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The Business Case for OpenTelemetry - APM for Modern Applications

DevOps professionals know that ensuring optimal application performance is paramount. More and more customers and prospects interact with companies online, and any hiccup can impact your bottom line. What’s more, companies continue to leverage cloud-native apps for improved flexibility and resource optimization. All of which means that Application Performance Monitoring (APM) tools need to evolve.

Getting Started With Azure Serverless

Serverless computing represents a paradigm shift in how we build, deploy and scale cloud applications. By decoupling infrastructure and server management from code development, developers are free to put a single focus on fine-tuning code in app development. The era of serverless computing puts innovation at center stage and removes the traditional constraints of server management.

A Basic Introduction to OpenTelemetry Python

Think of a tool that simplifies application monitoring and helps developers and staff trace, collect logs and measure performance metrics. That is what OpenTelemetry Python provides. OpenTelemetry (OTel) Python acts as a guiding light, offering insights into the behaviors and interactions of complex, distributed systems and enabling a deeper understanding of performance bottlenecks and system dependencies. The significance of OTel lies in its pivotal role in modern software development.

An Introduction to OpenTelemetry JavaScript

Monitoring and observing application performance is a cornerstone for maintaining robust and efficient systems in the ever-evolving development landscape. One key player in this domain is OpenTelemetry. This post provides a comprehensive tutorial and unpacks what OpenTelemetry is, its applications and integration into the JavaScript ecosystem.

ML and APM: The Role of Machine Learning in Full Lifecycle Application Performance Monitoring

The advent of Machine Learning (ML) has unlocked new possibilities in various domains, including full lifecycle Application Performance Monitoring (APM). Maintaining peak performance and seamless user experiences poses significant challenges with the diversity of modern applications. So where and how does ML and APM fit together? Traditional monitoring methods are often reactive, resolving concerns after the process already affected the application’s performance.

Syslog Tutorial: How It Works, Examples, Best Practices, and More

Syslog is a standard for sending and receiving notification messages–in a particular format–from various network devices. The messages include time stamps, event messages, severity, host IP addresses, diagnostics and more. In terms of its built-in severity level, it can communicate a range between level 0, an Emergency, level 5, a Warning, System Unstable, critical and level 6 and 7 which are Informational and Debugging. Moreover, Syslog is open-ended.

SQL Performance Tuning: 7 Practical Tips for Developers

Being able to execute SQL performance tuning is a vital skill for software teams that rely on relational databases. Vital isn’t the only adjective that we can apply to it, though. Rare also comes to mind, unfortunately. Many software professionals think that they can just leave all the RDBMS settings as they came by default. They’re wrong. Often, the default settings your RDBMS comes configured with are far from being the optimal ones.

How to Rescue Exceptions in Ruby

Exceptions are a commonly used feature in the Ruby programming language. The Ruby standard library defines about 30 different subclasses of exceptions, some of which have their own subclasses. The exception mechanism in Ruby is very powerful but often misused. This article will discuss the use of exceptions and show some examples of how to deal with them.

Python Garbage Collection: What It Is and How It Works

Python is one of the most popular programming languages and its usage continues to grow. It ranked first in the TIOBE language of the year in 2022 and 2023 due to its growth rate. Python’s ease of use and large community have made it a popular fit for data analysis, web applications, and task automation. In this post, we’ll cover: We’ll take a practical look at how you should think about garbage collection when writing your Python applications.