Recently Linkedin ServiceNow Learning Community contacted the evaluation of ServiceNow related posts through Linkedin and selected the top most popular ServiceNow posts loved by Linkedin members. This evaluation process has been performed based on the following categories:
- The post must be ServiceNow OOB features, configuration and technical scripts.
- The like score -
must be top 15 and have high repost
Top 13 most popular posts and authors are summarized below:
IT Operations Management (hashtagITOM) is an essential discipline within Service Management and has been a significant focus for ServiceNow since the early days of the hashtagnowplatform!
As technology is increasingly interwoven with the services and applications we use daily, ITOM's role in businesses becomes more crucial. ๐ป๐ฒ
However, the task is challenging, especially with the expansion of IoT devices and Artificial Intelligence. ๐ค In this context, ๐๐๐ญ๐ฒ๐ ๐๐๐๐๐ฅ๐ฅ๐, Microsoftโs CEO, aptly stated, "๐ธ๐ฃ๐๐๐ฆ ๐๐๐๐๐๐๐ฆ ๐๐ ๐ ๐ ๐๐๐ก๐ค๐๐๐ ๐๐๐๐๐๐๐ฆ. ๐๐๐ข โ๐๐ฃ๐ ๐ก๐ ๐ ๐ก๐๐๐ก ๐กโ๐๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐๐ก๐๐๐ ๐๐๐๐ ๐ ๐๐๐๐๐ก๐๐ ๐๐๐๐๐๐๐ฆ." ๐ฃ๏ธ
This quote highlights the importance of ITOM in modern business operations, where even a minute of downtime can cost ๐๐พ๐๐๐พโด๐๐! โฐ๐ธ
The following diagrams outline five critical areas of the ServiceNow ITOM Suite, now a part of Technology Excellence:
1๏ธโฃ ๐ฟ๐๐จ๐๐ค๐๐๐๐ฎ:: Integrated into the Now Platform from its early days, it helps collect information from devices and populates the hashtagcmdb ๐บ๐ป
2๏ธโฃ ๐๐๐๐๐ฉ ๐๐๐ฃ๐๐๐๐ข๐๐ฃ๐: This involves collecting events from monitoring systems, correlating them, and generating alerts. ๐จ
3๏ธโฃ ๐บ๐๐๐ซ๐๐๐ ๐ด๐๐๐ฅ๐๐ฃ๐: This feature enables the creation or discovery of Service impact models, attaching events to the nodes of these models. Service Mapping was the second ServiceNow acquisition of the company Neebula in 2014, and their flagship product, ServiceWatch, was fully reimplemented on the platform. ๐บ๏ธ
4๏ธโฃ ๐ช๐ค๐๐ ๐ผ๐๐ฉ๐๐ข๐๐ฉ๐๐ค๐: This plugin underpins the technical capabilities required for discovery. โ๏ธ
5๏ธโฃ ๐๐ฐ๐ฟ ๐๐๐ง๐๐๐: It serves as the foundation for the functioning of the Management, Instrumentation, and Discovery server, supporting discovery and many other capabilities. ๐ ๏ธ
The advent of hashtaggenai capabilities within the hashtagnowplatform is currently one of the most engaging topics of discussion, positioning the ServiceNow GenAI data model as an essential subject for exploration and comprehension.
GenAI symbolizes a pivotal moment for any organization, underscoring the realization that systems that ๐integrate ๐๐๐ ๐๐๐๐๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐ ๐๐๐
๐๐๐๐๐๐๐๐๐ are poised to surpass those powered solely by either. This observation highlights the impact of GenAI in ๐ propelling ๐จ๐ฉ๐๐ซ๐๐ญ๐ข๐จ๐ง๐๐ฅ ๐๐๐๐ข๐๐ข๐๐ง๐๐ข๐๐ฌ and ๐๐๐๐ข๐ฌ๐ข๐จ๐ง ๐ฆ๐๐ค๐ข๐ง๐ to new heights.
Incorporating GenAI into the ServiceNow architecture enriches its existing AI/ML capabilities. It aims to facilitate a myriad of tasks, including ๐ ๐ ๐ข๐๐๐๐๐๐ง๐๐ก๐๐๐, ๐ป ๐ก๐๐ฅ๐ก-๐ก๐-๐๐๐๐, ๐ ๐ก๐๐ฅ๐ก-๐ก๐-๐ค๐๐๐๐๐๐๐ค, ๐ฃ๏ธ ๐ฃ๐๐๐ก๐ข๐๐ ๐๐ ๐ ๐๐ ๐ก๐๐๐ก ๐๐๐๐ฃ๐๐๐ ๐๐ก๐๐๐๐ , ๐๏ธ ๐๐๐๐ ๐๐ข๐ก๐๐๐๐๐๐๐๐ก๐๐๐, and more, through seamless integration with both native (hashtagNowLLM) and third-party Large Language Models (hashtagllms ).
Attention might gravitate towards elements like the ๐๐ฒ๐ป๐๐ ๐๐ผ๐ป๐๐ฟ๐ผ๐น๐น๐ฒ๐ฟ. Yet, the essence of the GenAI data model is predominantly housed within ๐ฎ๐๐๐
๐ ๐ถ๐๐๐ฌ๐๐๐๐๐
, ๐ฎ๐๐๐
๐ ๐ช๐๐๐๐๐๐๐๐๐๐๐ ๐ฎ๐๐๐๐๐๐๐๐๐ ๐จ๐ฐ, and the ๐ต๐๐ ๐จ๐๐๐๐๐* ๐ฆpackages.
The diagram provided below outlines all the entities and relationships in those packages, offering valuable insights
for those keen on delving deeper into the product through documentation and available training resources:
๐ด ๐๐๐ง๐๐ ๐๐๐ฉ๐๐๐ข๐ฅ๐ข๐ญ๐ข๐๐ฌ: The foundational capabilities of the GenAI model, crafted through configurations, definitions, and attributes.
๐ด ๐๐๐ง๐๐ ๐๐๐ฅ๐ข๐๐๐ญ๐จ๐ซ๐ฌ: Employing validator scripts to enhance the quality and format of responses.
๐ด ๐๐๐ง๐๐ ๐๐จ๐ ๐ฌ: The logbook of all GenAI interactions, pivotal for subsequent analysis and gaining insights.
๐ด ๐๐จ๐ฐ ๐๐ฌ๐ฌ๐ข๐ฌ๐ญ ๐๐ค๐ข๐ฅ๐ฅ: Detailing the configuration of available skills.
๐ด ๐๐ ๐๐๐ง๐๐ ๐๐ค๐ข๐ฅ๐ฅ: Illustrating the specific skills related to virtual assistants.
A ๐ก๐ข๐ ๐ก-๐ซ๐๐ฌ๐จ๐ฅ๐ฎ๐ญ๐ข๐จ๐ง ๐ฏ๐๐ซ๐ฌ๐ข๐จ๐ง of the diagram is accessible via a ๐๐๐๐ ๐๐ ๐๐๐ ๐๐๐๐๐๐๐๐ for those interested in a more detailed exploration. If you find this overview beneficial, please consider ๐ญ๐ช๐ฌ๐ช๐ฏ๐จ, ๐ค๐ฐ๐ฎ๐ฎ๐ฆ๐ฏ๐ต๐ช๐ฏ๐จ, ๐ข๐ฏ๐ฅ ๐ด๐ฉ๐ข๐ณ๐ช๐ฏ๐จ this post with your network!
P.S.: The analogy of GenAI with clocks and alarms might stem from its inherent urgency and potential for immediate impact. Echoing ๐๐ญ๐๐ฉ๐ก๐๐ง ๐๐๐ฐ๐ค๐ข๐ง๐ , AI will be โ๐๐๐กโ๐๐ ๐กโ๐ ๐๐๐ ๐ก ๐๐ ๐กโ๐ ๐ค๐๐๐ ๐ก ๐กโ๐๐๐ ๐๐ฃ๐๐ ๐ก๐ โ๐๐๐๐๐ ๐ก๐ โ๐ข๐๐๐๐๐ก๐ฆ.โ We must navigate its development with careful governance to unlock [Gen]AI's vast benefits
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