Operations | Monitoring | ITSM | DevOps | Cloud

Cloud is driving the way modern software is being built and deployed. At the forefront of this revolution is AWS, holding a whopping 33% of the cloud services market in Q1 2019. Considering AWS had a seven-year head start before its main competitors, Microsoft and Google, this dominance is not surprising. AWS offers, by far, the widest array of fully evolved cloud services, helping engineers to develop, deploy and run applications at cloud scale.

With a shift toward the Internet of Things, where always-on connectivity is paramount, digital experience monitoring (DEM) is a transformational way of looking at application and end-user monitoring. DEM asks more than whether you have a slow website, it looks at how every step in the user’s experience performs at a granular level. This discipline measures the website’s response to the user’s needs.

When we think of an apprentice, we think of one of two things; the TV show ‘The Apprentice’ with Lord Sugar or, someone who gets stuck with the job of making the tea and coffee. These are pretty accurate, but neither of these is the actual truth in today’s world.

You probably use many tools to get through the day. Do you ever wonder what tools get other people through their days? In our Tools This Engineer Uses series, we explore the routines, systems, and tools your peers rely on to solve problems and accomplish goals.

When troubleshooting an issue with logs, it’s often fairly easy to find an important log; for example, an exception is logged and an alert is fired. Once you find an exception in the logs, the trickier part can be understanding why the exception was thrown. One common approach to this problem is looking at the surrounding logs. Logs are typically in chronological order, so if you see an exception, look at the logs’ lines from just before the exception occurred.

On June 20 we have released the 3rd update for EnterpriseAlert 2019. Don’t get confused by the version number, 8.2.0 would better be 8.3.0, but that’s the way it is. Here is a very short EA 2019 release history for CY 2019.

When I browse Stackery’s documentation and blog, I see some great writing that I know not everyone has read. Check out these great articles essential to growth as a developer.

At Datadog, we operate 40+ Kafka and ZooKeeper clusters that process trillions of datapoints across multiple infrastructure platforms, data centers, and regions every day. Over the course of operating and scaling these clusters to support increasingly diverse and demanding workloads, we’ve learned a lot about Kafka—and what happens when its default behavior doesn’t align with expectations.

It all started with monolith architecture; business logic, user interfaces, and data layers were stored in one big program. As tightly coupled applications, a simple update to the program meant recompiling the entire application and redistributing the program to all users. That led to the difficulty of maintaining consistent program versions and distribution across all clients in order to ensure stability and alignment. This made the monolith approach inefficient and cumbersome.