AWS re:Invent 2015 | (BDT312) Application Monitoring: Why Data Context Is Critical

Опубликовано 12 октября 2015, 18:00

The move towards microservices in Docker, EC2 and Lambda points to a shift towards shorter lived resources. These new application architectures are driving new agility and efficiency. But they, while providing developers with inherent scalability, elasticity, and flexibility, also present new challenges for application monitoring. The days of static server monitoring with a single health and status check are over. These days you need to know how your entire ecosystem of AWS EC2 instances are performing, especially since many of them are short lived and may only exist for a few minutes. With such ephemeral resources, there is no server to monitor; you need to understand performance along the lines of computation intent. And for this, you need the context in which these resources are performing.

Join Kevin McGuire, Director of Engineering at New Relic, as he discusses trends in computing that we’ve gleaned from monitoring Docker and how they’ve helped us rethink how we monitor and analyze AWS. We’ll dive into the case for how contextual information like instance size, AMI, availability zone and tags can be used to drive an elevated understanding of transient infrastructure behavior and how it contributes to application performance. We’ll show how integrating status information gives you a more accurate view of EC2 lifecycle and health. And finally, how that information powers the ability for you to analyze and display that performance information in new and powerful ways.