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NEW QUESTION: 1
Talal is a DevOps engineer and he has deployed the production infrastructure using Terraform. He is using a very large configuration file to maintain and update the actual infrastructure. As the infrastructure have grown to a very complex and large, he has started experiencing slowness when he run runs terraform plan. What are the options for him to resolve this slowness?
A. Break large configurations into several smaller configurations that can each be independently applied.
B. Use -refresh=true flag as well as the -target flag with terraform plan in order to work around this.
C. Use -refresh=false flag as well as the -target flag with terraform plan in order to work around this.
D. Run terraform refresh every time before running terraform plan.
Answer: A,C
Explanation:
Explanation
For larger infrastructures, querying every resource is too slow. Many cloud providers do not provide APIs to query multiple resources at once, and the round trip time for each resource is hundreds of milliseconds. On top of this, cloud providers almost always have API rate limiting so Terraform can only request a certain number of resources in a period of time. Larger users of Terraform make heavy use of the -refresh=false flag as well as the -target flag in order to work around this. In these scenarios, the cached state is treated as the record of truth.
Although 'Use -refresh=false flag as well as the -target flag with terraform plan in order to work around this.' is a solution, but its not always recommended. Instead of using -target as a means to operate on isolated portions of very large configurations, prefer instead to break large configurations into several smaller configurations that can each be independently applied. Data sources can be used to access information about resources created in other configurations, allowing a complex system architecture to be broken down into more manageable parts that can be updated independently.
Option 'Run terraform refresh every time before running terraform plan.' and 'Use -refresh=true flag as well as the -target flag with terraform plan in order to work around this.' is not correct because in both the cases terraform will query every resources of the infrastructure.

NEW QUESTION: 2
The United Nations Conference on Environment and Development is better known as:
A. Rio Earth Summit.
B. Rio Global Gathering.
C. Rio Environmental Conference.
D. Rio Climate Carnival.
Answer: A

NEW QUESTION: 3
A company uses Azure to host virtual machines (VMs) and web apps.
Storage Analytics data for the web apps must be kept as long as possible. The solution must not result in additional costs.
You need to configure a storage policy for the analytics data.
How should you configure the policy? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: retention
There are two ways to delete Storage Analytics data: by manually making deletion requests or by setting a data retention policy. Manual requests to delete Storage Analytics data are billable, but delete requests resulting from a retention policy are not billable.
To avoid unnecessary charges, set a retention policy for logging and metrics.
Note: By default, Storage Analytics will not delete any logging or metrics data. Blobs and table entities will continue to be written until the shared 20TB limit is reached. Once the 20TB limit is reached, Storage Analytics will stop writing new data and will not resume until free space is available.
Box 2: 365
You can configure two data retention policies: one for logging and one for metrics. When enabled for both, Storage Analytics will delete logs and table entries older than the specified number of days. The maximum retention period is 365 days (1 year).
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/Setting-a-Storage-Analytics-Data-Retention-Policy

NEW QUESTION: 4
計算ビューで一時的な条件をサポートする結合のタイプはどれですか？
A. テキスト結合
B. 内部結合
C. 参照結合
D. 左外部結合
Answer: B