Application Performance Monitoring (APM) is great for tracking the health and performance of your software tool. APM helps you understand what's happening inside your application by monitoring various parameters such as CPU/memory stress, internal network throughput, and more. However, mixing in log analytics can take your APM game up a notch. Almost all software tools generate logs when they run.
Many renowned businesses use the well-known web framework Flask. Flask is quite famous among developers for making small and full-fledged applications. It is known for being a straightforward framework to learn hence why it is popular among established organizations. Monitoring your Flask application can be a challenge. Many important operations are happening inside of them, and if anything goes wrong, it can cause some damage.
In this era where applications are taking over the world, delivering the service to your customer with scalability and security is of the utmost importance. The software delivery platform helps to manage the data flow, traffic management, and security of the data from both sides of the application. If you are studying software delivery platforms, then most of you must have heard about the Codefresh software delivery platform for continuous integration and continuous deployment of the application.
Nowadays, most organizations are highly dependent on APM technology, but many are shifting to automated monitoring, which is generally referred to as AIOps technology. AIOps is considered the future of operations management for organizations. As we already know, AI is considered the next revolution in the history of mankind. AIOps uses advanced AI for supporting day-to-day operational tasks so the employees don’t need to hassle for no reason.
In today’s world, a significant fraction of a software business’s reputation depends on its web application and its speed. It all comes down to how fast your server responds to client requests (assuming your application is reliable and reasonably user-friendly). Therefore, you could argue that the server endpoint is the centerpoint of all the server-side action — the operations here primarily determine the performance of your application.
Microservices have grown to become one of the most optimal alternatives to monoliths. However, just building your app and releasing it to the public isn’t everything. Monitoring microservices is as important as building and releasing them. You need to maintain it to resolve issues that may occur and also introduce new features from time to time.
Software applications have become crucial for business growth and success in today's world. However, as businesses become increasingly competitive, the necessity to provide top-notch software applications is also increasing. Additionally, as organisations gravitate towards developing extensive, feature-rich applications, they are witnessing an increase in software complexity – that can often cause things to get out of hand very quickly.
OpenTelemetry is a free and open-source software initiative with the objective of supplying software developers with the means to create distributed systems. OpenTelemetry was developed by engineers at Google, and developers have the ability to utilize it to create a standard foundation for the construction of distributed systems. The goal is to enable developers to write code once and then deploy it in any location of their choosing.
In today’s digital world, users expect to have a seamless experience in their day-to-day applications. To achieve such reliability and stability in our application, information about the health and performance of an application has become necessary for developers to gain insights and fix bottlenecks to provide a seamless user experience. One of the best ways to gain such insights into an application is to use a monitoring system.
Telemetry data is a powerful tool for understanding the behavior of complex systems. OpenTelemetry provides a platform-agnostic, open-source way to collect, process, and store telemetry data. This post explores the OpenTelemetry collector architecture, specifically focusing on the Collectors component. We'll look at how collectors work and how they can be used to process telemetry data from any system or application. We'll also discuss some benefits of using OpenTelemetry for your telemetry needs.
