In today’s complex software environments, ensuring that applications run smoothly and efficiently is more critical than ever. One of the key practices that developers and IT operations and DevOps professionals use to maintain the health and performance of their systems is application tracing. This blog post delves into application tracing, how it works, different types, and effective implementation.

Event streaming is a powerful concept that has gained significant traction in the areas of data processing and real-time analytics. This post discusses the basics: what event streaming is, examples, and uses. Additionally, the post explores how to implement event streaming, as well as the technologies and tools involved.

Containerization has deeply changed the way applications are built, deployed, and managed. Containers include both an application and its dependencies, enabling consistent and efficient deployment across diverse environments. However, as applications scale and become more complex, managing numerous containers manually becomes increasingly challenging. Container orchestration streamlines the deployment, scaling, and management of containerized applications.

Ensuring smooth transitions during application upgrades are important. Maintaining system consistency and stability with a database upgrade is paramount. Databases are complex systems with numerous stored procedures, each intricately linked to critical functionalities. Changes to these procedures during an upgrade could potentially disrupt overall system performance and negatively impact thousands of customers.

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.

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.

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.

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.

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 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.