.NET 4 Logging Done Right: An Opinionated Approach Using Serilog 2
|
Establish a great logging framework for all of your applications using Serilog as a foundation, then get them written to database sinks (SQL Server and Elasticsearch specifically), and explore log data using custom and in-the-box tools.
Establishing a foundational framework for logging can save hours in troubleshooting and provide valuable insights to both utilization and performance within all of your applications.
In this course, .NET Logging Done Right: An Opinionated Approach Using Serilog, you will learn about 4 primary “things” (usage, performance, errors, and diagnostics) to log and how to log them. You will also learn how to globally write these log entries without needing to inject logging code everywhere in an application – so developers can focus on business logic, not logging code.
Global logging will be shown with all flavors of
Author Name: Erik Dahl
Author Description:
Erik Dahl has been developing software and architecture for 20+ years, mostly doing in-house development for his employers. His recent work has included a multi-tenant B2B implementation and self-registration B2C implementation for Duende IdentityServer, upgrading legacy ASP.NET websites from server-side technologies to a client/server mix and adopting TypeScript, building Web APIs as the back end for mobile and web applications, and finding ways to modernize existing applications and make them … more
User Reviews
Be the first to review “.NET 4 Logging Done Right: An Opinionated Approach Using Serilog 2”
Related Products
Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Introduction to Docker
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
Object-Oriented Programming in Python
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Data Types in Python
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Data Structures and Algorithms in Python
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
Intermediate Python
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
There are no reviews yet.