Datadog Highlights How to Resolve Top 5 Redis Performance Issues

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New eBook describes how to access and use performance metrics to resolve Redis problems.

Datadog, the SaaS-based monitoring and data analytics platform that provides a unified view of IT infrastructure, released today a troubleshooting guide for developers and system administrators that work with Redis. In the new eBook, “Understanding the Top 5 Redis Performance Metrics,” Datadog’s technical team details the top five Redis performance metrics and provides instructions on how to use this data to detect and remediate performance problems.

Redis provides a fast and persistent memory storage system, superior caching and the ability to support multiple data types, which is ideal for a number of different processes within an application. However, to provide this speed and at the same time maintain its memory state, Redis functions differently from other key value stores or databases that IT teams have used in the past. These differences can lead to performance issues or lost data in various parts of an application if not addressed and remediated.

Datadog’s eBook provides Redis users with an understanding of how Redis works and how this system functions differently from other key value stores and NoSQL databases. The top five Redis performance metrics are identified to explain:

How to access metric values
What values are indicative of performance problems
How to resolve and ultimately avoid Redis performance issues

Download a complimentary copy.

Try a free trial of Datadog to get turnkey visibility into Redis performance metrics and alerting for common issues.

About Datadog
Datadog unifies the data from servers, OS, databases, applications, tools and services to present a unified view of the infrastructure. These capabilities are provided on a SaaS-based monitoring and data analytics platform that enables Dev and Ops teams working collaboratively on the infrastructure to avoid downtime, resolve performance problems and ensure that development and deployment cycles finish on time.

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