Operations | Monitoring | ITSM | DevOps | Cloud

For most of my career I’ve worked with health and wellness startups. Most of these companies have a wearable that tracks movement, heart rate, body weight or stimulates a body part. The common denominator between these apps is their use of sensor data to determine physiological progress an athlete is making. Problem is, your Bluetooth Low Energy (BLE) device does not have an internet connection and cannot send diagnostics anywhere if there are errors.

Between planning, triaging tickets, negotiating requirements with external stakeholders, and actually building software, it’s hard to take the time to make dashboards or even think about the most important metrics your team needs to track. To make it easier for you to get insights into your team effectiveness and project health, we made a few updates to Dashboards and Stats that you just might like.

Despite several widely acknowledged flaws, Python remains one of the most popular development languages worldwide. The sole fact that for years Python had two different and incompatible versions existing in parallel should have spelled the end for Python given the numerous alternatives available in the market. But Python overcame this conflict. Developers also criticized Python’s design and functionalities. Python is known to be slow and inadequate at dealing with memory-intensive operations.

A trace is the end-to-end journey of one or more connected spans and a span is an operation or “work” taking place on a service. So when it comes to debugging a performance issue, being able to pick out slow spans out of a line up is the fastest way to seeing the root cause and knowing how to solve it. Suspect Spans surfaces a list of spans that correspond to where the most time in a transaction is spent.