Jaana Dogan

If you are interested to learn about what and how Go generates machine code, this talk is for you. By learning more about the compilation, you can either avoid unnecessary hand-crafted optimizations or learn more about the compiler to become a contributor to the Go compiler.

Have you ever optimized some Go code to later realize Go compiler is already doing the same optimization automatically? Have you ever tried to understand what makes of of the Go compiler? Or, have you ever wondered how can you inspect machine code generated from Go source code? If you are interested to learn about what and how Go generates machine code, this talk is for you. By learning more about the compilation, you can either avoid unnecessary hand-crafted optimizations or learn more about the compiler to become a contributor to the Go compiler.

Complexity in coding and system design should be defeated until it is possible to do. Some problems are complex in nature and it is expensive to build and maintain solutions for problems in this category. Observability provides us tools to see our architectures from a different perspective. It is not just helping us to troubleshoot but also self-document our architectural decisions and help us to improve the most significant execution paths.

Complexity in coding and system design should be defeated until it is possible to do. Some problems are complex in nature and it is expensive to build and maintain solutions for problems in this category. Observability provides us tools to see our architectures from a different perspective. It is not just helping us to troubleshoot but also self-document our architectural decisions and help us to improve the most significant execution paths.

Agenda of the talk: - Give motivation why systems get more complex. - How to deal with complexity? - What else to do if complexity is in the nature of the problem? - Introduce critical path analysis as a solution. - Explain the organizational and technical challenges of critical path analysis. - Conclude by summarizing the pros/cons of critical path analysis.

The progression of microservices in the industry resembles me the way microservices progressed at Google. First, a common container format. Then, a way to express complicated systems in terms of containers. Then, tools to deploy them and services to schedule them. Then, core networking services to support the complicated networking requirements of our highly large systems with complex dependencies. Then, observability: collecting diagnostics data not just to recognize and debug production problems, but also to provide critical signals about usage to our highly adaptive and scalable environment.