Reducing Operational Overhead and Building Value through Improved Visibility
Customer Company Size
Mid-size Company
Region
- America
Country
- United States
Product
- Datadog Infrastructure Monitoring
- Datadog Application Performance Monitoring (APM)
- Datadog Synthetic Monitoring
Tech Stack
- Go
- Java
- Node.js
- React
- Python
- Amazon Aurora
- MongoDB
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Software
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Factory Operations Visibility & Intelligence
- Predictive Maintenance
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Arc XP is an independent division of the Washington Post with 300 employees. It is a cloud-native digital experience platform that enables large organizations to create and distribute content, drive digital commerce, and deliver powerful multi-channel experiences. As newspaper publishers shifted focus to address changing consumer behaviors and meet growing digital content demands, many were challenged by the complexities of creating, curating, and distributing content in what’s become a 24-hour news cycle. For the Washington Post, the answer was to develop an in-house content management system (CMS) known as Arc XP. Built to support the creation of tens of thousands of pieces of content daily, Arc XP is now an independent division of the Washington Post, offering an end-to-end digital experience platform that supports the content, digital commerce, and front-end website experiences of media companies, brands, and enterprise organizations across the globe. Since its launch in 2014, Arc XP has experienced explosive growth, and now powers eight billion monthly page views across more than 1,900 sites in over 25 countries.
The Challenge
As Arc XP grew, operational overhead increased, and it became more challenging for the Arc XP team to keep track of their environment and meet SLOs. The team needed to find a monitoring tool that could work in their complex environment and allow the organization to focus on building value for its customers. The company’s cloud infrastructure was expanding to multiple regions around the globe, and adequate visibility was vital to ensure a high quality experience for its customers. Furthermore, the engineering teams wanted a better tool to help them with technical support and IT operations. Engineers had no universal, proactive alerting system that could inform them as soon as issues arose, or a solution that could help them diagnose issues quickly. These technical obstacles, as significant as they were, ultimately presented the organization with an even more fundamental business challenge. The more time the Arc XP team spent bogged down in operations and support, the less it was using its strengths to pursue its organization’s founding mission.
The Solution
The Arc XP team knew that a powerful and centralized monitoring system could help them overcome these early growing pains. But finding a monitoring tool that could work within their particular environment would not be easy. The platform had evolved as a collection of interconnected microservices that were originally written as separate tools by different business units at the Washington Post. These tools were built with various languages, frameworks, and database types, including Go, Java, Node.js, React, Python, Amazon Aurora, and MongoDB. To this day, different engineering teams are responsible for developing and maintaining the platform’s growing and diverse set of microservices. To meet these complex monitoring challenges, Datadog offered a clear solution. Seeing that Datadog was based in the cloud and that it supported the platform’s polyglot environment, the Arc XP team took the tool around for a trial spin. During the trial period, Datadog’s ease of use stood out. When Arc XP started using Datadog, the first impression was that it was easy to use and provided a shared single source of truth for everyone, including developers, QA teams, performance teams, and product teams.
Operational Impact
Quantitative Benefit
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