In 2018, digital transformation ushered in a radical shift in how enterprises harness customer insights, technology capabilities, and rapid experimentation to drive revenue growth, profitability, and market leadership. Enterprises spent $1.3 trillion in 2018 on digital transformation technologies like public cloud platforms, microservices and containers, edge computing, machine learning, and artificial intelligence to improve customer experiences, business agility, and employee engagement.

If you’re a software developer, then you understand how vital application logging is in software development and a critical part of logging is something called logging levels. Log entries generally contain essential information—such as a timestamp, a message, and sometimes additional stuff like an exception’s stack trace. Those pieces of information are useful because they allow someone reading the log entry to understand how the application behaved in production.

The brand new Monitive platform is almost ready to be seen by the world, but just like any software development project, minor issues always surface that tend to push a release date back further and further. There’s always copy to be adjusted, links to be added, an icon that would improve clarity. Maybe a box is missing or the color of a button needs to change.

Time is running out to get your ticket to GrafanaCon LA, but you can still grab one of the last remaining seats. We’re really excited how the schedule has shaped up and hope you can join us!

Chances are you’ve heard of traditional credential-based attacks on Active Directory (AD) and cloud applications—brute force attacks, dictionary attacks, and keylogging, to name a few. There’s now another attack type you should familiarize yourself with: password spray attacks. In this blog, we’ll analyze why you should be wary of them and the best way to tackle them.

The Internet of Things offers tangible benefits, but businesses lack diagnostic tools that provide real-time visibility into IoT performance problems.

The open source revolution is back in full swing with the rise of Kubernetes. Flexibility and agility are the key factors to making the most of the cloud, multicloud, or hybrid cloud era. Kubernetes makes that easier by granting DevOps teams greater control across their infrastructure. But easier does not necessarily mean easy — there are still hurdles to overcome.

Despite decades of development, deep learning has been boosted by the increasing processing power of computers and the immense amount of data available, which has allowed it to obtain some achievements that were unthinkable years ago. Deep learning is at the heart of what we know today as artificial intelligence. However, like everything that is talked about a lot, deep learning has formed a series of myths that do not always obey reality.