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| Section | Weight | Objectives |
|---|---|---|
| Monitoring & Troubleshooting Cloud Native Applications | 10% | - Troubleshooting containerized and serverless workloads - Application performance monitoring and tracing - Centralized logging and metrics collection |
| Leveraging Serverless Technologies for Cloud Native Development | 33% | - Event-driven architecture with OCI Events, Streaming, and Queue - API-driven architectures using API Gateway - Oracle Functions development and management |
| Cloud Native Applications and Containerization | 33% | - Building containerized applications with Docker - Deployment and management with Oracle Kubernetes Engine (OKE) - Oracle Container Registry (OCIR) usage |
| Cloud Native Fundamentals | 11% | - Cloud-native principles and microservices architecture - DevOps concepts and CI/CD workflows - OCI developer services and tools overview |
| Testing and Securing Cloud Native Applications | 13% | - Testing strategies and secure deployment configurations - Application security best practices - Secrets management with OCI Vault |
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質問 # 49
Which statement is NOT valid regarding autoscaling configurations in Oracle Cloud Infrastructure Container Engine for Kubernetes (OKE)?
正解：B
解説：
Oracle explicitly lists Kubernetes Cluster Autoscaler among the deploymentsnot supported when using OKE virtual nodes. Virtual nodes provide a serverless data-plane model in which Oracle manages the underlying compute capacity, so customers do not resize a conventional virtual-node pool through Kubernetes Cluster Autoscaler. Cluster Autoscaler remains applicable to managed node pools, where worker-node capacity can be increased or decreased according to scheduling demand. Oracle also identifies Vertical Pod Autoscaler as unsupported on virtual nodes, while Metrics Server is supported through a deployment method adapted for virtual nodes. Horizontal Pod Autoscaler operates at the pod/deployment level and can adjust replica counts without requiring customers to resize virtual-node infrastructure. Therefore, B is the NOT valid statement because it incorrectly claims Cluster Autoscaler can resize both managed and virtual node pools.
質問 # 50
Your organization is developing serverless applications with Oracle Functions. Many functions will need to store state data in a database, which will require using appropriate credentials. However, your corporate security standards mandate encryption of secret information, such as database passwords. How would you address this security requirement?
正解：C
解説：
The best way to store and use secret information, such as database passwords, in Oracle Functions is to use the OCI Vault service. The OCI Vault service provides encryption and decryption capabilities for sensitive data. You can use the OCI Vault service to encrypt the password and store it as an application-level configuration variable. Then, you can use the generated key to decrypt the password in your function code when you need to access the database. Verified References: Oracle Functions: Using Key Management To Encrypt And Decrypt Configuration Variables
質問 # 51
Your development team wants to configure API Gateway request validation to shield an upstream backend microservice from ill-formed API calls. You want to test the validation rules in your staging environment first without blocking any non-compliant client requests, and you want to ensure the gateway checks that a mandatory HTTP header is present. Which TWO configurations should you apply to your API Gateway deployment specification to meet this requirement?
正解：A、B
解説：
OCI API Gateway request validation supportsEnforcing, Permissive, and Disabledvalidation modes. In Permissive mode, requests are validated and failures are recorded, but even non-compliant requests continue to the backend, making it appropriate for testing the impact of validation before enforcing it. Oracle also supports explicit header validation rules in which a header can be marked required: true. Enforcing mode instead blocks requests that fail validation and returns a 4xx response. No dynamic group is required for API Gateway to validate standard HTTP headers, and request.auth relates to authentication context rather than header-presence validation. Therefore, A and C directly satisfy both stated requirements.
質問 # 52
Which limit represents the maximum write throughput supported per partition of an Oracle Cloud Infrastructure stream when designing high-volume data producer workloads?
正解：C
解説：
Oracle ' s current OCI Streaming limits specify that each stream partition supports a total data write rate of 1 MB per second. Partition count is therefore a fundamental capacity-planning parameter for producer workloads. If an application is expected to produce more than 1 MB per second, the stream must contain enough partitions to distribute the required ingress throughput appropriately. Oracle ' s partitioning guidance likewise states that expected throughput should be calculated before stream creation because each partition is limited to the 1 MB-per-second write rate. The 2 MB figure is not the documented write limit, while 4 MB and 8 MB exceed the per-partition ingress capacity. Therefore, the maximum write throughput represented by the available choices is 1 MB per second.
質問 # 53
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?
正解：B
解説：
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.
質問 # 54
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