The latest News and Information on Log Management, Log Analytics and related technologies.
Having visibility into your Java application is crucial for understanding how it works right now, how it worked some time in the past and increasing your understanding of how it might work in the future. More often than not, analyzing logs is the fastest way to detect what went wrong, thus making logging in Java critical to ensuring the performance and health of your app, as well as minimizing and reducing any downtime.
Untangling a chaotic mess can be daunting. And that’s exactly the problem Alain Adler, the Head of Engineering at BetterHelp, faced.
Continuous Integration and Continuous Delivery (CI/CD) delivers services fast, effectively, and accurately. In doing so, CI/CD pipelines have become the mainstay of effective DevOps. But this process needs accurate, timely, contextual data if it’s to operate effectively. This critical data comes in the form of logs and this article will guide you through optimizing logs for CI/CD.
Microservice architecture is widely popular. The ease of building and maintaining apps, scaling CI/CD pipelines, as well as the flexibility it offers when it comes to pivoting technologies are some of the main reasons companies like Uber and Netflix are all in on this approach. As the amount of services in a microservice architecture rises, complexity naturally also rises.
The modern enterprise has expanded its reach by using the power of cloud computing. However, with that power comes complexity in leveraging the multiple platforms needed to provide rich functionality. To achieve a seamless integration that involves multiple cloud infrastructures you need insightful and actionable data. You also need the right team to bring the clouds together in a seamless, effective, and efficient manner.