As organizations continue to operate in an increasingly digitized fashion, ensuring network uptime and performance only keeps getting more critical. Network performance issues and downtime aren’t just a concern for network teams, they’re critical to the entire business. Network downtime is costly.

Written by John Stimmel, Principal Cloud Specialist Account Executive, LogicMonitor It’s common knowledge that Kubernetes (commonly referred to as “K8”s) container management and orchestration provide business value by enabling cloud-native agility and superior customer experiences. By their nature, the speed and agility of Kubernetes platforms come with complexity.

In today's cloud-centric landscape, managing and optimizing cloud resources efficiently is paramount for cloud engineers striving to balance performance and cost-effectiveness. By leveraging solutions like Tines and Elastic, cloud engineering teams can streamline operations and drive significant cost savings while maintaining optimal performance.

In the first part of this series, we toured performance APIs in Node.js. We discussed the capabilities of APIs and how they can diagnose slowdowns or network issues in your Node application. Now, in this concluding segment, we will embark on a practical journey, applying these performance hooks in a real-world scenario. You will understand how to effectively use these tools to monitor and enhance your application's performance. Let's dive in and see these concepts in action!

Starting today, Checkly users can send their traces from synthetics checks to Coralogix to view in-depth synthetic user data along with back-end APM based tracing. This gives SRE’s and Operations engineers a new insight into how the system is responding to automated synthetic tests of your service. For Checkly users, integrating with Coralogix data means it’s easy to correlate end-to-end user experience with backend performance, and track poor performance to its root cause.

There is an immense amount of IT and security data out there and there’s no sign of slowing down. Our customers have told us they feel like they’re drowning in data. They know some data have value, some don’t. Some might have value in the future. They need some place cost-effective to store it all. Some for just a short while, some for the long haul. But they’re not data engineers. They don’t have the expertise to set up and maintain a traditional data lake.

For SaaS platforms, utilizing observability is crucial, as it’s vital for these companies to deeply understand their users' experience and the root cause of any issues. Observability involves leveraging the appropriate tools and processes in place to effectively track, examine, and troubleshoot the performance and behavior of a system, even if you can't directly see what's happening inside it.