AI for IT
AI can help sift through the noise to identify significant patterns in the increasingly large pools of data generated by enterprises. We’re reimagining IT operations, using AI to automate core processes, better detection and diagnosis, preformance monitoring, and explainable action recommendations.
Our work
Publications
Future Workload and Cloud Resource Usage: Insights from an Interpretable Forecasting Model
- 2024
- Big Data 2024
Ansible Lightspeed: A Code Generation Service for IT Automation
- Priyam Sahoo
- Saurabh Pujar
- et al.
- 2024
- ASE 2024
Leveraging Large Language Models for the Auto-remediation of Microservice Applications - An Experimental Study
- Komal Sarda
- Zakeya Namrud
- et al.
- 2024
- ESEC/FSE 2024
End-to-End AI (E2EAI) with Julia, K0s, and Argo Workflow
- 2024
- JuliaCon 2024
Decoding Logs for Automatic Metric Identification
- Pranjal Gupta
- Prateeti Mohapatra
- et al.
- 2024
- CLOUD 2024
Transformer Models with Explainability for IT Telemetry and Business Events
- Shiau Hong Lim
- Laura Wynter
- 2024
- SSE 2024
IBM Solution: IBM Cloud Pak for Watson AIOps
Our research has contributed to the development of IBM Cloud Pak for Watson AIOps, which deploys advanced, explainable AI across the entire IT operations toolchain to assess, diagnose, and resolve incidents for mission-critical workloads.
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