Eric Wright of VMTurbo wrote about the death of root cause analysis (RCA) with the rise of microservices. I take exception to this, as microservices aren’t really all that new. Even what’s being called “serverless computing” isn’t particularly new. However, that’s a discussion for another time. The point of RCA is to find the real reasons for failures. I don’t see how using microservices changes this. All we’ve done is add more layers to delve through to find the true root cause of a problem.
IT as a Service
IT as a Service (ITaaS) covers private clouds, hybrid clouds, and on-premises clouds, as well as cloud management, including performance management offerings used to create and manage these entities. Consider this IT consumption as a utility. (Read More)
This topic explores Infrastructure as a Service (IaaS) private and hybrid cloud offerings, Platform as a Service (PaaS) private and hybrid cloud offerings, and Software as a Service (SaaS). It also investigates emerging areas such as Desktop as a Service (DaaS), Storage as a Service, and Applications as a Service.
The key areas covered include enterprise applications and use cases that are appropriate for private and hybrid clouds, and how consumers and vendors should select cloud management offerings they will use to manage the various types of cloud services and the journey to the cloud: from A to Z and all points between.
Data drives the modern business. It drives the modern development process. And it drives IT operations analytics in the NOC and the SOC. This raises the questions “Who owns all this data? Do data sovereignty rules apply?” Data is everywhere, and it is used in many ways. In many cases, the same data is used in multiple ways by distinctly different groups, working methods, and ivory towers.
Any part of any infrastructure, application, or cloud is data. Data is used by applications, and myriad data is presented to IT organizations for their use, edification, insights, and more. But what really is this data? Can we classify the types of data in some way? Data classifications should not be just “structured” and “unstructured”; they must go deeper than that. To understand how IT operations analytics (ITOA) can act on data, we first need to classify data into something we can comprehend. ITOA leads to insights that can be used to predict capacity, track applications, and tell us when we have security events.
There can be no real arguing against the fact that Amazon Web Services reigns supreme with regard to public cloud. Its recently announced quarterly results show that AWS is not only gaining revenue, but actually making a “small” surplus. OK, maybe not so small: a tad over half a billion dollars, compared to a $57 million loss for the same quarter in 2015.
What I have found interesting whilst watching it grow is how much like VMware it has become. I can hear you all saying, “It is nothing like VMware.” But please hear me out. AWS’s growth cycle is very similar. Why do I say this?
When we talk about monitoring for performance, security, and business rules, we often refer to monitoring of infrastructure or Platform as a Service mechanisms. But how do you monitor Software as a Service? Do you just tally the dollars spent for the service, or can you look at application performance, security issues, or even your business rules today? Or do you trust the SaaS to provide data?
At Zenoss GalaxZ 16, there was a button titled “Talk Data to Me.” That got me thinking about the nature of data or, more importantly, what we keep, what we use, and the future of data altogether. Do we throw away data because we have no way to store it or analyze it, or because we consider data to be a renewable resource? Are enterprises embracing data? Or is this just a next-generation application concept?