Raja Sambasivan (Tufts University)- Toward understanding and efficiently observing microservices

The microservices architecture is a commonly used paradigm for building distributed applications. Many small software services, each providing different functionalities, interact to provide high-level application behaviors. This paradigm has many benefits: it enables fine-grained scaling, it facilitates’ development teams’ independence, and it aligns with the breakdown of Moore’s law, which incentivizes smaller compute units. Unfortunately, it also has one well-known drawback—understandability or observability. End-to-end behaviors in microservices applications are very challenging to reason about because they result from myriad interactions within and among services. Though there is opportunity for research to help, a lack of real-world data about microservice deployments depresses opportunities to provide value.

In this talk, I will discuss our efforts to characterize a large cloud providers’ microservice deployment. I will also discuss one key challenge our studies revealed—the tension between the desire for deep observability and immense instrumentation exhaust—and our efforts to address it via a framework that automatically chooses which logging points should be enabled at any time to provide visibility into performance problems.