Tuesday, February 12, 2019

Tech Field Day 18 - Day 2 with SolarWinds

Picking up from the data analytics, machine learning and artificial intelligence discussion from my last blog post about Tech Field Day 18 - Day 1, I wanted to dive into the briefing we got from SolarWinds on Day 2. SolarWinds is using that analytics and data sets to make informed decisions and they are leveraging machine learning as part of that process. The presentations are up to watch, you can find them at the link below.

SolarWinds:
https://techfieldday.com/appearance/solarwinds-presents-at-tech-field-day-18/

Of particular note is the presentation by Thomas LaRock, Head Geek and Karlo Zatylny, Distinguished Engineer at SolarWinds discuss machine learning, anomaly detection, and Database Performance Analyzer. This presentation goes over the difficulties of using algorithms to try and determine the right way to do predictive analysis and how to display that information to users. It was a very good presentation on the challenges the industry faces in getting things right and how hard it can be to make good assumptions. It also highlights how important it is to have good data and the context of that data. I think even harder is the UI work and how to give the right context around the data being displayed. Honestly, that will likely be the second hardest part of all of this data science work. Providing an intuitive way to understand what the data is telling you without putting in unnatural bias or artificial conclusions in the presentation of that data will be tough. I think SolarWinds is on the right track with what they are doing and their customers will ultimately get a lot of value from the product because of that. At the end of the day, value is what is most important. If they can provide better insight to drive better outcomes or actions then they win a vote of confidence from their customers. I think, for most customers, this will be the determination of if they demand data analytics, machine learning and eventually artificial intelligence or not and if they are willing to pay for it. SolarWinds is helping folks find the needles quickly, now what to do with them is the next challenge.
- Ed

In a spirit of fairness (and also because it is legally required by the FTC), I am posting this Disclosure Statement. It is intended to alert readers to funding or gifts that might influence my writing. My participation in Tech Field Day was voluntary and I was invited to participate in TFD18. Tech Field Day is hosted by Gestalt IT and my flights, hotel, transportation, food and beverage was paid for by Gestalt IT for the duration of the event. In addition, small swag gifts were provided by some of the sponsors of the event to delegates. It should be noted that there was no requirement to produce content about the sponsors and any content produced does not require review or editing by Gestalt IT or the sponsors of the event.

Monday, February 11, 2019

TechField Day 18 - Day 1 with Datera, NetApp and VMware

I was fortunate to be invited to participate in Tech Field Day 18 in Austin, TX. Day one had Datera, NetApp and VMware presenting to the delegates. The mix of delegates made for some interesting questions and discussions so I recommend you watch the presentation for each so you can hear the conversations. You can find each of the videos at the links below:

Datera:

VMware:


While all the marketing in the industry is talking about data analytics, machine learning and artificial intelligence it was interesting to see how companies are actually trying to apply these ideas in practice in their products. I think the transition happening today is that data analytics is providing information that allow lay people the ability to discover details and insight into their business or technical processes that they didn't know before. This is an opportunity for companies that are providing this level of insight to stand out. Using that analytics and data sets to make informed decisions and leverage machine learning is the natural progression. Not everyone is there, not everyone has the same data sets gathered and the journey from data, to information, to knowledge, will not be equally distributed across the industry either.

As an example, it is clear that the data insights that Datera leverage allow them to make a much more efficient and cost effective storage solution, there isn't anything unique about the hardware, in fact they make that a selling point. The value is in looking at the data, the intention of what that data needs to do and the letting their system figure out what the right thing to do with the data.

A different lens is what NetApp Active IQ is doing with the huge telemetry data they get in supporting their customer. They are providing proactive guidance and recommendations on what to do in supporting their solutions. Their challenge is given the massive amount of data they gather, how do you gain the best insights and turn those into recommendations and finally, how do you extend that to something predictable. I think their next challenge will be how to integrated third party data into the platform in a meaningful way. While I am happy to see them doing this work, it feels too narrow in it's current form. Once their data and insights are extended out into other third party products or they can integrate with major partners then their combined data insights become that much more compelling. I will be keeping an eye on what they do to see if that happens.

Finally, VMware has an equally interesting data support insight model around vSAN and their vCenter products. They are doing some fantastic work around anonymizing customer data and still providing great support and telemetry around what they customers need. I would like to also see them extend beyond their own product lines to do integration with third party so that customers can see across their diverse products and solutions and get a much more holistic view of their environment and the potential impacts might happen from an operational change or upgrades/downgrades.

As with any transition, the devil is in the details and this data revolution is no different. Moving from unstructured data to structured in order to gain data insights is hard. Logging and monitoring data is hard to manage and without the right tools, almost impossible to get anything useful out of it. Finding all the needles is the goal with what is happening now. They next phase is what do you do with all these needles once you find them.
- Ed

In a spirit of fairness (and also because it is legally required by the FTC), I am posting this Disclosure Statement. It is intended to alert readers to funding or gifts that might influence my writing. My participation in Tech Field Day was voluntary and I was invited to participate in TFD18. Tech Field Day is hosted by Gestalt IT and my flights, hotel, transportation, food and beverage was paid for by Gestalt IT for the duration of the event. In addition, small swag gifts were provided by some of the sponsors of the event to delegates. It should be noted that there was no requirement to produce content about the sponsors and any content produced does not require review or editing by Gestalt IT or the sponsors of the event.