Bank Cuts Response Time with Lossless Visibility

Automate Event Triggers and Monitoring Response

Summary

Being more responsive, even proactive in investigating or preventing outages takes a highly automated monitoring infrastructure. Data capture and analysis must occur in near-real-time for responders to find and resolve the root cause of performance or security issues. Automate visibility to avoid manual effort and speed resolution times dramatically, sometimes by 75%.

With automated visibility, IT and SecOps teams use open or RESTful APIs to proactively define triggers and automate visibility workflows instead of using a UI to react each time something happens. Automated workflows speed delivery of the right traffic to the right tools for analysis—even before users open tickets. Admins use APIs to automate dynamic filtering of traffic from specific IP addresses to specific monitoring tools for analysis.

Operations skills exist in ever-shorter supply. An adaptive monitoring environment lets ops teams manage visibility programmatically and integrate packet brokers with monitoring tools for next-level efficiencies. Use open APIs to speed integration of inline or out-of-band monitoring tools into your visibility framework. With the right data at the right time, the 40+ APM and cybersecurity tools in your SOC or data center become more accurate, available, and efficient. Ultimately, automation improves MTTR and extends monitoring capabilities without additional investment to provision multiple tools across your entire network.

Challenges

Maintaining application quality

Application quality and end-user satisfaction are central to the bank’s success. The bank’s systems development department is responsible for resolving issues with applications that affect service quality and end user transactions. The team noticed an increase in customer complaints involving service disruptions. Traditional performance monitoring and WAN optimization tools did not provide the insight necessary for the team to diagnose the underlying cause.

Diagnosing underlying performance issues

The systems development team was struggling to diagnose the underlying cause of application disruptions and slow performance. Frequently, issues the team had closed recurred and required additional investigation. The team found it difficult to objectively determine the effectiveness of application implementations in the production network even in situations where information was available from logs and web servers.

Ensuring monitoring systems scale with business

An initial assessment revealed that recent increases in traffic volume had overwhelmed the company’s monitoring tools. As a result, the tools were taking too long to process data and were dropping packets. Support managers suspected incorrect results were contributing to the recurrence of application disruptions.

Use case

This large regional financial institution is committed to customer service, which has been its competitive advantage for 60 years. Executives had the foresight to strengthen the bank’s online presence, resulting in roughly 10 million downloads and application updates for smartphones and tablets. Amid the bank’s digital transformation, IT began struggling to maintain service quality as customers did more of their banking from smartphones, tablets, and other remote points of service.

Solution overview

Automatically align Application Performance Monitoring (APM) and cybersecurity tools with dynamic network changes to promote adaptive monitoring, faster response, and better tool, skills, and bandwidth utilization.

Results

The newly created Application Performance Monitoring (APM) center of excellence (CoE) team takes responsibility for ensuring application availability and identifying the root cause of issues. The CoE also defines key performance indicators to track application quality and availability over time. Since the deployment of the new visibility and monitoring solutions, engineers report a 30 percent reduction in response time for key application MTTR. The team attributes a reduction of 25 percent in support cases related to application outage for better detection and root cause analysis.

With better systems and automation in place, the APM CoE team can devote more time to proactive monitoring – running synthetic application traffic through their network to identify potential issues.