Slam Dunk: How One Broadcaster Rose to the Challenge

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One of the world’s largest television and digital entertainment companies had a problem.

A company-wide initiative to reinvent its service delivery demanded that IT help make its content available anytime, on any device. As a global media conglomerate, its enterprise spans numerous entertainment, news and sports networks – including broadcasts of major league basketball. Customer data would need to be better leveraged to deliver more relevant experiences and target advertising across all channels, in time for the next NBA season.

To support this drive, existing IT systems would need be centralized, modernized and moved to the cloud. Unfortunately, these changes added strain in the IT service operations center for a monitoring and incident response team that was already stretched thin. The operations team was overwhelmed by the volume of alerts from more than a dozen monitoring systems across more than 400 internal applications, dozens of digital properties, and numerous back office systems.

Its current stack made quick, proactive response to IT events difficult or impossible. Engineers spent significant time triaging alerts and manually correlating event data into incidents. This profound lack of automation slowed response times, limited situational analysis across teams, and increased service disruptions and outages. The fragmentation and complexity of these processes made it impossible to measure and optimize the effectiveness of IT service operations from either a technical or a business perspective.

Nothing But Net: Selecting BigPanda

To support its changing infrastructure, the broadcaster required a unified view of incident management across its entire monitoring stack. The company’s specific objectives were:

  • Improve response quality through insights
  • Enable visibility across teams
  • Reduce operational costs and risk

After attempting to build a DIY system, the broadcaster evaluated vendors that apply machine learning to automate the alert correlation process. In the end, they selected BigPanda’s Algorithmic Service Operations platform over Moogsoft, a competing alternative.

Only BigPanda offered the breadth of integrations, sophisticated correlation algorithm, and intuitive UI that the customer required. The platform’s open integration with its existing monitoring stack leverages existing investments to provide holistic, contextually enriched incident data.

One example is BigPanda’s integration with Catchpoint, a digital experience management platform that monitors web application performance from over 700 global locations. Using the Catchpoint Alert Webhook, results from Catchpoint web and mobile tests are correlated into high-level incidents in BigPanda. This helps the DOC team understand and respond faster to web production issues.

BigPanda was also able to prove its deep integration with other tools of choice including AWS CloudWatch, Circonus, DataDog, Monit, New Relic, ServiceNow and Zabbix.

BigPanda Fast Breaks to Strong Finish

Once this media powerhouse had made its decision, the clock was ticking. As a major sports broadcaster, they wanted to be up and running on BigPanda before the new NBA season began in November.

BigPanda was up and running in less than three months, including a custom outbound integration with the broadcaster’s IT service desk system, ServiceNow. The BigPanda platform is delivering correlation rates exceeding 80% in the customer’s critical DOC environment. 35 users actively interact with the platform, and collaborate across teams to speed resolution of specific incidents.

How do they do it? First, algorithmic alert correlation employs machine learning to analyze alert storms from multiple tools and cluster them into incidents, eliminating past manual efforts. Once events have been correlated, our Smart Ticketing and incident management workflows streamline the escalation and remediation process. This centralization of IT event data allows ops engineers to speed up incident response. With BigPanda, users across application, network, platform and database teams can respond more quickly and collaborate more efficiently. The result for the broadcaster is increased operational agility at reduced risk and cost.

BigPanda is also improving the customer’s operational visibility by providing insights necessary to design more resilient and efficient ITOM systems and processes. Armed with the platform’s operational analytics and reporting, ops engineers will optimize for key business metrics. The algorithm’s correlation patterns will be further customized to the enterprise’s unique environment. Over time, these insights will further shorten response times and increase availability of critical applications and services.

That’s how one global media leader is employing intelligent automation to improve the quality of IT service operations. IT is a critical component of powering exceptional, more targeted customer experiences across its entire business.

Read more: BigPanda Announces Catchpoint Integration