100+ Free EX267 Practice Questions
Pass your Red Hat Certified Specialist in OpenShift AI (EX267) exam on the first try — instant access, no signup required.
Which Operator must be installed first to manage Red Hat OpenShift AI components on an OpenShift 4.17 cluster?
Key Facts: EX267 Exam
210/300
Passing Score (70%)
Red Hat
3 hours
Single Section
Red Hat
$400
Exam Fee (USD)
Red Hat
RHOAI 2.13+
Product Version
Red Hat
$130-200K
MLOps Engineer Salary
Glassdoor 2024
3 years
Cert Valid
Red Hat renewal
EX267 is Red Hat's specialist credential for OpenShift AI (RHOAI). It is a 3-hour, hands-on, performance-based exam with a 210/300 (70%) passing score and a $400 fee. The exam covers the RHOAI Operator, DataScienceCluster and DSCInitialization CRs, workbenches, data science pipelines, distributed training with Ray, and KServe/ModelMesh model serving on OpenShift 4. Credential is valid for 3 years and counts toward Red Hat Certified Architect (RHCA).
Sample EX267 Practice Questions
Try these sample questions to test your EX267 exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.
1Which Operator must be installed first to manage Red Hat OpenShift AI components on an OpenShift 4.17 cluster?
2Which custom resource initializes cluster-wide settings (such as the applications namespace and monitoring) for Red Hat OpenShift AI?
3In a DataScienceCluster CR, what value of managementState causes the operator to install and reconcile a component?
4Which namespace does the RHOAI Operator create by default for its application workloads (dashboard, controllers, etc.)?
5Where does an administrator install the Red Hat OpenShift AI Operator from in the OpenShift web console?
6An administrator wants to enable KServe single-model serving but keep ModelMesh disabled. Which two managementState values should they set in the DataScienceCluster?
7After installing the RHOAI Operator, a DataScienceCluster CR stays in a Pending state. Which condition is most likely the cause?
8Which command shows the reconciliation status of a DataScienceCluster named default-dsc?
9Which RHOAI component is responsible for the Kubeflow Pipelines control plane within a data science project?
10Which two operators are typically required as KServe dependencies when KServe is set to Managed in RHOAI Serverless mode?
About the EX267 Exam
Performance-based certification for data scientists, MLOps engineers, and platform engineers operating Red Hat OpenShift AI. EX267 validates hands-on skills in installing the RHOAI Operator, configuring DataScienceCluster and DSCInitialization custom resources, creating data science projects and workbenches, building Kubeflow data science pipelines with Elyra, running distributed training with Ray and CodeFlare, serving models via KServe single-model and ModelMesh multi-model runtimes, and configuring GPU acceleration on Red Hat OpenShift Container Platform 4.
Assessment
Single 3-hour performance-based hands-on section on a live OpenShift cluster with Red Hat OpenShift AI installed
Time Limit
3 hours
Passing Score
210/300 (70%)
Exam Fee
$400 USD (Red Hat)
EX267 Exam Content Outline
Install and Configure Red Hat OpenShift AI
Install the RHOAI Operator from OperatorHub, configure DSCInitialization (DSCI) and DataScienceCluster (DSC) CRs, manage component states (Managed, Removed, Unmanaged), upgrade RHOAI
Manage Data Science Projects and Permissions
Create data science projects (namespaces with RHOAI labels), configure user and group access, RBAC for project members and admins, project quotas
Workbenches and Notebooks
Launch workbenches via the RHOAI dashboard, Notebook custom resource, prebuilt notebook images (Standard Data Science, PyTorch, TensorFlow, CUDA), custom notebook images via ImageStream, persistent volumes for notebooks
Data Science Pipelines
DataSciencePipelinesApplication (DSPA) CR, Kubeflow Pipelines backend, Elyra visual pipeline editor, runtime configurations, S3-compatible storage for artifacts, scheduled pipeline runs
Distributed Training with Ray and CodeFlare
RayCluster and RayJob CRs, CodeFlare SDK, AppWrapper, KubeRay operator, GPU-accelerated training jobs, Ray dashboard
Model Serving with KServe and ModelMesh
KServe single-model serving (InferenceService CR), ModelMesh multi-model serving, ServingRuntime CR (OpenVINO, Triton, TGIS, vLLM, Caikit), model registry, inference endpoints, REST and gRPC
Accelerator Support and GPU Configuration
NVIDIA GPU Operator, Node Feature Discovery (NFD), AcceleratorProfile CR, taints and tolerations, nodeSelector for GPU nodes, MIG partitioning
Object Storage Integration
S3-compatible storage (OpenShift Data Foundation NooBaa, MinIO), DataConnections, secrets for S3 credentials, model artifacts and pipeline storage
Monitoring and Observability
User Workload Monitoring stack (Prometheus, Grafana), metrics for KServe and ModelMesh, ServiceMonitor, distributed-workloads metrics, model performance dashboards
How to Pass the EX267 Exam
What You Need to Know
- Passing score: 210/300 (70%)
- Assessment: Single 3-hour performance-based hands-on section on a live OpenShift cluster with Red Hat OpenShift AI installed
- Time limit: 3 hours
- Exam fee: $400 USD
Keys to Passing
- Complete 500+ practice questions
- Score 80%+ consistently before scheduling
- Focus on highest-weighted sections
- Use our AI tutor for tough concepts
EX267 Study Tips from Top Performers
Frequently Asked Questions
What is the EX267 pass rate?
Red Hat does not officially publish pass rates. Industry estimates suggest approximately 50-60% of candidates pass on the first attempt because the exam is hands-on and RHOAI is a young, fast-changing product. The passing score is 210/300 (70%). Most candidates need 100-150 hours of practice on a real OpenShift AI cluster before they reliably hit the threshold.
What RHOAI version does EX267 cover?
EX267 currently aligns to Red Hat OpenShift AI 2.13 or later running on Red Hat OpenShift Container Platform 4.17 or later. Always check the official Red Hat exam page before scheduling — RHOAI ships frequent releases and Red Hat updates the exam objectives accordingly. Practice on a current RHOAI release so the dashboard, CRDs, and operator names match what you see on exam day.
How is EX267 different from EX280?
EX280 is the OpenShift platform administration exam (oc CLI, RBAC, routes, SCCs, operators in general). EX267 assumes you already know that and tests AI-specific workloads on top: installing the RHOAI Operator, managing DataScienceCluster and DSCInitialization CRs, workbenches, data science pipelines, KServe and ModelMesh model serving, and Ray distributed training. EX280 holders still need to study the RHOAI-specific surface area for EX267.
What are the EX267 prerequisites?
Red Hat strongly recommends EX280 (OpenShift Administration) before EX267, plus completion of AI267 (Red Hat OpenShift AI) or equivalent experience. There is no hard prerequisite enforced at registration, but the exam assumes solid OpenShift fluency, container concepts, and practical familiarity with Jupyter notebooks, Kubeflow Pipelines, and Python ML frameworks like PyTorch or TensorFlow.
Does EX267 expire?
Yes — EX267 is valid for 3 years from the date you pass. You can recertify by retaking the current EX267, passing a higher-level Red Hat exam, or earning enough Red Hat credentials to maintain Red Hat Certified Architect (RHCA) status. Red Hat sends renewal notifications before expiration so you can plan ahead.
How long should I study for EX267?
Plan for 100-150 hours of hands-on study over 8-12 weeks if you already hold EX280 and have OpenShift experience. If you are new to OpenShift, double that and pass EX280 first. Build a working RHOAI lab (developer sandbox or self-hosted), drill the RHOAI dashboard, CRDs, KServe InferenceServices, and Ray clusters until commands and YAML are muscle memory.
What jobs can I get with EX267?
EX267 qualifies you for: MLOps Engineer ($130,000-180,000), AI Platform Engineer ($140,000-190,000), Machine Learning Engineer ($130,000-200,000), Data Science Platform Lead ($150,000-200,000), and AI Infrastructure Specialist ($135,000-185,000). Demand is concentrated in regulated industries (banking, telecom, healthcare, government) where RHOAI is the supported AI platform on OpenShift.