Exception monitoring in Java plays a vital role in Java application performance monitoring by providing real-time insights into the health and stability of the application. Java is now the backbone of many critical and complex business applications in sectors such as banking, healthcare, finance, retail, and e-commerce. The complexity of these systems is also compounded by the fact that they involve distributed Java microservices that communicate across various layers.

Interaction to Next Paint is the newest of Google’s Core Web Vitals. The three metrics that make up the CWVs are Google’s attempt at defining proxy metrics for measuring things they believe are critical to a good user experience on the web. The three metrics are: Debugging and fixing these metrics can be quite complicated. In this post, I’m going to walk through how you can use Honeycomb for Frontend Observability to debug INP, which was just promoted to a stable Core Web Vital in March.

Another huge release is heading your way with our new Image Backup engine, Documentation upgrades, new automation scripts, MDM enhancements, and much more!

Organizations need highly scalable compute capacity in the cloud to handle fluctuating workloads. This ensures they can meet peak demand without over-provisioning resources or incurring unnecessary costs during low activity periods. Amazon EC2 offers one of the most flexible, on-demand infrastructures that can be scaled to meet business needs. Yet, it isn’t suitable for everyone. In this guide, we’ll explore why that is and share the best EC2 alternatives to consider. But first, a quick recap.

Have the concepts of “work” and “workplace” ever seen as much change as they have in the past five years? These changes have driven a corresponding shift in employee attitudes toward work. The Great Resignation may have been the first highly visible indication that something organizations and workers had never experienced was afoot. It laid to rest any notion that every employee was grateful to be tethered to a desk in a locked-down location from nine to five.

In today’s fast-paced digital landscape, enterprise data stands as both a critical asset and a potential liability. With data volumes expanding at an annual rate of 28% while budgets increase by only 7%, organizations face mounting challenges. The unpredictable nature of data value complicates decisions on what to store and where. Moreover, the rise of connected devices and evolving security threats further exacerbate the situation.

In today’s rapidly evolving networking landscape, enterprise networks are more complex than ever before. Network organizations must manage traditional Layer 2 networks while adopting cutting-edge software-defined technologies such as SD-WAN, SDDC, and SD-LAN. Managing these globally distributed, multi-dimensional networks is no small feat.

In today’s complex environments such as cloud-native technologies, containers, and microservices-based architectures, reliable log monitoring is crucial for keeping your systems secure and resilient. Continuous monitoring enables organizations to stay in-control, providing proactive insights into system health and performance. With platforms like AWS, GCP, and Azure churning out massive amounts of logs, it’s easy to get overwhelmed.

Logs play a critical role in monitoring your applications and systems in terms of health, system behavior, and problem diagnosis. However, logs can assuredly bring value only if they are structured and well-formatted. Effective log formatting can help identify an issue to fix on time rather than having to sift through unorganized, hard-to-read logs. In this blog, we delve into 7 super-effective practices for production logging to help you maximize your log analysis capabilities.