With build-or-buy decisions, it often comes down to an all-in-one platform or a mixture of best-of-breed technologies. With open-source technology companies can actually get the best of everything. So, why not roll your own platform based on top-notch technologies? The real question is whether enterprises can afford to. Open-source software is free to use, but teams have to invest quite a bit in selecting, introducing, using, and maintaining these technologies.

AI is everywhere. Except in many enterprises. Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail, and for the few models that are ever deployed, it takes many months to do so. While AI has the potential to transform and boost businesses, the reality for many companies is that machine learning only ever drips red ink on the balance sheet.

With the increase in open-source software tools, developers have become more powerful. Open Source refers to an openly distributed code which allows users to inspect, modify and enhance it. It includes a license that allows users to utilize the source code and you can also modify and share under defined terms and conditions.

In this How-To, we’re going to look at a specific Catchpoint synthetic monitor that helps you analyze the health of systems built around the Internet of things (IoT). Now, IoT is obviously a huge category, so in this case, we’re going to look at systems that utilize the Message Queuing Telemetry Transport or MQTT for short.

Security is an essential part of any modern IT foundation, whether in smaller shops or at enterprise-scale. It used to be sufficient to implement rules-based software to defend against malicious actors, but those malicious actors are not standing still. Just as every aspect of IT has become more sophisticated, attackers have continued to innovate as well. Building more and more rules-based software to detect security events means you are always one step behind in an unsustainable fight.

According to the Association of Certified Fraud Examiners, the money lost by businesses to fraudsters amounts to over $3.5 trillion each year. The ACFE's 2016 Report to the Nations on Occupational Fraud and Abuse states that proactive data monitoring and analysis is among the most effective anti-fraud controls.

Zero Trust security. Some would say it’s the latest and greatest buzzword and this disposition is understandable given the amount of jargon introduced into the Information Technology market each year. With vernacular being used interchangeably like “AI,” “Machine Learning,” and “Deep Learning,” these words get stripped of their real significance.