It is based on the 4-series log Streams and Tables in Apache Kafka.

A note about general concepts of high performance: both throughput and response time.

The Logback Project has three modules: logback-core, logback-classic and logback-access. The logback-core has the core functions for other two modules. The logback-classic implements the SLF4J API. The logback-access integrates with the Servlet containers to provide HTTP-access log functionality. Logback is fast, native SLF4J, well-documented and dynamic configurable.

Ch3 covers functional data strucure: what structures, how to define and how to use them. Contents include functional data types, pattern matching and pure function generalization. 1 Functional Data Structure A pure function must not change data in place or perform other side effects. Functional data structure are by definition immutable. An empty list is immutable, so is the result of two lists combined. 1 2 3 4 5 6 7 8 9 sealed trait List[+A] case object Nil extends List[Nothing] case class Cons[+A](head: A, tail: List[A]) extends List[A] object List { def apply[A](as: A*): List[A] = if (as.

This part covers the ZIO tests. It is based on the ZIO document of Data Types. A small number of data types help you develop applications in a functional approach. All the data types are just values that

• describe effectful or asynchronous actions
• manage resources
• are used to make concurrent programming safe and simple.

This note is based on the ZIO Logging doc. It supports context across fibers. It comes with a console implementation and a SLf4j intergration. The code is not elegant and the sample code is a mess.

This part covers the ZIO tests. It is based on the documents of, Testing Effects, Testing Use Case and ZIO test effects. ZIO makes tests first-class objects in that tests are values that can be passed, transformed and composed. ZIO tests are effects.