PagerDuty gains reliable, scalable analytics solution to help its 19,000 customers deliver better digital experiences
Company Size
1,000+
Country
- United States
Product
- Sumo Logic Continuous Intelligence Platform™
- Sumo Logic's application performance monitoring
Tech Stack
- AWS
- Microservices
- Cloud-native platform
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Professional Service
- Software
Applicable Functions
- Business Operation
- Quality Assurance
Services
- Cloud Planning, Design & Implementation Services
- Software Design & Engineering Services
- System Integration
About The Customer
PagerDuty, founded in 2009, is a leader in digital operations management, serving over 19,000 customers globally. The company specializes in delivering better digital experiences by identifying issues and opportunities in real time and bringing together the right people to resolve problems quickly and prevent future occurrences. PagerDuty processes billions of events to support its customer use cases, relying heavily on real-time data to understand performance across its platform’s core infrastructure and several hundred microservices running in AWS. This data intelligence is crucial for PagerDuty to meet its SLA commitments and ensure a high-quality customer experience. The company’s rapid growth and innovative approach have positioned it as a key player in the tech industry, with a strong focus on operational insights and customer satisfaction.
The Challenge
Founded in 2009, PagerDuty has grown rapidly and is now a leader in digital operations management. More than 19,000 customers across the globe rely on PagerDuty to deliver a better digital experience by identifying issues and opportunities in real time and bringing together the right people to fix problems faster and prevent them in the future. As an innovative tech company that processes billions of events to support its customer use cases, PagerDuty relies on real-time data to understand performance—from the platform’s core infrastructure to several hundred microservices running in AWS to efficiently manage customer inquiries and support operations. Data intelligence is essential for PagerDuty to deliver on its SLA commitments for a high-quality customer experience. With the desire to gain operational insights, PagerDuty chose a traditional log monitoring solution. The vendor proved unreliable in supporting PagerDuty’s significant data ingestion volume, which introduced gaps in historical data. The inability to dynamically scale with PagerDuty’s business needs created an untenable situation. PagerDuty no longer had confidence in the quality and accuracy of its query search results. Ultimately, the company concluded that the vendor wasn’t serving its needs.
The Solution
PagerDuty selected Sumo Logic—a reliable and scalable cloud-native solution—to provide much-needed operational insights. The company engaged Sumo Logic’s professional services team to assist with an accelerated migration to the platform, completing the migration in three months. The customer service from Sumo Logic during that effort was exceptional, and PagerDuty continues to receive high-quality service that sets the standard for other vendors. From the onset, PagerDuty unlocked the power of Sumo Logic’s observability with data analytics and dashboards. Sumo Logic’s monitoring and custom dashboards provide PagerDuty with visibility across developers, support, and security teams. There are 400 users who rely on the Sumo Logic platform for daily searches and inquiries, making it fast and efficient for team members to troubleshoot development issues and rapidly respond to customer support cases. The development teams use insights from Sumo Logic to understand how code changes impact the platform and the customer experience. Leveraging Sumo Logic during incident response efforts, the team has a library of troubleshooting queries and prebuilt dashboards at their fingertips to assess microservice performance, streamlining the process for engineering to resolve development issues quickly.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Factor-y S.r.l. – Establishes a cost-effective, security-rich development environment with SoftLayer technology
Factor-y S.r.l., a web portal developer, was faced with the challenge of migrating its development infrastructure to a reliable cloud services provider with highly responsive technical support. The company needed a solution that would not only provide a secure and reliable environment but also support its expansion by providing resources to create and deliver innovative offerings.
Case Study
UBM plc: Taking the pulse of the business and engaging employees with a far-reaching strategic transformation
UBM, a leading global events business, was undergoing a significant strategic transformation named 'Events First'. As part of this transformation, the company was preparing to complete the largest acquisition in its history - Advanstar, a US-based events and marketing services business valued at more than USD970m. The company faced the risk of human capital flight if it was unable to effectively engage top talent with the new strategic direction. UBM needed to make significant structural, process and systems changes, uniting its previously autonomous regional businesses. The challenge was to ensure all of its employees were engaged and aligned with the new future vision.
Case Study
Darwin Ecosystem: Accelerating discovery and insight through cutting-edge big data and cognitive technologies
Darwin Ecosystem was founded with a unique vision of harnessing chaos theory mathematics to uncover previously hidden connections in unstructured data. The company’s algorithms can look at all the data generated by any source (such as news, RSS feeds and Twitter), and analyze how a specific set of concepts within that data are evolving over time. This is particularly valuable in situations such as business and competitive intelligence, social research, brand monitoring, legal discovery, risk mitigation and even law enforcement. A common problem in these areas is that a regular web search will only turn up the all-time most popular answers to a given question – but what the expert researcher is actually interested in is the moment-tomoment evolution of the data available on that topic. Darwin’s algorithm is computationally intensive, and the sources of data it correlates can be vast. To bring its benefits to a larger commercial audience, Darwin needed to find a way to make it scale.
Case Study
Wittmann EDV-Systeme launches IT monitoring services
Small and medium-sized businesses often lack the know-how and resources required for thorough IT system monitoring. Wittmann EDV-Systeme wanted to launch a solution to plug the gap – enabling it to improve its own competitiveness and that of its customers. IT landscapes are becoming ever more complex and outsourcing is gaining popularity, IT systems must nonetheless remain easy-to-use and extremely reliable at all times. Automated, round-the-clock system monitoring therefore represents an immensely valuable proposition for companies: downtime for business-critical applications can be avoided, and IT systems remain available at all times.
Case Study
Zend accelerates, simplifies PHP development
Zend Technologies, a major contributor to the PHP open source community, needed to keep pace with emerging trends such as mobility, agile development, application lifecycle management and continuous delivery. The company needed to provide the right tools to the worldwide community of PHP developers. The challenge was to support enterprise-class capabilities from end to end, including mobile, compliance and security. The pace of business required developers to show results fast across a variety of devices without compromising quality or security.
Case Study
Delivering modern data protection with cloud scale backup from Cobalt Iron and IBM
Organizations are struggling to modernize their legacy data protection environments in the face of growing demands around new infrastructure, new applications, and budget consolidation. Virtualization and modern application development processes have significantly outgrown legacy backup architectures. In response, infrastructure teams have created multiple backup solution types to handle the varying SLAs (performance, scale, cost) required by their business sponsors. However, the sheer number and variety of solutions in this uncontrolled expansion creates huge amounts of work, threatening to overwhelm the IT team in many organizations. Today, developers may add new applications and virtual server instances by the hundreds per day without accounting for the restrictions of the existing backup infrastructure. They leverage the cloud for immediate compute and storage resources, yet rarely communicate succinctly with corporate IT to ensure that the appropriate data protection services are in place.
