1Z0-1127 Practice Test 32 — 15 Questions

Question 1

An administrator created the above IAM policies. A member of the GenerativeAIAdmins group reports they cannot invoke the model endpoint. Which permission is missing?

Accepted Answer

Permission to use or manage generative-ai-endpoint. The error occurs because the IAM policy grants permissions for 'generative-ai-model' but not for 'generative-ai-endpoint'. Invoking a model endpoint requires the 'use' or 'manage' permission on the 'generative-ai-endpoint' resource type, as the endpoint is the runtime interface that handles inference requests. Without this permission, the API call to the endpoint is denied, even if the user has access to the underlying model.

Answer

Permission to access the compartment

Answer

Permission to manage generative-ai-model

Answer

Permission to read the model's training data

Question 2

An organization is deploying a large language model on OCI using a dedicated AI cluster. They need to minimize inference latency. Which configuration step is most critical?

Accepted Answer

Configure the cluster to use high-bandwidth RDMA networking. RDMA (Remote Direct Memory Access) bypasses the CPU and kernel to transfer data directly between GPU memories, drastically reducing latency and CPU overhead. In a dedicated AI cluster on OCI, high-bandwidth RDMA networking (e.g., using RoCE v2 or InfiniBand) is the most critical step to minimize inference latency because model parallelism and tensor parallelism across nodes depend on fast, low-latency interconnects. Without RDMA, even with optimized model parallelism, the network becomes the bottleneck, increasing per-token latency.

Answer

Set up a load balancer across multiple regions

Answer

Use a single VM shape to reduce network hops

Answer

Disable model parallelism to simplify setup

Question 3

An enterprise is deploying a generative AI model that must comply with data residency regulations. Which two configurations should they implement? (Select TWO.)

Accepted Answer

Set up OCI IAM policies to prevent data egress from the region for the model's resources. Option A is correct because OCI IAM policies can explicitly deny data egress from a specific region, ensuring that the generative AI model's resources (such as training data, model artifacts, and inference endpoints) remain within the region that satisfies data residency regulations. This is achieved by writing policy statements that restrict the movement of data across regional boundaries, which is a direct control for compliance.

Answer

Enable OCI Logging for all API calls

Answer

Use OCI Object Storage with cross-region replication for redundancy

Answer

Store encryption keys in an OCI Vault in a different region

Question 4

A company notices that some inference requests to their deployed model on OCI Generative AI take longer than acceptable. They want to reduce per-request latency. What should they do?

Accepted Answer

Reduce the maximum number of tokens generated. Reducing the maximum number of tokens generated directly decreases the amount of computation required per inference request because the model stops generating output earlier. Since latency is proportional to the number of output tokens produced, this is the most effective single change to reduce per-request response time in OCI Generative AI deployments.

Answer

Enable request batching

Answer

Use a larger model to improve accuracy

Answer

Increase the number of replicas in the deployment

Question 5

A data scientist wants to deploy a fine-tuned LLM on OCI for inference with low latency. Which OCI service should they use?

Accepted Answer

OCI Generative AI Service (Dedicated AI Cluster). B is correct because OCI Generative AI Service with a Dedicated AI Cluster provides a managed, high-throughput, low-latency inference endpoint for fine-tuned LLMs. It leverages GPU-accelerated infrastructure and optimized serving stacks (e.g., vLLM, TensorRT-LLM) to minimize response times, making it ideal for production inference workloads.

Answer

OCI Data Science Notebook Session

Answer

OCI Data Flow

Answer

OCI Functions

Question 6

A developer receives the above error when trying to send a request to a model endpoint. What is the most likely reason?

Accepted Answer

The endpoint was deleted by an administrator. The error message indicates that the model endpoint is not found. In OCI Generative AI, when an administrator deletes an endpoint, subsequent requests to that endpoint's URL return a 404 Not Found error. This is the most likely reason because the endpoint resource no longer exists in the tenancy, and the request cannot be routed to any model.

Answer

The network connection to OCI is down

Answer

The API key is invalid

Answer

The model is still being deployed

Question 7

What is the primary benefit of using a Dedicated AI Cluster over On-Demand serving for deploying generative AI models on OCI?

Accepted Answer

Higher throughput and lower latency due to reserved capacity. A Dedicated AI Cluster provides reserved compute capacity on OCI, ensuring consistent high throughput and low latency for generative AI inference workloads. Unlike On-Demand serving, which shares resources and can suffer from contention or cold starts, a Dedicated AI Cluster guarantees that GPU resources are always available for your model, eliminating variability in response times.

Answer

No need to manage model versions

Answer

Automatic scaling to zero when not in use

Answer

Lower cost for variable workloads

Question 8

A company is deploying a fine-tuned Cohere model on OCI Generative AI service for real-time inference. They need to ensure low latency even during demand spikes. Which configuration should they prioritize?

Accepted Answer

Use a dedicated AI cluster for the endpoint.. A dedicated AI cluster provides isolated compute resources (GPUs) that are not shared with other tenants or workloads, ensuring consistent low latency even under demand spikes. This is critical for real-time inference because shared endpoints can experience resource contention and throttling during high traffic, while a dedicated cluster guarantees predictable performance.

Answer

Enable model caching on the endpoint.

Answer

Use streaming responses.

Answer

Increase the max tokens parameter.

Question 9

A financial institution needs to deploy a fine-tuned model on OCI with strict data residency requirements. They must ensure that data used for inference never leaves a specific OCI region. The model is stored in Object Storage in the same region. What additional configuration is needed?

Accepted Answer

Configure the dedicated AI cluster to use a private endpoint and restrict access to the region. Option A is correct because configuring the dedicated AI cluster to use a private endpoint ensures that inference traffic stays within the OCI region and never traverses the public internet. This satisfies the strict data residency requirement by keeping all data and model inference within the designated region, while the model stored in Object Storage in the same region is accessed via the private endpoint without leaving the region.

Answer

Use OCI Data Transfer service to move data

Answer

Set up a VPN connection to on-premises

Answer

Enable cross-region replication on the bucket

Question 10

Refer to the exhibit. A user receives this error when using the OCI CLI to chat with a model. What is the most likely cause?

Accepted Answer

The user does not have the required IAM policy to invoke the model.. The error occurs because the user lacks the necessary IAM policy to invoke the model. In OCI, even if the model is deployed and the CLI is correctly configured, the IAM policy must grant the user or group the 'inference' permission on the specific model or model family. Without this policy, the OCI CLI returns an authorization error when attempting to chat with the model.

Answer

The model is not deployed.

Answer

The model ID is incorrect.

Answer

The OCI CLI is not configured with the correct region.

Question 11

A user wants to invoke an OCI Generative AI endpoint from a cloud function. What is the required authentication method?

Accepted Answer

API signing key. OCI Generative AI endpoints require API signing keys for authentication because they are REST APIs that use the Signature Version 1 algorithm (based on HMAC-SHA256) to sign requests. Cloud Functions must include a signed HTTP header using a user's or service principal's OCI API signing key pair (private key for signing, public key uploaded to OCI) to prove identity and authorization. This is the standard method for programmatic access to OCI services, including Generative AI, and is enforced by the OCI Identity and Access Management (IAM) policy layer.

Answer

User name and password

Answer

Session token

Answer

OCI certificate

Question 12

An enterprise with strict data residency requirements wants to use OCI Generative AI. They must ensure that no training data or inference data leaves a specific OCI region. Which configuration option should they choose?

Accepted Answer

Use a dedicated AI cluster in the desired region and disable cross-region access.. A dedicated AI cluster in the desired region, with cross-region access disabled, ensures that all compute, training data, and inference data remain physically within that OCI region. This satisfies strict data residency requirements because the cluster is isolated from other regions at the network and infrastructure level, preventing any data egress.

Answer

Configure a service gateway with a private endpoint.

Answer

Implement a policy restricting data transfer via OCI Identity and Access Management.

Answer

Use OCI Data Transfer Service to keep data within the region.

Question 13

Refer to the exhibit. A team created this dedicated AI cluster. However, when they try to create a model deployment, the deployment fails with an error indicating insufficient public IPs. What change to the cluster configuration should they make?

Accepted Answer

Change assignPublicIp to true.. The error indicates insufficient public IPs because the cluster's subnet does not have enough available public IP addresses. Setting `assignPublicIp` to `true` in the cluster configuration allows the cluster to automatically allocate public IPs from the subnet's pool, resolving the shortage. This is required for model deployments that need public endpoints.

Answer

Increase the nodeCount to 8.

Answer

Attach a different subnet that has more available public IPs.

Answer

Change the AI cluster shape to VM.GPU.A10.2.

Question 14

A data scientist fine-tunes a model using OCI Data Science and wants to deploy it as a managed endpoint in OCI Generative AI. What must they do first?

Accepted Answer

Upload model artifacts to Object Storage and register in Model Catalog. To deploy a fine-tuned model as a managed endpoint in OCI Generative AI, the model artifacts must first be uploaded to Object Storage and registered in the Model Catalog. This is a prerequisite because OCI Generative AI endpoints pull model artifacts from the Model Catalog, which references the storage location. Without registration, the service cannot locate or serve the model.

Answer

Write a custom container

Answer

Create a dedicated AI cluster

Answer

Use OCI CLI to create an endpoint

Question 15

An AI team is fine-tuning a large language model using OCI Data Science and plans to deploy the fine-tuned model using the Generative AI service's custom model deployment. What is the required format for the model artifacts?

Accepted Answer

A .zip archive containing model weights and configuration files. The OCI Generative AI service requires custom model artifacts to be packaged as a .zip archive containing the model weights, configuration files (e.g., config.json, tokenizer files), and any necessary inference code. This format ensures the service can extract and load the model correctly into its managed inference infrastructure, aligning with the standard Hugging Face model repository structure.

Answer

A Git repository URL

Answer

A single .pth file

Answer

A Docker image with the model and inference code

1Z0-1127 Practice Test 32 — 15 Questions

Exhibit

1Z0-1127 Practice Test 32 — 15 Questions

Exhibit