With the demands of rapid service delivery and data center scale of bearer service increasing continuously, it needs to standardize and plan the construction and maintenance of data center, and use O&M automation tools (or devices) to handle with repeated and mechanical works, to save human resources, reduce manual error risk and achieve rapid service onboarding. ZTE TECS automatic O&M solution provides three kinds of automation tools including iDevise, Daisy and HealInspect, to carry out automatic project provisioning and daily O&M of data center.
iDevise: According the customer’s BOQ, it implements automatic DC design, automatically generating configuration documents for the deployment and installation of HLD, LLD and DC.
Daisy: It is responsible for the automatic deployment, upgrade and expansion of DC. ZTE Daisy is based on the open source Daisy, and makes innovation in interface, version management, automated expansion and other aspects, addressing large-scale cluster deployment and centralized deployment, to achieve more automatic, simpler and efficient deployment, upgrade and expansion.
HealInspect: It provides unattended O&M capability, achieving automated polling and network monitoring. It also provides automated test and network enforcement as well as failure device replacement capability.
The solution customer value is as follows:
1)Rapid Service Onboarding
Automated DC design and deployment shortens the construction period, and accelerates the onboarding speed of service carried by the DC. At the edge cloud, the solution is able to deploy multiple edge DCs remotely in a centralized manner, to shorten the construction period and balance the construction progress of all the DCs.
The solution provides unattended O&M, which carries out rapid and accurate fault location and implements fault self-healing according to user policy, such as automated replacement of faulty device.
3)Reducing Possibility of Manual Error
Cloud DC has lots of devices, presenting very complicated networking and software functions. The O&M of fault location, troubleshooting and fault avoiding is very complex. If using manual O&M, it subjects to the ability of O&M staff, and some on-site decision may not be correct. Whereas, the AI and big data based automated decision can ensure the consistency and correctness of each decision as long as the software is correctly designed.
4)Easy to Operate
The solution supports automated navigational deployment, upgrade and expansion. It provides configuration templates to simplify cluster and host configuration. It also supports the automatic expansion of computing nodes, convenient for new hosts accessing the cloud environment quickly.
The graphic network topology intuitively displays fault and traffic status, enabling O&M staff to monitor the network conveniently.