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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Cloud Native Fundamentals | 11% | - Cloud Native Principles
|
| Topic 2: Testing and Securing Cloud Native Applications | 13% | - Cloud Native Security
|
| Topic 3: Monitoring & Troubleshooting Cloud Native Applications | 10% | - Monitoring, Logging, and Tracing
|
| Topic 4: Cloud Native Applications and Containerization | 33% | - OCI Registry
|
| Topic 5: Leveraging Serverless Technologies for Cloud Native Development | 33% | - OCI Queue
|
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NEW QUESTION # 123
Your organization has mandated that all deployed container images used for microservices must be signed by a specified master encryption key (MEK). You have appropriately signed the container images as part of your build process, but must now ensure that they are automatically verified when they are deployed to Oracle Cloud Infrastructure (OCI) Container Engine for Kubemetes (OKE) clusters. Which option should be used to mandate image verification when deploying to OKE clusters, assuming that MEK is already stored in an available OCI Vault? (Choose the best answer.)
Answer: D
Explanation:
To mandate image verification when deploying container images to Oracle Cloud Infrastructure (OCI) Container Engine for Kubernetes (OKE) clusters, you should enable image verification policies separately for each OKE cluster. This is enforced at the cluster level. Enabling image verification policies at the cluster level ensures that all container images deployed to the OKE cluster are automatically verified against the specified master encryption key (MEK). This helps maintain the security and integrity of the deployed microservices by ensuring that only signed and trusted container images are used. Enabling image verification policies at the cluster level allows for consistent and centralized enforcement of the verification process across all nodes and node pools within the cluster. It provides a standardized approach to image verification for the entire cluster, simplifying management and ensuring compliance with the organization ' s mandate. Enabling image verification policies separately for each node pool or at the pod level would introduce complexity and potential inconsistencies in the verification process. Therefore, enforcing image verification at the cluster level is the recommended approach.
NEW QUESTION # 124
Which two " Action Type " options are NOT available in an Oracle Cloud Infrastructure (OCI) Events rule definition? (Choose two.)
Answer: B,D
Explanation:
The two " Action Type " options that are NOT available in an Oracle Cloud Infrastructure (OCI) Events rule definition are: Email (Correct) Slack (Correct) The available " Action Type " options in OCI Events rule definition include Functions, Notifications, and Streaming. However, email and Slack are not directly supported as action types in OCI Events. Instead, you can use Notifications to send notifications to various notification channels, including email and Slack, through the OCI Notifications service.
NEW QUESTION # 125
Which technique is used for testing the entire user flow as well as the moving parts of a cloud native app, ensuring that there are no high-level discrepancies?
Answer: C
Explanation:
End-to-end testing is a technique that involves checking the entire user flow as well as the moving parts of a cloud native app, ensuring that there are no high-level discrepancies3. End-to-end testing simulates real user scenarios and validates the functionality, performance, reliability, and security of the app from start to finish3. End-to-end testing has several benefits, such as3:
* Comprehensive testing: You can test your app as a whole and verify that all the components work together as expected.
* User-centric testing: You can test your app from the user's perspective and ensure that it meets the user' s needs and expectations.
* Quality assurance: You can test your app in a realistic environment and identify any issues or defects before releasing it to the users.
NEW QUESTION # 126
(CHK_4 > 2) Which TWO statements are NOT valid regarding the Oracle Cloud Infrastructure (OCI) Streaming service? (Choose two.)
Answer: C,D
Explanation:
The two statements that are NOT valid regarding the Oracle Cloud Infrastructure (OCI) Streaming service are: A stream can be configured with either a public or a private endpoint with support for customer managed encryption keys. This statement is not valid because the OCI Streaming service currently supports only private endpoints. Customer managed encryption keys are not currently supported for OCI Streaming. OCI Streaming can support up to 2,000 requests per second to each partition. This statement is not valid because the throughput of a stream is not defined by the partition in terms of requests per second. The throughput of a stream is defined in terms of data input and output rates. Each partition provides 1 MB/sec data input and 2 MB/sec data output, but it does not correspond to a specific number of requests per second. The other statements are valid: OCI Streaming stores all data for 24 hours by default, but that can be extended up to 7 days. Although OCI Streaming automatically encrypts all data while in transit, it is the developer ' s responsibility to encrypt data at rest, if needed.
NEW QUESTION # 127
Your development team has deployed a fleet of web application servers across three fault domains in a specific compartment in OCI. To simplify operational dashboards, you must construct a single Monitoring Query Language (MQL) expression that calculates the average CPU utilization for each individual fault domain, rather than plotting each server individually. The expression must output exactly three lines, one for each fault domain, on the resulting Metrics Explorer chart.
Which MQL expression correctly fulfills these requirements?
Answer: A
Explanation:
Oracle Monitoring documents groupBy(x) specifically for aggregating metric streams according to a shared dimension. Oracle ' s own fault-domain example uses the exact expression CpuUtilization[1m].groupBy (faultDomain).mean(). The resulting chart contains one aggregated metric stream for each fault domain, which means a compartment containing three fault domains produces three lines rather than one line per Compute instance. grouping() combines all selected metric streams into a single aggregate instead of retaining separate fault-domain groups. filter(faultDomain) is not the appropriate MQL grouping operation, and split() is not the documented operator for this requirement. Because the scenario requires mean CPU utilization separately aggregated for each value of the faultDomain dimension, option B exactly matches Oracle ' s documented MQL pattern.
NEW QUESTION # 128
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