Nastel XRay allows you to find data outliers faster and sense problem conditions before they actually affect users. Your data (streaming or imported from a file) is put in a repository and displays as a collection of customized viewlets grouped into one or more dashboards depending on your needs. Watch the following video for a brief overview.
Nastel XRay answers business related questions and provides guidance for decision-makers
Nastel XRay combines:
- Analytics using advanced predictive anomaly detection and machine learning algorithms for problem prevention across apps, messaging, logs, mobile, and the IoT.
- Insight into applications including payment processing, trade compliance, order tracking, healthcare claims processing, compliance, machine data, and more.
- Visibility across the IBM stack (IBM MQ, IBM Integration Bus (IIB), DataPower, MQ File Transfer), Java, mobile, and the newer open-source technologies such as Kafka, STORM, Spark, MQTT, log files, Python, REST, and much more.
- Multi-tenancy with private data repositories available on premise or in SaaS.
- Lambda architecture with grids for real-time, in-memory analytics as well as historical analytics, data replication, and time-to-live for all streaming data.
- End-to-end business transaction tracking that spans technologies, tiers, and organizations.
- Intuitive, easy-to-use data visualizations and dashboards.
These capabilities fuse seamlessly across dynamic IT environments, from mobile to mainframe. They provide the broad array of analytic and decision-support capabilities needed by developers, IT admins, and business analysts to satisfy real-time operations intelligence and application performance monitoring (APM) needs.
Insight, visibility, prediction, and machine learning that is easy-to-use to:
- Improve service to customers and reduce operational risk– using machine learning analytics.
- Highly scalable with self-service access, without need for data scientists– using flexible web-based UIs and natural language for ease of use and a powerful Lambda architecture with micro-services for scalability.
- Reduce support costs– via Docker deployment, open-source data collectors and ease of use.