Book Image

The Complete Rust Programming Reference Guide

By : Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger
Book Image

The Complete Rust Programming Reference Guide

By: Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger

Overview of this book

Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: • Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta • Hands-On Data Structures and Algorithms with Rust by Claus Matzinger
Table of Contents (29 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Approaches to logging


When integrating logging in an application, we need to decide what information to log and how granular it should be. If there are too many logs, we lose the ability of easily finding relevant information in the sea of noise and if there's not enough log messages, we risk missing that one important event. We also need to think about how to organize information in our log message so that it becomes easier to search and analyze it later. These questions lead to logging frameworks that are broadly divided into two categories: unstructured logging and structured logging.

Unstructured logging

The usual way to approach logging is the practice of logging events as plain strings and shoving any fields from required values into the log message by converting them into strings. This form of logging is called unstructured logging as the information in the log message doesn't have any predefined structure or order. Unstructured logging serves well for most use cases, but it has its...