IBM SmartCloud Analytics - Predictive Insights

1 like Updated 9/8/14, 7:00 AM by JCliffordTags: None

What is SmartCloud Analytics - Predictive Insights?

SmartCloud Analytics - Predictive Insights is proactive fault management system that can identify and predict faults and performance degradations in the physical and logical infrastructure.

SmartCloud Analytics - Predictive Insights analyzes performance data and learns the normal behaviour of a system. It can use data from various sources, and integrate with existing monitoring products. SmartCloud Analytics - Predictive Insights creates a performance model and uses this model to detect or forecast behaviour outside the modelled range, and generate an alarm when this occurs.


Stay a step ahead of service & IT issues with behavioral learning based outage avoidance.

The difficult task of preventing a critical service or application outage is increasingly complex with the evolution of physical to virtual computing and the broader move to cloud based infrastructures. Traditional approaches for managing services, applications and the IT infrastructure reactively will not suffice as both the speed of new services delivered and cost of service disruptions increase.

There is a fundamental need to shift to behavioral learning and to move beyond a break-and-fix to early detection. To replace decisions made on instinct and intuition to ones that are fact based and driven by real-time information and to utilize adaptable, automated solutions that continuously learn as change becomes the norm in dynamic IT infrastructures. To have a holistic view of the environment and understand the complex inter-relationships between the many components that comprise and support a service. In addition, these capabilities must be easy deploy and use, without skilled analytics experts.

With IBM SmartCloud Analytics - Predictive Insights you can fully leverage your existing performance management investments and make the necessary shift to behavioral learning based outage avoidance.



  • Maximizes early detection of service and application issues and spots problems while they are emerging to avoid business impacting service disruptions and outages.
  • Learns the normal operational behavior of dynamic infrastructures, such as a cloud, and identifies problems before you know to look for them—catches problems the first time they happen.
  • Analyses performance and monitoring data across silos, domains and vendors. Provides a single analytic solution for complete heterogeneous monitoring infrastructures.


Detect problems before they become business or service impacting

IBM SmartCloud Analytics - Predictive Insights is a state-of-the-art analytic solution for detecting emerging problems before they impact services or interrupt business. Built on a foundation of the industry’s most powerful and scalable streaming analytic engine, it processes performance and metric data in real-time from the existing IT monitoring and performance management solutions. Applying advanced analytics technologies which mathematically discover complex relationships between metrics and learns the normal operational behavior of IT and network environments. Based on this learned behavior, IBM SmartCloud Analytics - Predictive Insights is able to detect anomalies indicative of faults and support early problem detection, prior to a service disruption, by identifying the offending metrics. Built to support highly virtual cloud environments, it does not require the rip and replacement of an enterprise’s existing, often heterogeneous, performance management infrastructure. Instead both IBM Tivoli and non-Tivoli sources of performance data are able to be analyzed.


Learns complex IT infrastructure interrelationships to reduce operational costs

IBM SmartCloud Analytics - Predictive Insights doesn't require any kind of human input, such as thresholds, scripts, services models or rules; instead it employs advanced analytics that learns and models the values of performance metrics together holistically. This enables the solution to learn the complex relationships and inter-dependencies that comprise an IT and network infrastructure. In addition, it does not require statisticians or mathematicians to configure, deploy, or utilize. It was designed to be easily deployed and used by existing IT operations groups who already manage the performance and availability of services, applications and the IT infrastructure