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Pass Guaranteed Quiz Efficient IBM - C1000-173 - IBM Cloud Pak for Data v4.7 Arc
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IBM Cloud Pak for Data v4.7 Architect Sample Questions (Q80-Q85):NEW QUESTION # 80
Which two storage requirements are essential to achieve High Availability?
- A. Data redundancy
- B. Scalable storage solutions
- C. Regular data purging
- D. Frequent system downtime for maintenance
Answer: A,B
NEW QUESTION # 81
Which components of IBM Cloud Pak for Data are essential for implementing an end-to-end data science workflow?
- A. Data Refinery and Watson Studio
- B. Decision Optimization and Streams
- C. Watson Studio and Watson Machine Learning
- D. Watson Knowledge Catalog and DataStage
Answer: C
NEW QUESTION # 82
An enterprise architect in a financial institute is deciding on the deployment option for Cloud Pak for Data on their existing OpenShift Container Platform cluster.
They have decided to use an automated deployment option and install Cloud Pak for Data from the cloud provider's marketplace. What are the limitations they may face with this decision?
- A. Cloud Pak for Data operators cannot be co-located with the IBM Cloud Pak foundational services operators.
- B. Automatic installation cannot be done for any of the Cloud Pak for Data services.
- C. Partial installation of the Cloud Pak for Data has to be done manually for the first time installation.
- D. Cloud Pak for Data cannot be installed on an existing cluster.
Answer: C
Explanation:
According to theIBM Cloud Pak for Data 4.7 Installation Guideand official IBM documentation, when deploying Cloud Pak for Data (CP4D) via a cloud provider marketplace (such as Red Hat OpenShift OperatorHub or a cloud marketplace), the deployment process offers an automated installation method that simplifies the setup. However, there are certain limitations and manual steps that may be required during the initial installation phase.
* CP4D supports installation on an existing OpenShift Container Platform cluster, so option A is incorrect.
* Some core services and operators, including foundational services, can be installed automatically via operators, so option B is incorrect.
* Cloud Pak for Data operators and IBM foundational services operators can coexist in the same OpenShift cluster, so option C is incorrect.
* Theofficial installation documentation for version 4.7specifies that the initial installation requires manual intervention for partial installation - for example, manually setting up foundational services or configuring specific operators before automated installation of the rest of the platform can continue smoothly. This partial manual setup is especially relevant when using marketplace deployment to ensure all prerequisites and configurations are met.
Exact extract from IBM Cloud Pak for Data 4.7 Installation documentation:
"When deploying Cloud Pak for Data via the OperatorHub or cloud marketplace, the initial setup requires manual installation of foundational services operators and configuration of the cluster environment before proceeding with the automated installation of Cloud Pak for Data services. Thispartial manual step ensures proper configuration and avoids conflicts during automated deployment."
-IBM Cloud Pak for Data Installation Guide v4.7, section "Installing from OperatorHub and Marketplace" References:
IBM Cloud Pak for Data 4.7 Installation Guide (https://www.ibm.com/docs/en/cloud-paks/cp-data/4.7?
topic=deployment-installing-from-operatorhub-marketplace)
IBM Knowledge Center for Cloud Pak for Data 4.7
NEW QUESTION # 83
Why is tethering projects to the IBM Cloud Pak for Data control plane beneficial?
- A. Enhances project isolation while enabling resource access control
- B. Disallows resource monitoring and management
- C. It ensures all projects are untethered for greater flexibility
- D. It prevents any form of project organization
Answer: A
NEW QUESTION # 84
Which two of the following can be used with Watson Pipelines?
- A. Bash scripts
- B. Notebooks
- C. PowerShell
- D. Postgres
- E. Db2 Big SQL
Answer: A,B
Explanation:
Watson Pipelines in Cloud Pak for Data support orchestration of diverse workload types including notebooks (Python or similar interactive environments) and scripts such as Bash. These pipeline components allow integration of notebook cells or shell scripts as tasks. There is no built#in support for executing PowerShell tasks directly (unless wrapped in Bash-like containers), and Postgres is used as a data source-not a pipeline component type. While Db2 Big SQL can be invoked within a notebook or script, it is not itself a pipeline component. Therefore the supported types in pipelines are notebooks and Bash scripts.
NEW QUESTION # 85
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