Observability
In control theory, observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs.
Today, in software engineering, observability is a set of practices to understand what your systems are doing. There are three ways that are often referred too in observability. These are:
- logging
- metrics
- tracing
At QCon, several talks will discuss the practices of observability and running complex distributed systems. Below are a few to watch for.
Position on the Adoption Curve
Presentations about Observability
Microservices & Scaling of Rational Interactions
Observability and Emerging Infrastructures
How to Build Observable Distributed Systems
The Present and Future of Serverless Observability
How Events Are Reshaping Modern Systems
Monitoring Cloud Native applications with Prometheus
Attack Trees, Security Modeling for Agile Teams
Observable JS Apps
Testing Observability
Debugging Microservices Applications
Observability Panel
Observability Panel
Observability Panel
Observability Panel
Observability Panel
Developing a Monitoring Philosophy
Testing Microservices: Contracts, Simulation and Observability
Testing Microservices: Contracts, Simulation and Observability
Interviews
The Present and Future of Serverless Observability
What is the focus of your work today?
At the moment, I’m building the backend services for a real-time multiplayer game on mobile, including an inhouse networking stack that will be deployed globally and supports both TCP and reliable UDP. We’re still doing a lot of tuning, and would put an early alpha build in front of users for external validation on our networking stack as well as general gameplay and meta design, and to get a better idea on the game’s potential to be the next big hit.
What’s the motivation for this talk?
I have worked extensively with AWS Lambda the last 2 years, especially during my previous job as architect at a social networking startup called Yubl, where we learnt a lot about operating a serverless architecture in production and many of the operational challenges that need to be addressed, as the technology itself is still very much rough around the edges.
See more interviews
