Are We Too Busy to Innovate? SplunkConf19 #DataToEverything
Here is the full prologue of SplunkConf19 in 6 charts, based on full-text indexing of the show agenda and session descriptions. 11,000 operators, developers, and analysts have come together in Vegas to learn about how to better leverage their operations data (the digital exhaust that happens if you use it or not) for business.
Are We Too Busy to Be Innovative
And like last year, Splunk gets it right. But the key questions is: “are we ready?” As Doug Merrit says: “the limit to what we can do with data is our imagination.” This may sound trivial, but in our reality of having to run IT operations and DevOps pipelines, there often is not all too much time for innovation and experimentation. The first announcement, the Splunk Data Stream Processor, might be a very interesting platform to attack the crucial challenge of us all just being “too busy to be be innovative.”
Before diving into the new product announcements from #SplunkConf19, let us take a look at the 6 different tracks #Splunk laid out for its customers.
Business Analytics
Business analytics is the most exciting area for Splunk and all other analytics vendors to grow into. Modern enterprises are missing out on millions and billions of additional revenue and cost savings potential simply because of ignoring existing signals within their own companies. This digital exhaust is already there, but we usually analyze it within silos and we ignore entire, potentially relevant, data streams entirely. The word cloud shows Splunk’s priorities in this area.
IT Operations
IT operations and AIOPs is Splunk’s original claim to fame. In the beginning the company strategy was focused on log analytics only. Today, Splunk is pushing to become a full observability platform that looks at and correlates logs, metrics, and traces. This is so interesting as all the talk about machine learning and artificial intelligence only makes sense if we are serious about picking up data in real time.
Developers
Modern developers are expected to take advantage of machine learning, deep learning, and artificial intelligence capabilities. Splunk is positioning itself as the technology vendor that automatically surfaces, contextualizes, and analyses data within a role and situational context. Below is the word cloud made up of all of the SplunkConf19 sessions on this topic.
Security
The equation is simple: the more metrics, logs, and traces you can correlate, the more effectively you can automate security based on machine learning and deep learning models. I strongly believe that everyone has access to the same learning algorithms. This means that whoever is able to source, process, contextualize, and model the data foundation for these fancy learning models to ingest, wins
Internet of Things
It is Splunk’s declared mission to pick up the signals (logs, metrics, traces) from any system to add to continuously enhance the corporate data lake. Ultimately, the organization with the strongest data lake will dominate its market.
Foundations/Platform
The Foundations/Platform is the operational hub for Splunk to connect to internal and external systems and data sources to feed its intelligently learning models.
