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| Section | Weight | Objectives |
|---|---|---|
| Monitoring and Troubleshooting Cloud Native Applications | 10% | - OCI Logging
|
| Testing and Securing Cloud Native Applications | 13% | - Cloud Native Security
|
| Cloud Native Fundamentals | 11% | - Cloud Native Principles
|
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - OCI Queue
|
| Cloud Native Applications and Containerization | 33% | - Container Orchestration
|
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NEW QUESTION # 161
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: B
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 # 162
You are deploying a containerized database application on a host using the standard Docker engine. To prevent data loss when the container instance is destroyed or updated, you must configure a storage mechanism that isolates application data from the volatile container layer and guarantees persistence. Which TWO statements or approaches correctly describe Docker storage components that satisfy this requirement?
Answer: B,C
Explanation:
Persistent container data must be stored outside the container ' s ephemeral writable layer. Docker volumes provide Docker-managed storage that remains independently available from the lifecycle of an individual container. Bind mounts provide another persistence mechanism by mapping a specified host file or directory directly into the container. Oracle ' s Docker documentation demonstrates both data volumes and host-path mounts for externalizing files from containers and preserving them independently. The writable container layer is removed with the container, a tmpfs mount stores data in volatile memory rather than persistent disk, and Docker image layers are immutable and cannot receive normal runtime database writes. Therefore, Docker volumes and bind mounts are the two valid persistence approaches described.
NEW QUESTION # 163
Which special column in the OCI Logging Query Language represents the raw text of the entire original log message?
Answer: A
Explanation:
Oracle ' s Logging Query Language specification defines logContent as aspecial column representing the text of the whole original message. This field is particularly valuable when the required information is not available through a known indexed JSON field or when administrators need full-text matching across the original log payload. For example, Oracle documents queries such as where logContent = ' *ERROR* ' to return log lines containing the specified text. messageBody, rawPayload, and eventSource are not documented LQL special columns representing the complete original message. Individual services can contain fields such as data.message, but those fields are part of the service-specific structured payload rather than the universal raw-message special column. Therefore, A is correct.
NEW QUESTION # 164
Your enterprise is migrating a synchronous order fulfillment system to a distributed microservices architecture on Oracle Cloud Infrastructure. The development team originally implemented a Two-Phase Commit protocol to handle transactions spanning multiple databases, but it caused severe performance bottlenecks due to extended resource locking periods. You must now design a decentralized transaction strategy that processes steps as a sequence of independent local transactions, publishes events to coordinate subsequent steps, and executes compensating actions if a step fails. Which transaction design pattern should you implement to meet these requirements?
Answer: D
Explanation:
The Saga Design Pattern is specifically intended for distributed transactions across microservices without the extended locking associated with Two-Phase Commit. Oracle explains that a Saga decomposes a business transaction into a sequence of independent local transactions. After completing its local operation, each service publishes an event or message that triggers the next participant. If a subsequent step fails, corresponding compensating transactions reverse previously completed operations and restore consistent business state. This approach shortens lock duration and supports eventual consistency across separate databases. Transactional Outbox solves reliable database-update-and-message-publishing coordination but does not by itself manage the entire distributed transaction sequence. Therefore, the required pattern is the Saga Design Pattern.
NEW QUESTION # 165
You deployed a Python application to an Oracle Container Engine for Kubernetes (OKE) cluster. However, while testing you found a bug, which you rectified and then created a new Docker image. You now need to ensure that if this new image does not work once deployed, you should be able to roll back to the previous version. Using kubect1, which strategy should you use?
Answer: D
Explanation:
A rolling update is a deployment strategy that gradually replaces the old version of an application with the new version without any downtime4. OKE supports rolling updates by using the kubectl rollout command4. A rolling update allows you to roll back to the previous version if something goes wrong with the new version4.
Therefore, using a rolling update strategy with kubectl ensures that you can roll back to the previous version of your Python application if the new image does not work once deployed.Verified References: Deploy Oracle Container Engine for Kubernetes
NEW QUESTION # 166
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