How to Build a Powerful Status Page With Great Performance and Design

This tutorial shows how a lightweight and performant time-series database coupled with queued status checks and a simple UI are best for robust applications.

Highly available services that serve millions of requests rely on the visibility of the system status for customers and internal teams.

This tutorial shows how a lightweight and performant time-series database coupled with queued status checks and a simple UI are key ingredients for robust application monitoring.

Why build a status page for an application?

Even if we design the most reliable systems, incidents will occur for hard-to-predict reasons.

It's critical to provide as much information as possible to users, customers, and service teams.

The most convenient way to display this is through a status page.

Although the page's responsibility is to provide information, it can reduce the support team's load and eliminate duplicate support tickets.

Status pages are a crucial part of incident management, and usually, other teams enjoy benefits like client and service owners when they need to refer to SLAs.

In this tutorial, I'll show you how to build a simple yet powerful status page that scores well on performance and design.

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In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Today you're going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates. We gonna use Python OS remove( ) method to remove the duplicates on our drive. Well, that's simple you just call remove ( ) with a parameter of the name of the file you wanna remove done.

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc.. You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like __init__, __call__, __str__ etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Having to handle exceptions is common in Python and so is having to define your own. Yet, I have seen competing ways of doing so in various projects. The inconsistency comes from Exceptions being something that can easily be subclassed and extended, but also something that can be easily instantiated and used in their base form.