As organisations strive to deliver seamless user experiences, maximise operational efficiency, and maintain a competitive edge, the need for comprehensive Application Performance Monitoring (APM) tools becomes increasingly evident. APM tools offer invaluable insights into the performance and behaviour of applications in real-time. They go further than the conventional monitoring approach by providing a holistic view of the entire stack, encompassing servers, databases and user interactions.

Application performance monitoring (APM) tools have become a fundamental part of many organisations that wish to track and observe the optimal functioning of their web-based applications. These tools serve to greatly simplify the process through automation and allow teams to effectively collaborate to maximize efficiency, enabling you to reach the root cause of an issue before it reaches your customers.

The majority of users continually depend on a variety of web applications to meet their everyday needs, so a business’s success is now often proportionate to the success of its application performance. As a result, the importance of using an appropriate APM solution has become even greater to businesses globally. Application Performance Monitoring (APM) still continues to grow in popularity and is now considered a must for observing the health and performance of your organization's applications.

Whatever the size of your network, as an engineer you will often notice a significant amount of log data being generated. This data will require centralizing for further analysis and management, which can be particularly challenging if you have varying log formats, such as plain text or HTML.

Monitoring the key metrics of your application’s performance are essential to keep your software applications running smoothly as one of the key elements underpinning application performance monitoring. In this article, we will cover many of the key metrics that you should strongly consider monitoring to ensure that your next software engineering project remains fully performant.

When focusing on application performance monitoring (APM), there are currently many options to select from. With many of the tools available offering similar features, it can often be challenging to make an informed decision. One tool that appears to be on almost every list of ‘the best APM tools’ is Datadog.

In the context of application performance monitoring (APM) and observability, traces and spans are fundamental concepts that help users to track and understand the flow of requests and operations within a system. They are essential in assisting users to identify bottlenecks, troubleshoot issues, and optimize application performance.

MLOps stands for Machine Learning Operations. MLOps refers to the set of practices and tools that facilitate the end-to-end lifecycle management of machine learning models, from development and training to deployment and monitoring. The primary objective of MLOps tools is to address the unique challenges associated with deploying and managing machine learning models in real-world scenarios.

In this guide, we will compare two of the leading data visualization tools based upon open-source software that are available for use for metrics, traces and log analysis. To allow new users to know exactly which solution may be best suited to their needs, we wanted to explore in more depth a comparison between OpenSearch Dashboards and Kibana across various aspects in our latest guide covering the differences between leading open-source software.

Container monitoring refers to the process of monitoring and managing containers deployed within a containerization platform, such as Docker or Kubernetes. As containerization has become increasingly popular in software development and deployment, monitoring and managing containerized environments has become increasingly important.