IBM Cloud Pak for AIOps vs. Splunk Cloud Platform

IBM Watson AIOps is well suited for IT Asset Management tasks due to its insightful dashboard that leads our IT Team to track IT Asset usage/requirements in real-time. We have also enjoyed using the reports provided for IT Asset Management which we provide to our upper management team for predictive budgeting purposes. We found that IBM Watson AIOps is not as well suited for our Application resource automation as the tuning (aggressiveness) is not as tunable as we would like.

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Splunk is excellent when all your data is in one location. Its ability to correlate all that data is intuitive (once the hurdle of learning the query language is overcome). It is also easy to standardize the presentation of information to the company. When data is siloed/standalone, other systems can be cheaper and faster to implement.

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• Easy management of multiple data center from single platform.
• Multiple host issues management and also nice file management tool.
• Effective interactive chatbot building.

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• This SIEM consolidates multiple data points and offers several features and benefits, creating custom dashboards and managing alert workflows.
• Splunk Cloud provides a simple way to have a central monitoring and security solution. Though it does not have a huge learning curve, you should spend some time learning the basics.
• Splunk Cloud enables me to create and schedule statistical reports on network use for Management.

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• Deployment procedure documentation can be improved.
• Fine tuning capabilities for IT Asset management could be improved.
• Alerting features could be improved.

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• The SPL programming language that the queries are built in is not very intuitive.
• There should be a better repository of pre-built queries for what I would think of as common Active Directory usage monitoring.
• I would like to see more free training/familiarization information made available.

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Ease of use and have all the features we need

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Splunk AI Assistant for SPL is good tool, as I said, it is really useful for educational purpose, taking in its hands small and simple tasks (ex:small query dashboard,...), but it's not a ten because the contextual memory for complex issues/dashboarding/reports etc can be limited, and can sometime suggets none optimized query which are not always checked by teammates and can cause issue on the long term.

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Splunk Cloud support is sorely lacking unfortunately. The portal where you submit tickets is not very good and is lacking polish. Tickets are left for days without any updates and when chased it is only sometimes you get a reply back. I get the feeling the support team are very understaffed and have far too much going on. From what I know, Splunk is aware of this and seem to be trying to remedy it.

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IBM Watson AIOps stacks up well with Turbonomic because it basically is Turbonomic. IBM added Turbonomic's feature set into IBM Watson AIOps and we were therefore quite comfortable shifting to the re-branded version introduced by IBM. We do like the fact that IBM Watson AIOps includes the functionality of Turbonomic.

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Vs elastic: - SPL's statistical functions superior to KQL for complex correlations - Better enterprise support, less operational overhead - Splunk Cloud Platform's detection engineering more mature vs Sentinel: - SPL more powerful than KQL for custom analytics - Better cross-platform visibility (non-Azure environments) vs Datadog - SPL enables deeper forensic Investigations - Superior compliance/audit capabilities

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• Easy to manage and monitor services from one single platform.
• The best and functional solution to host various Cloud environment.
• The management of multiple document and files.

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• End-end visibility across your departmental silos
• Strengthen the overall global monitoring posture
• Move from Reactive to Proactive Monitoring
• Highly secure environment at your finger-tips
• Takes you away from managing infrastructure/administration, allows saving time & money. Reduce the overall TCO (Total Cost of Ownership)

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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