Build Stuff 2018

Understanding failures or latencies in monoliths or small systems usually starts with looking at a single component in isolation. Microservices architecture invalidates this assumption because end user requests now traverse dozen of components and a single component simply does not give you enough information: each part is just one side of a bigger story.

In this talk we’ll look at distributed tracing which summarizes all sides of the story into a shared timeline and also distributed tracing tools like Zipkin, which highlights the relationship between components, from the very top of the stack to the deepest aspects of the system.

We usually think of monitoring as something the Operations team will take care of. In a "monolithic" system that might be enough.
But we like to distribute our systems. We deploy microservices with persistent queues and automated retries. We allow them to tolerate failure, at least for short periods of time. Sometimes it may seem everything is running OK. No heavy load, no memory or CPU surges, no immediately observable slow-downs. But in fact the system may not be functioning and effective performance is degrading. Messages are piling up in queues. Business SLA's are starting to get breached. With distributed systems, we need to do more than basic monitoring.
Let's talk about how we can do a better job at keeping the lights on and ensuring our systems are functioning as designed.
I'll introduce various aspects of monitoring and the things we need to think about when writing code. I'll show how you can optimize your distributed systems and find performance bottlenecks. You'll discover how you can win if you give monitoring a bit more love :-)

Serverless introduces a number of challenges to existing tools for observability, we need to adapt our practices to fit this new paradigm. In this talk we will see how you can implement log aggregation, tracing and correlation IDs for a serverless application.