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NEW QUESTION: 1
An architect is planning an HPE Moonshot System to host a customer Hadoop MapReduce2 application. The architect originally proposed the following:
* m710cartridges
* HPE 45XGc switches
* HPE 4-QSFP+ Uplink Modules
The customer now needs each HPE Moonshot chassis to provide at least 1TB of memory and 40TB or local storage.
Cartridge nodes needs two 10GbE ports each.
What does the architect need to replace in the solution to meet the customer's new requirements?
A. m710 cartridges with m350 Cartridge, which provide more memory
B. m710 cartridges with m710p cartridges, which support higher capacity local drives
C. 45XGc switches with 180G switches, which provide the required two 10GbE ports to the cartridges
D. 4-QSFP+ Uplink Modules with 16-SFP+ Uplink Modules, which provide 10GbE ports to the cartridges
Answer: D
NEW QUESTION: 2
Review the following query:
path:c:\program\ files\ \(x86\)\microsoft
How would this query input term be interpreted?
A. c:rogram files (x86)icrosoft
B. c:\program files x86\microsoft
C. c:rogramfilesx86icrosoft
D. c:\program files (x86)\microsoft
Answer: D
NEW QUESTION: 3
アプリケーションは、データの永続化のために、2つのAZとマルチAZ RDSインスタンスに展開されたWeb /アプリケーションサーバーのAuto Scalingグループの前でELBを使用しています。
多くの場合、データベースのCPUは80％を超える使用率であり、データベースのI / O操作の90％は読み取りです。パフォーマンスを向上させるために、最近、頻繁なDBクエリ結果をキャッシュする単一ノードのMemcached ElastiCacheクラスターを追加しました。今後数週間で、全体的なワークロードは30％増加すると予想されます。
予想される追加の負荷で高可用性またはアプリケーションを維持するために、アーキテクチャを変更する必要がありますか？どうして？
A. いいえ。キャッシュノードに障害が発生した場合、自動化されたElastiCacheノードリカバリ機能により、可用性への影響が防止されます。
B. はい、RDS DBマスターインスタンスと同じAZに2つのノードを持つMemcached ElastiCacheクラスターをデプロイして、1つのキャッシュノードに障害が発生した場合の負荷を処理する必要があります。
C. いいえ、キャッシュノードに障害が発生した場合、可用性に影響を与えることなく、常に同じデータをDBから取得できます。
D. はい。キャッシュノードに障害が発生した場合、RDSインスタンスはロードを処理できないため、異なるAZに2つのMemcached ElastiCacheクラスターをデプロイする必要があります。
Answer: D
Explanation:
Explanation
ElastiCache for Memcached
The primary goal of caching is typically to offload reads from your database or other primary data source. In most apps, you have hot spots of data that are regularly queried, but only updated periodically. Think of the front page of a blog or news site, or the top 100 leaderboard in an online game. In this type of case, your app can receive dozens, hundreds, or even thousands of requests for the same data before it's updated again.
Having your caching layer handle these queries has several advantages. First, it's considerably cheaper to add an in-memory cache than to scale up to a larger database cluster. Second, an in-memory cache is also easier to scale out, because it's easier to distribute an in-memory cache horizontally than a relational database.
Last, a caching layer provides a request buffer in the event of a sudden spike in usage. If your app or game ends up on the front page of Reddit or the App Store, it's not unheard of to see a spike that is 10 to 100 times your normal application load. Even if you autoscale your application instances, a 10x request spike will likely make your database very unhappy.
Let's focus on ElastiCache for Memcached first, because it is the best fit for a caching focused solution. We'll revisit Redis later in the paper, and weigh its advantages and disadvantages.
Architecture with ElastiCache for Memcached
When you deploy an ElastiCache Memcached cluster, it sits in your application as a separate tier alongside your database. As mentioned previously, Amazon ElastiCache does not directly communicate with your database tier, or indeed have any particular knowledge of your database. A simplified deployment for a web application looks something like this:
In this architecture diagram, the Amazon EC2 application instances are in an Auto Scaling group, located behind a load balancer using Elastic Load Balancing, which distributes requests among the instances. As requests come into a given EC2 instance, that EC2 instance is responsible for communicating with ElastiCache and the database tier. For development purposes, you can begin with a single ElastiCache node to test your application, and then scale to additional cluster nodes by modifying the ElastiCache cluster. As you add additional cache nodes, the EC2 application instances are able to distribute cache keys across multiple ElastiCache nodes. The most common practice is to use client-side sharding to distribute keys across cache nodes, which we will discuss later in this paper.
When you launch an ElastiCache cluster, you can choose the Availability Zone(s) that the cluster lives in. For best performance, you should configure your cluster to use the same Availability Zones as your application servers. To launch an ElastiCache cluster in a specific Availability Zone, make sure to specify the Preferred Zone(s) option during cache cluster creation. The Availability Zones that you specify will be where ElastiCache will launch your cache nodes. We recommend that you select Spread Nodes Across Zones, which tells ElastiCache to distribute cache nodes across these zones as evenly as possible. This distribution will mitigate the impact of an Availability Zone disruption on your ElastiCache nodes. The trade-off is that some of the requests from your application to ElastiCache will go to a node in a different Availability Zone, meaning latency will be slightly higher. For more details, refer to Creating a Cache Cluster in the Amazon ElastiCache User Guide.
As mentioned at the outset, ElastiCache can be coupled with a wide variety of databases. Here is an example architecture that uses Amazon DynamoDB instead of Amazon RDS and MySQL:
This combination of DynamoDB and ElastiCache is very popular with mobile and game companies, because DynamoDB allows for higher write throughput at lower cost than traditional relational databases. In addition, DynamoDB uses a key-value access pattern similar to ElastiCache, which also simplifies the programming model. Instead of using relational SQL for the primary database but then key-value patterns for the cache, both the primary database and cache can be programmed similarly. In this architecture pattern, DynamoDB remains the source of truth for data, but application reads are offloaded to ElastiCache for a speed boost.