Gathr Case Studies DORA Metrics : Ensuring DevOps Success
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DORA Metrics : Ensuring DevOps Success

Gathr
Analytics & Modeling - Real Time Analytics
Business Operation
Predictive Quality Analytics
Root Cause Analysis & Diagnosis
Data Science Services
The company, a leading media and entertainment entity with a presence in over 150 countries, was facing challenges in managing its applications, including a newly launched subscription-based streaming application. The company's internal DevOps team was responsible for managing these applications, but the company wanted to improve visibility into performance, identify areas for improvement, and gauge customer experience. However, they lacked a standard framework to measure DevOps success and relied on monthly manual reports to understand the team's health and performance. This approach had limitations in analyzing DevOps data and metrics. Furthermore, frequent bugs and a longer time to resolve issues led to a poor customer experience.
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The customer is a leading media and entertainment company with a presence in over 150 countries. The company has a headcount of over 3000 employees. In addition to its newly launched subscription-based streaming application, the company has other apps that require frequent updates. The company's internal DevOps team manages these applications. However, the company was seeking to improve visibility into performance, identify areas for improvement, and gauge customer experience.
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The company partnered with Gathr to implement DORA metrics, a widely accepted standard for tracking DevOps success. The solution included a unified dashboard to monitor the metrics, enabling the company to understand the root cause of issues and drive decisions for continuous performance improvements. The solution featured out-of-the-box connectors to unify data across tools like Jira and Jenkins, providing end-to-end visibility across development, deployment, and operations. The visual dashboard monitored the four key DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service). The solution also allowed for custom metrics to meet evolving requirements for strategic and operational decision making and trend analysis to gauge metrics over a defined period and analyze Lead Time based on parameters like Assignee, Type, Priority, etc.
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The company gained accurate visibility into the performance of its DevOps team and the time taken to resolve issues.
With near real-time visibility and the ability to track and analyze metrics over a unified interface, the delivery leaders could easily identify performance gaps.
Deployment Frequency increased from 1 deployment per week to 2 deployments per week.
Time to Restore Services reduced from 18 hours to 6 hours.
Change Failure Rate reduced from 26% to 11%.
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