Hugging Face vs. Splunk IT Service Intelligence (ITSI)

If an organisation has more access to data and have access to high end computers like GPUs it’s recommended to use Hugging face as it will give better accuracy than any other models. If an organisation having less data and has less access to GPUsis looking for decent performance then traditional algorithms are more appropriate than hugging face

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Splunk ITSI is a great tool (and toolbox) for combining together numerous and varied monitoring regimes to bring more holistic analysis and reduce alert fatigue. By leveraging the Splunk ITSI service and KPI modeling regime, ecosystem telemetry can be turned into a more reliable, clearer, high-level perspective on the current state of your components and services.

• Model APIs
• Hugging Face Spaces for deploying demo apps
• Latest updated models available easily
• Vast support for language parsing and other relevant tasks

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• Monitor hundreds of IT services by continuously tracking thousands of KPIs in a scalable way.
• Quickly identify problem areas by a combination of default visualizations and ability to create custom dashboards.
• Extremely configurable to effectively monitor nearly any KPI imaginable from Splunk.

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• Most of the Hugging face models are of big size, hence difficult to work if there is no access to high computational system like GPU.
• It’s good to have some visualization tool in hugging face for viewing model architecture.
• I recommend to implement hugging face lite version so that it can run on any system with less specifications.

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• ITSI really needs a robust splunk log ingestion infrastructure at its core
• ITSI requires a great engineering team to build out the automated discovery and topology
• Unless you use an API to build the topology, the view can quickly become static

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We have replaced our monitoring platform with Splunk & ITSI, and with the success, it's seen at our organization thus far we would be hard-pressed to pivot to another tool. Frankly, our business partners and application teams love Splunk & ITSI.

Splunk IT Service Intelligence (ITSI) is a platform with extended functionality and provides various functionalities which can be utilized to improve the efficiency and accuracy in analyzing the data and detecting the attacks.

During POC, pre-planning, and implementation, we have had interactions with numerous folks at Splunk. Everyone from sales & engineering to markets analysts to specific IT component SMEs, and a small professional services engagement to get started. They have all been exceptionally helpful and go above and beyond the call of duty. They actively reach out to ensure success is being realized and find ways to help proactively, instead of having to simply open support cases with the vendor.

There are some other services offer similar capacity as to Hugging Face, but not entirely the same. For example, amazon web services have a machine learning service called Comprehend, which offer a set of easy to use APIs to do machine translation and entity recognition and some other common NLP use case.

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Splunk has raised itself as a platform not just as a tool unlike other products in the market. If I talk about Moogsoft it also has similar capabilities but Splunk ITSI has more visibility and its GUI is making a different impact on the users. ServiceNow and Splunk are equally capable products however Splunk seems to have more tech-savvy people tools than ServiceNow.

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Independently Invited by TrustRadius

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• Hugging Face is cost and time saving.
• Pay is less, you pay what you use, doesn't affect much.
• Overall positive impact on business.

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Independently Invited by TrustRadius

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• Splunk ITSI has reduced the number of alerts exposed to our Network Operations Center by 100x while increasing the context around outages.
• Splunk ITSI has increased the accuracy of our incident detection by leveraging the Event Analytics system to weigh the behavior of the many characteristics of each component together instead of independently.
• Splunk ITSI has reduced our incident MTTR (mean time to restore) by detecting issues faster, presenting them more clearly, and surfacing the salient details about the underlying issue.