In today’s digital age, mobile applications are essential for large enterprises to connect with customers and drive growth. However, even the most meticulously tested apps can experience outages, leading to significant consequences for both users and the organizations behind them. This article explores the impact of unforeseen downtime, the repercussions on end users and company reputation, and how tools like LaunchDarkly can help alleviate these challenges. Learn how enterprises can uphold application reliability and ensure customer satisfaction amidst unexpected disruptions, leveraging Observability tools with the help of Vscetpre and LaunchDarkly.

Organizations invest significant time, often months or even years, into modern application development life cycles. However, deployment can feel like a pivotal moment. While many Continuous Integration/Continuous Deployment (CI/CD) practices aim to simplify and reduce the stress of deployment by making it a regular occurrence, it can still pose substantial challenges and lead to various issues.

If you have a chance to attend any presentation or public seminars from the APM vendors, you may come across some demonstrations of how easily to jump from trace to log or log to trace to diagnose a slow API call. This is one of the key differentiation of using a siloed approach for monitoring vs true full stack visibility. Often times, the technical details and prerequisites of how to achieve this are omitted from those overview demos. Today I am going to take a more detail discussion of how to ensure your application can achieve the log to trace correlation. We use DataDog as the example monitoring backend in this exercise.