Intelligent Cloud Operations
AI-powered observability for serverless applications. Troubleshoot and resolve problems quickly with sophisticated features such as anomaly detection, and root-cause-analysis. Save time and money with contextual awareness, end alert fatigues and remove data siloes while increasing productivity.
The Ultimate AI Solution for Microservices
CloudAEye root-cause analysis with context
Key Features and Benefits
Manage your cloud operations and boost your team productivity with the helpful AI augmented services.
Intelligent Monitoring
Real-time insights about critical application issues without the constant tuning of configuration and rules. Setup in minutes
Logs Analysis
See AI-powered root-cause indicators from the logs automatically during an incident and avoid digging through logs
Detect & Fix Operational Issues
Automatic detection of lambda operational issues. Resolve issues quickly with ML-powered insights. See contextual information about the issue and recommendations on a possible fix
End-to-end Monitoring
AI-powered anomaly detection of distributed tracing. Avoid digging through a large number of traces during an incident
Root-cause Analysis
AI-based root-cause analysis with context to reduce MTTR. RCA removes siloes and save time and money by expediting recovery from downtime
Solution Brief
Current tools and processes aren’t ready for modern fast-paced cloud applications. Downtime and application issues translate directly into loss of revenue and adversely impact brand image. Curious if there is a better way to manage your cloud applications? Read this solution brief to learn more.
What Everybody is Saying
Monitoring serverless, actionable insights without the digging, root-cause indicators, fast recovery are some of the few things people are appreciative of.
Zakaria Swapan
Founder & CEO, Priyo
CloudAEye observability provided us with unparalleled visibility for our serverless functions. Onboarding took only a few minutes. The AI services were great to identify operational issues and provided timely insights. We saved valuable time with the AIOps workflow.
Satish V
VP & Head of Engineering, AgriTech Startup
I like how CloudAEye is using AI to enable faster recovery times in production. Easier on-call and happier SREs!
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Winner of AngelList's Top 10 Startups of the Year in AI!
"We selected these teams based on their potential to not only succeed, but to transform their respective industries."
Our Latest Blog Posts
Stay up to date on the latest innovative technologies CloudAEye is building in AI, Cloud, DevOps.
MLOps: Concept Drift
Machine Learning has proved to be a lucrative innovation, generating substantial profits for many organizations. In the context of machine learning, the term “concept drift” a.k.a. “nonstationarity“, “covariate shift” and “dataset shift” describes a phenomenon where the connections between input and output data in a given problem undergo changes over time.
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