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Cisco 300-610 Exam With Confidence Using Practice Dumps

Exam Code:
300-610
Exam Name:
Designing Cisco Data Center Infrastructure for Traditional and AI Workloads v1.2 (DCID 300-610)
Certification:
CCNP Data Center
Vendor:
Cisco
Questions:
299
Last Updated:
Sep 1, 2026
Exam Status:
Stable
Cisco 300-610

300-610: CCNP Data Center Exam 2025 Study Guide Pdf and Test Engine

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Designing Cisco Data Center Infrastructure for Traditional and AI Workloads v1.2 (DCID 300-610) Questions and Answers

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Question 1

Refer to the exhibit.

A Cisco engineer is configuring a next-generation Cisco HyperFlex HX data platform with 2 x Cisco UCS 6248UP fabric interconnects. 8 x Cisco HX-Series HX240c-M4SX servers, plus 8 x Cisco UCS B200-M4 blade servers Cisco UCS 5108 blade chassis, and Cisco UCS 2204XP fabric extenders The solution is configured with HX Release 4 5(2a) using VMware ESXi 7 0 U2 After the engineer migrates all customer VMs to the new solution platform, the engineer decides to create HX Native snapshots for all the VMs The engineer performs the operation and notices that some of the VMs are not creating snapshots. What is the most probable reason that the HX Native snapshots are not created?

Options:

A.

Virtual machines are in suspended state

B.

The servers have duplicate names

C.

The source disk is thick provisioned

D.

The node has insufficient datastore space

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Question 2

After experiencing traffic disruptions from the failure of a single router, a customer asks an engineer to design a solution that will prevent this from occurring in the future. While examining the customer’s environment, the engineer discovers that the routers are manufactured by a variety of different vendors, and they have varying amounts of CPU and memory resources. Additionally, several of the customer’s applications require the ability to fine-tune the load-balancing parameters between multiple routers. Which solution should be used to meet these requirements?

Options:

A.

VRRP

B.

GLBP

C.

FHRP

D.

HSRP

Question 3

Which statement describes differences between training and inference in AI learning models?

Options:

A.

The inference process requires high throughput to enable rapid training on large datasets.

B.

The training process is more computationally demanding because it processes new data.

C.

The training process is more optimized for low latency, which enables faster analysis of large datasets.

D.

The inference process requires continuous model adjustments to maintain accuracy with new data.

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