Peter Lawrey likes to inspire developers to improve the craftmanship of their solutions, engineer their systems for simplicity and performance, and enjoy their work more by being creative and innovative.
He has a popular blog "Vanilla Java" which has had over 3 million page views, is 3rd on StackOverflow.com for Java with over 10K answers, founder of the Performance Java User's Group with 900 members and is lead developer of the OpenHFT project which includes support for off heap memory such as embedded databases supporting billions of keys-values with 1 micro-second update latency, thread pinning and low latency persisted IPC (as low as 100 nano-seconds)
In many applications, there is a tension between how much you can log without slowing down your application, and how much information you would like to have.
Chronicle provided a number of solutions which allow you to record millions of events per second, with micro-second latencies in a persisted way without contributing to your garbage.
How does this simplify the design, help you increase the determinism and vertical scalability of your application?
After working with lambdas for the last 5 months, from a code base originally written in C#, a number of real life patterns and anti-patterns have become apparent.
What are some of the common patterns we used, and what are some patterns which needed to be avoided?