We now have lots of “tools” for operations in cloud-native. Yet they all seem to suffer from the impact of single POV. And at the same time, we have more complexity, in infrastructure with the adoption of orchestration, cloud elasticity, microservices and FaaS. Piled on with heavily request-driven models, the old style of reacting to anomalies and headaches fails.
With RED, unlike the modern belief in metrics, your architecture is watched from aspects of multiple dimensions. You receive alerts and indications not just from anomalies, but also from headache alerts. By seeing multiple dimensions of concerns, be they failures in service or activity to close to the edge of capability, these combined monitors and deep-dive, focused access get you to your root cause faster, with less false positives and quicker resolution.
Thus, we need an understanding of RED, designed to meet the precise conditions now prevalent in our applications.
RED clearly has advantages over competing models (Golden Signals and USE) specifically with respect to DevOps models (and Devs). Through a deep dive into what this multi-dimensional problem AND multi-dimensional approach to resolution will help reduce the production scale and fail panics we see in the industry.
So RED gives you the framework to build alerting, monitoring and analysis into a flexible structure to meet the emerging needs of services-based cloud-native architectures as well as give you the capability to grow as your environment scales.
This talk will dive into RED, what it is and how it fits in the modern world of services and explore how RED can expand to deliver faster Mean Time to Recognize and Mean Time to Respond.