Talks

For years Google has consistently been able to cut down multiple percentage points in their fleet-wide resource usage every quarter, using techniques described in their “Google-Wide Profiling” paper. Ad-hoc profiling has long been part of the developer’s toolbox to analyze CPU and memory usage of a running process, however, through continuous profiling, the systematic collection of profiles, entirely new workflows suddenly become possible. Matthias and Kemal will start this talk with an introduction to profiling with Go and demonstrate via Conprof - an open-source continuous profiling project - how continuous profiling allows for an unprecedented fleet-wide understanding of code at runtime. Attendees will learn how to continuously profile Go code to help guide building robust, reliable, and performant software and reduce cloud spend systematically. ...

For years Google has consistently been able to cut down multiple percentage points in their fleet-wide resource usage every quarter, using techniques described in their “Google-Wide Profiling” paper. Ad-hoc profiling has long been part of the developer’s toolbox to analyze the CPU and memory usage of a running process. However, through continuous profiling, and the systematic collection of profiles, entirely new workflows suddenly become possible. The presenter will start this talk with an introduction to profiling applications, and demonstrate how one can practice it using open-source continuous profiling tools, and how continuous profiling allows for an unprecedented fleet-wide understanding of code at production runtime. ...

In modern days, we run our applications as loosely coupled micro-services on distributed, elastic infrastructure as (mostly) stateless workloads. Under these circumstances, observability has become a key attribute to understand how our applications run and behave in action, in order to provide highly available and resilient service. There exist several observability signals, such as “log”, “metric”, “tracing” and “profiling” that can be collected from a running service, which we can also call pillars of observability. Using these signals, we can create real-time, actionable alerts, create panels where we can monitor applications closely, and perform in-depth analysis to find the root of the systems’ failures. Within the Go and CNCF ecosystem, there are a variety of tools that can collect and make these observable signals useful. ...

Thanos is an open-source, CNCF’s Incubated project that horizontally scales Prometheus to create a global-scale highly available monitoring system. It seamlessly extends Prometheus in a few simple steps and it is already used in production by hundreds of companies that aim for high multi-cloud scale for metrics while keeping low maintenance cost. During this talk, core Thanos (and Prometheus) maintainers, will briefly introduce basic ideas behind Thanos and deployment models and use cases. After that, to satisfy more experienced users, they will explain more advanced concepts, tips for running on the scale, and the latest shiny usability improvements. Thanks to the growing community there is much to talk about! ...

Live Website: The Zen of Prometheus In modern days, we run our applications as loosely coupled microservices on distributed, elastic infrastructure as (mostly) stateless workloads. Under these circumstances, observability is the key to understanding how our applications run and behave in action to deliver highly available and resilient service. Prometheus is born in such an atmosphere as a solution to satisfy the observability needs of the cloud-native era. Among many other observability signals like logs and traces, metrics play the most substantial role. Sampled measurements observed throughout the system are crucial for monitoring the health of the applications and they enable real-time, actionable alerting. Although the tools in the Prometheus ecosystem make life a lot easier, there are still numerous possibilities to make mistakes or misuse them. ...