Adventures of a Technical MasterMind

As someone who bought and implemented NPM solutions, covered them as an analyst, and now watches the industry, one cannot help but notice that NPM(D) is broken. According to Gartner themselves, the data center is rapidly changing, the data center is going away, m aybe not as quickly as Capp states, but it’s happening. This is apparent by the massive public cloud growth posted by Amazon, Microsoft, and Google in their infrastructure businesses. This means that traditional appliance-based NPMD offerings will not work, nor will traditional ways of collecting packet data. Many of the flow offerings do not handle the new types of flows which these services generate, but most importantly they do not understand the internet, which is the most important part of assuring services in cloud hosted environments. The network itself is not just moving to overlay a-la NSX and ACI, it's moving inside of orchestrated containers, and new proxy/load balancing systems typically built off component

Amazing that it’s been two months since last writing, but it’s been a bit busy launching new products and getting customer implementations under our belts. Since the well-oiled machine is accelerating, and additional help is inbound, there is more time in the day to analyze the market and the rapid changes occurring. There has been a lot of AI washing, even more so than 10 months ago when this was penned . As expected, AI is the new cloud (these Microsoft AI commercials are driving me crazy). If you don't have AI in your message, you are not relevant. The buyers of technology are eating up the wording even though this is far from reality, as I have explained. The outcomes associated with generically attaching to a word is a good marketing move but creates a mess for the users of technology, and those analysts who cover and define markets. We already are seeing many end users of technology asking why they need so many different "AIOps" tools. For those who see this te

When first hearing of the OpenTracing project in 2016 there was excitement, finally an open standard for tracing. First, what is a trace? A trace is following a transaction from different services to build an end to end picture. The latency of each transaction segment is captured to determine which is slow, or causing performance issues. The trace may also include metadata such as metrics and logs, more on that later. Great, so if this is open this will solve all interoperability issues we have, and allow me to use multiple APM and tracing tools at once? It will help avoid vendor or project lock-in, unlock cloud services which are opaque or invisible? Nope! Why not? Today there are so many different implementations of tracing providing end to end transaction monitoring, and the reason why is that each project or vendor has different capabilities and use cases for the traces. Most tool users don't need to know the implementation details, but when manually instrumenting wi

Artificial Intelligence in Digital Operations Not a week goes by where I don't see a vendor claiming that they have applied Artificial Intelligence (AI) to running digital businesses (there was a new one this week, but I began writing this beforehand). The list of vendors continues to increase, and when digging into the technology, the marketing is often overstepping the use of the AI term. Let's take a step back and understand what AI is from a computer science perspective. The traditional problems (or goals) of AI research include reasoning , knowledge , planning , learning , natural language processing , perception as per Wikipedia. The other interesting trend is the application of the AI effect . This term explains that as we apply models and data to problems, and create algorithms to solve these problems, we move the problem outside of the scope of AI. Thus, abusing term AI to describe much of what we do in technology. Most of the technology itself is not complex w

As outlined in a prior post, Digital Business operations require new thinking and new technologies. As Operations evolves to meet the needs of Digitalization, so too must the core systems of record for operations. When running a data center with physical assets, or even user assets such as laptops, printers, and desktops the CMDB was a useful construct to understand what you had, things were static, and thus the problem was more easily solved. In reality, almost no one had an accurate CMDB, they most often hovered around 80% coverage, based on the beliefs of staff, and often were driven by a combination of automated and manual processes. The use cases for the CMDB are often tied to ITSM processes such as request, incident, problem, and change management. By having good data capture to record asset and component ownership and configuration it made these processes more robust, reliable, and accurate. By using discovery tools which crawled technologies or leveraged the network for data

Being a Canadian, and to celebrating Canada turning 150 years old, I wanted to call out some interesting trend data I recently came across. Having spent a good amount of time visiting with customers in Canada in 2017, as I do each year I have noticed changes in the country. Quite possibly due to the changes in government and the political climate, or change and progress in the private sector. In Canada, there are economic challenges today, mostly due to a high reliance on natural resources, and low market prices today. Even with these difficulties there are increased IT budgets in Canada, surpassing the global average growth rates based on the Gartner IT survey data. When breaking this down further, only 38% of government employees projected budgetary growth versus 64% of non-government respondents in Canada. Comparing these to last year the numbers were 16% and 57% respectively. Canada sees increased investment from a technology perspective based on the survey group. Much of