HCSP - Data Center Network Planning and Design

- Participants should have a fundamental understanding of IP technologies and networks.

- It is recommended that you complete the HCSA-Presales certification course before attending this training

On completion of this course, participants should be able to:

- Understand the key technologies in the data center (DC) field, including underlay/overlay, VXLAN, M-LAG, BGP EVPN, virtualization, network security, and intelligent network O&M technologies.

- Describe the typical data center network (DCN) architecture.

- Describe the common DCN virtualization and reliability technologies, their working principles, as well as their application scenarios of various virtualization technologies.

- Describe the basic principles and functions of the CloudFabric Solution.

- Describe the basic concepts and working principles of VXLAN, as well as the benefits brought by VXLAN in DCNs.

- Describe the intelligent lossless Ethernet technology.

- Describe the M-LAG technology for DCs.

- Describe the four scenarios for automatic service provisioning in the CloudFabric scenario.

- Design the CloudFabric underlay and overlay network solutions.

- Design large- and medium-sized CloudFabric DCN solutions.

- Describe the main functions and cases of FabricInsight-based intelligent O&M.

The HCSP-Presales-Data Center Network Planning and Design certification exam # H19-402 written exam covers the data center network (DCN) architecture and application of typical technologies (DCN principles, VXLAN, BGP EVPN, Underlay&Overlay, and M-LAG), CloudFabric solution and components, service automation scenarios (network virtualization, computing, OpenStack cloud-network integration, and Kubernetes container network) of the CloudFabric solution, intelligent lossless technology, and CloudFabric's "three data centers (DCs) in two cities" network design, CloudFabric's "multiple DCs in multiple cities" network design, CloudFabric network security design, and intelligent O&M of the CloudFabric solution.