプリケーションを更新します。アプリケーションのDockerコンテナーイメージを構築します。アプリケーションコンテナーとRedisをホストする別のコンテナーを含むAmazon ECSタスク定義を作成します。 AWS Fargateを使用して新しいタスク定義をECSサービスとしてデプロイし、Auto Scalingを有効にします。
D. Lambdaプロキシ統合を使用してリクエストをAWS Lambda関数に渡すAmazon API Gateway REST APIを作成します。コア処理コードをLambda関数に移行し、プロキシイベントを内部アプリケーションデータモデルに変換して処理モジュールを呼び出すハンドラーメソッドを提供するラッパークラスを記述します。
Answer: A
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