Deploypartners Case Study
Machine Learning in Network Monitoring
How a large electricity distributor in Queensland consolidated and automated their operations with IBM’s Operations Insight and DeployPartners as the lead System Integrator. Using predictive insights capability enabled the client’s operators to focus on the root cause and has delivered the business a reduced MTTR and greater visibility.
The client operates and maintains an electricity distribution network which supplies electricity to the majority of the state of Queensland. To support the maintenance and control operations for this energy supply network, the client also operates and maintains a telecommunications network that facilitates remote control and field services communication. The communications network is leveraged by a subsidiary to provide retail services to government and wholesale services to carriers and carriage service providers.
The client’s existing telecommunications Network Management System (TNMS) consisted of IBM’s Netcool Network Management (NNM) product, providing a variety of capabilities including Fault, Performance, Network Discovery and Configuration Management.
Due to the growth in network size and complexity it meant that, to maintain their effectiveness in identifying and repairing service impacting issues across their MPLS, SCADA, P25 and Cellular data networks, the operations teams needed a platform that would enable them to work more efficiently.
To achieve the goal our client required a single integrated solution that would ensure their operations continued to maintain or improve on service levels while increasing the complexity and size of the telecommunications network.
They chose to leverage DeployPartners’ skills and knowledge of service assurance solutions to enhance their legacy systems.
After a detailed evaluation, IBM’s Netcool Operations Insight Product suite with the Predictive Insights extension was selected. As it delivers comprehensive capabilities to automate tasks such as pattern based event grouping and seasonality, machine learned performance anomaly detection and data enrichment providing operators with useful information regarding a particular event, such as service, infrastructure information and location. These enhancements were sought, in addition to the primary goal of the TNMS, to present complex operational availability, health and performance information in a simple and logical way.
Over a five month period from August 2017, DeployPartners upgraded the existing TNMS components, deployed and subsequently integrated the new capabilities.
The process began with the “As-Is” analysis of custom configuration that needed to be maintained. These were mapped into the requirements and capabilities of the enhanced TNMS.
The first priority was to upgrade the core of any Network Management System, being Fault Management, this included the deployment of a multi-tier highly available architecture to cater for growth and ensure platform availability and the associated probes for collecting and processing event data. The updated Web Portal, Dashboard Application Services HUB, was also deployed at this stage to provide a single place to view Availability, Health and Performance – represented within list views and dashboards. This update included a map that indicates the health of assets by geographic location utilising an integration with Free Street Map.
The following capabilities were delivered with this solution:
- Predictive insights provides automation to performance management through learning behaviours of singular or related metrics over time. It baselines the behaviour and will automatically insert a single event into the fault management system when a singular or related group of metrics deviates beyond a normal range. This allows the client to be notified earlier than previously possible and without the administrative challenges of applying manual thresholds across thousands of metrics.
- Improved discovery and network relationship discovery.
- Additional capacity and automation of the Configuration Management platform.
- Performance Management was extended to support further network growth and upgraded to include Machine Learning capability with the Predictive Insights product.
- Event Analytics capability. Which identifies patterns of events that are unique to the client’s proposing a grouping and associated certainty that can be accepted or rejected as a rule. Adding to this the capability of Predictive Insights to group performance deviations into a single event, the volume of events presented to operators is reduced.
Event Analytics also identifies Seasonal events to allow operators to easily gain visibility of events that are recurring at certain times in order to help identify the root cause or to determine if it can be ignored and suppressed. Event grouping also takes advantage of out of the box rules for events that are known to occur together as a result of research and information shared between IBM and equipment vendors. The client has leveraged the event grouping capability to group events into categories, based on location and equipment, allowing them to immediately gain a different perspective of the state of the network. Delivery of Log Analytics to the TNMS solution allows them to store event and log file data from across their telecommunications environment giving them the ability to effectively search through and visualise large quantities of data to find patterns, anomalies and errors that dramatically improves the MTTI for enhances incident resolution and problem management.
DeployPartners has delivered to the client a single, integrated Service Assurance platform that provides the ability to view and manage the availability, health, performance and configuration of the entire network from a variety of perspectives. It provides management with the high level visibility of the overall state of services whilst giving operators greater clarity to focus on the cause (instead of the symptoms) with granular detail and information instantly available to pinpoint the event so that they can address it.
If you want to talk about predictive insights, machine learning and consolidating your TNMS using IBM Netcool or just have a chat about reviewing your current network assets please use the form below to get in touch and we’ll set up a meeting.