Taking Monitoring to the Next Level
Company Size
1,000+
Region
- Asia
Product
- Datadog
- Amazon Web Services (AWS)
- Elasticsearch
- Kafka
- Braze
Tech Stack
- AWS
- Elasticsearch
- Kafka
- Terraform
- StatsD
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Software
Applicable Functions
- Discrete Manufacturing
- Product Research & Development
Use Cases
- Predictive Quality Analytics
- Real-Time Location System (RTLS)
- Remote Asset Management
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
Devsisters is a mobile gaming company with some of the most popular games in the market, including Cookie Run, which has over 100 million downloads. Devsisters focuses on promoting social interaction in its games while ensuring top-notch user experiences for its community of gamers. Devsisters is a leading tech company in South Korea and an early adopter of Amazon Web Services (AWS) and other modern technologies. With the launch of DevPlay in 2018 (Devsisters’ global game platform), and expansions to the hit franchise such as Cookie Run: OvenBreak, Devsisters has continued to scale and strengthen its operations. It has also expanded its market reach by investing in new genres such as casual Match 3 and RPG (role-playing games).
The Challenge
Devsisters, a leading mobile gaming company, needed visibility into the health of their applications to meet the demands of their rapidly expanding user base. Their existing tools added complexity that made it increasingly difficult to pinpoint user-facing issues. Additionally, the implementation and integration of these tools into their tech stack required a significant and continual time investment from the engineering team. As Devsisters’ engineering team set out to monitor and ensure the reliability of their cloud-native systems, they initially adopted a handful of open source tools for their perceived low cost. However, implementing and integrating these tools with their tech stack required a significant time investment from the engineering team, both upfront and continually. More importantly, Devsisters realized that these open source tools could not handle the scale and complexity of their modern environments.
The Solution
Devsisters chose Datadog for its flexibility, ease of use, and built-in support for dynamic and ephemeral systems. Datadog’s turn-key integrations enabled Devsisters to monitor all the technologies they use in a single place, which eliminated the burden on their engineers to build out their own solutions. The ability to see their performance data and custom metrics in the same platform also allowed them to spend less time investigating and quickly detect abnormal trends. With hundreds of vendor-backed, turn-key integrations, Datadog enables Devsisters to monitor all the technologies they use in a single place. Unlike previous monitoring solutions, Datadog does not require engineers to invest time in building out their own integrations; Devsisters is able to simply plug and play with any of the 450+ integrations that Datadog offers and easily start collecting data. Datadog is also developer-friendly and scalable by design, with support for automation tools and monitoring-as-code technologies like Terraform.
Operational Impact
Quantitative Benefit
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