Hugging Face vs. ignio AIOps

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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It's good for issue resolution, user access request automation, standard report generation, health checks, executing self-healing as configured in the attributes. Currently not good at real-time monitoring to trigger an action. Health checks have to be on a scheduled basis.

• 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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• ignio handles 100+ use cases covering the entire organization including applications and infrastructure.
• Centralize the dashboard to view and executed the health of systems in our environment.
• It handles CA services desk Incidents and requests. Using automated tools with power shell scripts.
• ignio event management helps the organization to manage the alerts well and make an informed decision.

• 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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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• There is a lot more the desktop tool can do. For example, we need to apply an upgrade to get the tool to talk to our infrastructure while employees are working from home. The tool was initially installed with the assumption that the desktops would be in UserLand. Instead after COVID-19 the desktop/laptops have been used for over a year on people's home networks. As of right now, we have to sync when the devices are connected to VPN. Moving forward with the upgrade, we will be getting this data over TLS when they are connected to the untrusted networks.
• The concept of ignio AlOps requires OCM efforts within most operational teams. This isn't necessarily the fault of the tool itself, but when implementing ignio, or any AIOps tool, the team will get a lot of pushback as an outside team is centralizing the operational improvements. The tool should have a centralized intake process that will allow the collection, ranking, and management of automation opportunities. ignio AlOps should then simulate the proposed efficiencies from implementing something within the backlog. Right now a lot of local teams are having a hard time getting on the same page as the enterprise teams, and a common methodology for prioritizing (even if overly simplistic) would go a long way to enterprise planning.
• These tools are very new and things get added to them all the time. There should be a way for the product's stakeholders and process owners to understand the additional value ignio AlOps is gaining over time.

It is a very good product and it helps our organization.

ignio AIOps version upgrades were a heavy lift. Having to learn a new language versus an industry standard language took time. More consideration on overall internal long-term support needs to be determined.

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It was up than Dynatrace

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

We had performance issues in older version butterfly. But the new version cheetah is simply amazing

We have built a healthy relationship with the vendor support team throughout the implementation phase, all incidents raised were resolved within the SLA without a fail

Implementation team has provided necessary training & enablement.

Online training materials are shared by the implementation team and it was good.

I am happy with the way team has implemented and shared the product for our organization. However, would like to see it get extended to the other line of business too.

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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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Self HEAL OOB Capabilites

Quite Scalable!

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

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• ignio has had a positive impact on our organization by saving 7,000+ hours within Operations and automatically resolving 84% of our service requests.
• ignio has increased our alert coverage by over 60%.