The world’s largest financial service firms use AutoPilot® to monitor applications such as compliance, payment and fraud detection.
A major US-based financial services firm switched vendors from a large software provider to Nastel for its real-time monitoring and administration of WebSphere MQ. The customer is using AutoPilot for root-cause analysis of issues across both their distributed and mainframe topologies. The applications monitored include: payment, trading and insurance.
A Wall Street Capital Markets firm utilizes AutoPilot for monitoring compliance with the Dodd-Frank Act. Dodd-Frank compliance requires improved transparency and accountability for trade reporting. And this implies new demands on IT to ensure performance and visibility including reporting all swaps no later than 15 minutes after electronic execution and verification and resubmission of rejected trades within the original 30 minute deadline. In addition all trades must be retrievable for up to 5 years after maturity or termination. These demands and many others in this still evolving standard translate into a need for greater IT visibility with smaller windows for course correction. AutoPilot is being used by both IT and Compliance Officers in order to ensure they are effectively working together. For more information watch the video on this case study.
Global Cash Services
A Fortune 50 bank uses AutoPilot to monitor their global cash services, worldwide. This includes cash management, file transfer, EFT, equities, credit card processing and their connection to the Federal Reserve and CHIPS for funds transfer and interbank payments transactions. These applications are running on both distributed and mainframe environments in the bank’s private cloud. In order to deliver the highest customer service, performance and availability this bank uses AutoPilot in both production and development. For more information: read the case study on this bank.
Bill Payment and Fraud Detection
Fiserv uses AutoPilot to monitor their Bill payment and Fraud Detection infrastructure. They utilize AutoPilot’s monitoring and SLA management to immediately spot the difference between “business normal” and “business abnormal” application states and meet its goal to catch errors before they become problems, increasing service quality. For more information: read the Case Study on Fiserv.
How we do it
AutoPilot’s automated discovery and real-time analytics provide deep visibility, delivering unified visualization on a single pane of glass. This is done across all infrastructure tiers:
- AutoPilot automatically correlates (stitch) all transactions and messages across tiers into meaningful end-to-end transactions, optionally based on payload visibility
- It captures all message payloads for both real-time and historical analysis
Simple Proactive Analytics
- Built-in, real-time analytics handles millions of events per second using Complex Event Processing implemented on an active data grid for transparent scaling and high availability
- AutoPilot evaluates situations comprised of relevant application performance indicators in-memory as they happen, essential for compliance monitoring where there isn’t a second to spare
- Baselines are automatically created for each relevant indicator
- Analytics detect patterns and policies are evaluated
- Immediate determination is made when performance first begins to veer from “business normal”
- Faster problem detection and resolution, before users are impacted by providing significant intelligence around the issue. “What the request was, which servers were involved, the timing of the actions related to the failure and what data was in the payload”
- Reduced support costs – by preventing false alarms (false positives)
- Vital insight into compliance – faster and in context