Continuously Monitor and Fix your Cloud and Kubernetes infrastructure with Security detection and response module. Monitor the behaviour of Cloud services and VM, detect threats and anomalies in your cloud infrastructure and automatically respond.
We analyse the behavioural patterns using ML algorithms and identify insider threats in Cloud Identities and Assets.
Our Compliance engine ensures your cloud assets and data stored in cloud is compliant with PHI, PII, HIPAA, PCI, NIST etc standards.
Our intelligent AI algorithm protects your data stored in cloud like Amazon S3, Azure blob with Sensitive Data Detection, De-Identification, Data Watermarking and Row/Column Access control. Monitors the behaviour of the data shared with your partners and pre-empts data exfiltration threats.
Real-time alert ingestion and event correlation. Moderate the signal-to-noise ratio using techniques like alert bucketing, Natural Language Processing, Temporal Correlation to analyse only the alerts that matter
Alerts and Change events are intelligently filtered and grouped into Cases. DevOps can Pin Point the problem in minutes using the information presented in the Case. Alert and Asset Graph Topology, Metric Anomalies, Causality algorithms using presented visually to help the DevOps understand the problem quickly.
Probable Root cause analysis is conducted using combination of AI/ML algorithms involving Alert graphs on Topology, Probabilistic Graph Models, Neural Networks, Temporal and Time Series forecasting.
Pre-built Cloud Automation programs engineered to manually/automatically remediate 100+ Availability and System Reliability use cases. Support for AWS, Kubernetes and GCP.
How to analyse and detect a Root Cause in Cloud like a DevOps ? Can AI algorithms make this simple and intelligent ?
Detecting outliers in metrics time series plays an important role in preventing our applications from failures. Let us see how to use time series forecasting model with seasonality component to handle this problem
How to use Machine learning to analyse the behaviour patterns, detect anomalies and indicate potential threats using User and Entity Behaviour analysis?