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NEW QUESTION: 1
From the code below, identify the implicit dependency:
1. resource "aws_eip" "public_ip" {
2. vpc = true
3. instance = aws_instance.web_server.id
4. }
5. resource "aws_instance" "web_server" {
6. ami = "ami-2757f631"
7. instance_type = "t2.micro"
8. depends_on = [aws_s3_bucket.company_data]
9. }
A. The EC2 instance labeled web_server
B. The AMI used for the EC2 instance
C. The EIP with an id of ami-2757f631
D. The S3 bucket labeled company_data
Answer: A
Explanation:
The EC2 instance labeled web_server is the implicit dependency as the aws_eip cannot be created until the aws_instance labeled web_server has been provisioned and the id is available.
Note that aws_s3_bucket.example is an explicit dependency.
NEW QUESTION: 2
HOTSPOT
You plan to deploy two new Microsoft Azure SQL Database instances. Once instance will support a data entry application. The other instance will support the company's business intelligence efforts. The databases will be accessed by mobile applications from public IP addresses.
You need to ensure that the database instances meet the following requirements:
The database administration team must receive alerts for any suspicious activity in the data entry
database, including potential SQL injection attacks.
Executives around the world must have access to the business intelligence application.
Sensitive data must never be transmitted. Sensitive data must not be stored in plain text in the
database.
In the table below, identify the feature that you must implement for each database.
NOTE: Make only one selection in each column. Each correct selection is work one point.
Hot Area:
Answer:
Explanation:
Explanation/Reference:
Explanation:
Data entry: Threat Detection
SQL Threat Detection provides a new layer of security, which enables customers to detect and respond to potential threats as they occur by providing security alerts on anomalous activities. Users receive an alert upon suspicious database activities, potential vulnerabilities, and SQL injection attacks, as well as anomalous database access patterns.
Business intelligence: Dynamic Data Masking
Dynamic data masking limits (DDM) sensitive data exposure by masking it to non-privileged users. It can be used to greatly simplify the design and coding of security in your application.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-threat-detection
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking
NEW QUESTION: 3
Facility fast reroute with node protection is enabled for an LSP, which of the following is FALSE?
A. When a failure occurs, the PLR pushs an additional label onto the label stack.
B. No bypass tunnel is established if the PLR cannot provide node protection.
C. Each PLR signals a bypass tunnel that avoids the next-hop downstream router.
D. The head-end router sets the local protection desired flag in the session attribute object.
Answer: B
NEW QUESTION: 4
A. Option C
B. Option A
C. Option D
D. Option B
Answer: C