This case study focuses on one of the largest cloud Human Capital Management (HCM) providers in the world. Founded in the early 2000s, its software-as-a-service products and human resource transformation services are used by more than 6,600 customers with 120 million users in more than 200 countries. The company is based in San Francisco, California and is a subsidiary of a market leader in enterprise application software. Its digital transformation initiative recently migrated 100% of its services to a cloud environment. The subsequent exponential growth in transactions triggered a byproduct of “alert fatigue” with too many monitoring tools generating too much noise to effectively identify issues and quickly resolve them. The company turned to Moogsoft to simplify performance support, accelerate resolution of issues, and boost customer confidence in its ability to support their businesses.
“Moogsoft has changed [our] ability to support our cloud customers better. AIOps gives us visibility on what may happen in the future, which grows our customers’ confidence in [us] supporting their business in the cloud.”
– Chief Technology Officer
Managing a Full Transition to All-Cloud Architecture
The company is a global provider of cloud-based human capital management (HCM) solutions. The San Francisco-based company is a major enterprise cloud service provider that recently migrated 100% of its services to a cloud environment. Its push for digital transformation to an all-cloud microservices architecture came from exponential growth during 2017 and 2018. Transactions grew 46% with 650 million per day and two million unique daily visitors on the platform. The company needed to scale operations faster albeit with a major caveat: “As part of the migration, our board directed us to ‘delight our customers’ with even better service,” says their Chief Technology Officer.
Too Many Tools for Useful Results
“We knew the old approach to managing infrastructure would be problematic as the surge in event data was causing ‘alert fatigue,’” the CTO says. Lack of visibility and increased overhead for each DevOps team usually delayed first responders by 45-60 minutes just to determine who the responsible parties were for each incident. The culprit was having to manually decipher operational data from seven individual monitoring tools – each with its own dashboard covering 18 data centers. “That model could not scale,” the CTO says. Moreover, support teams were usually in “reaction” mode because 80% of incidents were first reported by customers. Having to acknowledge performance issues after-the-fact to customers who already knew something was amiss was not engendering confidence in the company's ability to support their respective business missions.
“When our board members ask us how we are improving operations and customer performance, we show them what we’re doing with Moogsoft.”
Deploying AIOps to Manage Digital Transformation Performance
To address its business challenges, the company deployed Moogsoft, the pioneering platform for IT operations powered by purpose-built machine learning algorithms. The company’s motivation was to improve its operational signal-to-noise ratio by reducing and then correlating alerts together. The AIOps platform automatically suggests root cause and enables rapid cross-team collaboration to solve incidents faster.
A huge factor in choosing Moogsoft was closely tied to the HCM company’s adoption of a microservices architecture for agile application development, according to the CTO. “The microservices approach increases event telemetry dramatically, which makes it harder to detect and resolve incidents without AIOps,” says the CTO. To successfully monitor six million data points per month, the new AIOps solution replaced all of the old individual monitoring tools and dashboards.
After deployment, support teams experienced a 99.6% reduction in alert noise and the number of actionable tickets. The ability to focus exclusively on events that truly mattered transformed support operations from reactive to proactive and increased DevOps productivity, according to the CTO. “Operators are now aware of the potential for incidents before they impact services. This predictive capability includes visibility across Azure and on-premise services with a single consolidated view – all without increasing headcount or resources,” says the CTO.
“... we matured the Operational staff from just looking at incidents and flashing lights to looking at incidents and coming out of that and saying here is what happened, here's how we fixed and here's what we know going forward to make sure it doesn't happen again.”
Accelerated Resolution of Operational Issues
One of the most important benefits the company can provide to its customers is rapid resolution of operational issues. The CTO notes that some of these companies are among the largest businesses in the world, so every minute of downtime or reduced performance can have significant revenue impact to their bottom lines. “AIOps lets us identify and notify owners almost instantaneously.” He says the transformation in support capability has been dramatic. “Moogsoft has changed our ability to support our cloud customers better. Our teams automatically get context and executable knowledge that has in some cases cut time-to-resolution by 80 percent.”
Improved Performance of Cloud HCM Solutions
The company has accomplished its goal of delivering a better cloud-based customer experience for its HCM solutions. The machine-learning automation has enabled a simplified support infrastructure, which in turn has helped the company meet its organizational maturity goals. As an institutional benefit, the company has met its year-to-date ITIL goal across the five stages of best practices maturity for IT service management. The CTO says this achievement has increased scalability with customer deployments.
Boosted Confidence in Support
As for “delighting its customers” with better service from an all-cloud model, the company has used AIOps to help deliver on four related promises to its customers: (1) Availability, where SLAs are met and outage minutes have dropped; (2) Transparency, where the service catalog availability and customer communications are now managed via ServiceNow; (3) Speed, with issues that are now fixed faster; and (4) Maturity, which enables increased scalability with deployments.
The use of Moogsoft has also reinforced the business value of the company to its executive management. “We want our board to look at our competence, and using AI to enhance business operations is very big [here],” the CTO says. “So when our board members ask us how we are improving operations and customer performance, we show them what we’re doing with Moogsoft.”