The process of identifying, analyzing, and solving IT-related problems, in the system running the application.

when your computer is sluggish and processes tasks at a reduced speed.

A condition in which a chunk of memory that's no longer needed is not released.

two different categories: urgent and important. Tasks can be important and urgent, urgent but not important, not urgent and important and not urgent and not important.

transforms your Python code into high-speed machine language, by way of a just-in-time compiler or JIT.

It is a sequential search method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched.

Process Monitor, Linux Observability Tools, Utilization Saturation and Errors (USE) Method, Activity Monitor, Performance Monitor and Process Explorer.

Stores all the information related to the crash so that we, or someone else, can debug what’s going on.

The best way to do this is to compare the task that you're trying to do with similar tasks that you've done before. To make a better estimate of a bigger than average project, you'll want to chop it up. Split the task into smaller steps. Compare each step to a similar task that you've done in the past and assign an estimated amount of time to each step based on that. Putting all the pieces together will take additional time. Finally, take the sum of your previous estimates and multiply it by a factor. For example, if the last time you did this exercise, it took you three times longer to complete the task than you'd planned, go ahead and multiply your estimation by three.

occur due to mistakes in the source code, such as spelling and punctuation errors, incorrect labels, and so on, which cause an error message to be generated by the compiler.

It is a Searching technique which is applied on a sorted list by repeatedly dividing the search interval in half.

code that's readable, easy to maintain and easy to understand, which would reduce the number of bugs in the code.

It is a Python library with tools to profile an entire Python application.

Communication is key. Try to be clear and upfront about when you expect the issue will be resolved, and if for any reason the issue isn't solved by then, explain why and what the new expectation should be.

The short version of it is that you want the computers you care about to send their data to a centralized location that aggregates all this information. And then you want to be able to look at both the information yourself, and trigger alerts when the values are not within acceptable range.

a software bug that seems to disappear or alter its behavior when one attempts to study it.

lists, tuples, dictionaries, and sets

It is the process of marking the data packets and assigning higher priorities when being sent over the network.

how much data can be sent or received in a second. This is effectively the data capacity of the connection.

The checkpoints in the code that let code run until a certain line of code is executed.

A way to verify if the problem exists or not.

some reasons include: too many applications configured to start on boot, a bug in the program that uses more RAM over long periods of time, reading from the network is notably slower than reading from disk, hardware failures, malicious software and malicious browser extensions.

It is a detailed document of an issue which includes the root cause and remediation. It is effective on large, complex issues.

it's used in Python to add extra behavior to functions without having to modify the code.

allows you to create programs that can run concurrently (bypassing the GIL) and use the entirety of your CPU core.