Watson AIOps 2.1 Guide to New Year's Resolutions

4 min read

November is a tad early for New Year's resolutions, but 2020 has been a year, right?

I'm going to go ahead and assert that it's never a bad time to take stock of where we are and where we're going. 

In that spirit, here's why our exciting Watson AIOps 4Q news resonates deeply with what I want to recognize this year and wish for the year to come.

Always learning

2020 Reflection: Given global health's recent impact on work and childcare, I've had the opportunity to closely (too closely?) observe my 20-month-old learning. His curious mind consistently turns novel inputs into new skills — using a fork (cultural adaptation), learning the word "hot" (self-preservation), and dancing like his dad (sneaky survival tactic through self-endearment). 

IBM Watson AIOps has also learned a lot in 2020. We started the year with a beta program and a dream, engaging with early adopter clients to put our product to the test. Thanks to our client partners and the hard work of our development teams and AI/Ml experts, we proved our ability to detect anomalies hours before they escalate into incidents and to help teams resolve incidents in minutes, instead of hours.

But we're not done, and we're ambitious enough to know that we'll never be done. There's always more to learn, ways to get better at learning, and the need to ensure that intelligence is interpretable and useful. 

In the 4th quarter, we're excited to continue making our learning advancements available to users. 

A few highlights include the following: 

  • Smarter recommendations based on similar past incidents, with algorithms improved by expert input and now supported with evidence from logs.
  • Improved ability for humans to influence event grouping so that Watson AIOps benefits from user expertise.
  • Visualization of a problem's location and blast radius within ChatOps, helping teams quickly learn what's going on and easily benefit from Watson AIOps insights (especially all you visual learners out there). 

Watson AIOps's learning means humans and artificial intelligence (AI) work better together to resolve incidents faster, reducing costs associated with incidents and improving the resiliency of applications. 

Well. I'm inspired. You? 

2021 Resolution: Be more like the Watson AIOps team and test smarts in the real world, tackle audacious learning goals, and consider learning a requisite skill in a complex world. 

Globally aware and locally specific

2020 Reflection: Any illusion that our little corners of the world are isolated from our global (health/economic/political/cultural) community is gone. At the same time, we've seen how important local context is for any effective program/effort/policy. Feeling waves of global trends wash over daily life while rarely leaving a 15-minute driving radius has been an eye-opening experience, especially as someone who (pre-global lockdown) held the unexamined belief that travel = exposure and no travel = isolation.

Watson AIOps is built on the premise that local effects can only be understood in the context of a system, and that a system's health depends on quickly localizing the source(s) of a problem. This crucial balancing act requires deep understanding of client applications and the dynamic topology of enterprise environments. 

Our upcoming release strengthens Watson AIOps's ability to localize problems and quickly assess their blast radius (i.e., other areas that were potentially affected). We're excited to bring users the following advances in topological understanding to accelerate investigation, diagnosis, and resolution of complex problems: 

  • Automatically discover relationships between resources in complex topologies. 
  • Find resources — even if they no longer exist — to build a historical understanding of how applications change. 
  • Recognize expected vs. abnormal changes in a topology over time with first-of-a-kind change metrics to help users focus on aberrations in normal behavior. 

Topological insights alone help users understand their applications, and we magnify their value by using topology to power intelligent event grouping, similarity to past incidents, and the insights users need to diagnose and resolve incidents. 

2021 Resolution: Take solace (and important lessons) from the reality that living in a more restricted local context doesn't mean I'm disconnected from the rest of the world. I'm part of the same 'topology' as my far-flung loved ones and fellow human/plant/animal/bacterial/viral earth-mates! Also, let's all take a reminder from Watson AIOps, and next time there's a 'locally observed problem' in an 'interconnected global system' — let's all pay attention and take action. 

Connected to what matters

2020 Reflection: I'd bet pretty much everyone has considered what it means to be "connected" this year. Connection has taken on a whole new meaning, from bandwidth to e-learning to screen fatigue to missing loved ones. It's also been a year of assessing what 'connected to truth' means, and what data sources we can and should rely on to make decisions. 

Watson AIOps is determined to work with the data that matters and deliver insights where people work. Connection makes 'learning' and 'topological awareness' practical and actionable by ensuring insights are based data on you care about and easily accessible to people who need them.

We're excited to expand the aperture of how product connections benefit our users and build on our existing integrations and partnerships. With our 4Q release you can do the following: 

  • Preview our Microsoft Teams integration to accelerate ChatOps workflows around incident and problem resolution.
  • Quickly gain insights from Splunk and Elastic log data and build custom integrations with other log data sources. 
  • Surface insights into alternate user experiences via API connection to accelerate your teams wherever they work. 
  • Experience our previously announced integrations with ServiceNow and IBM System Z.

Connection is the foundation for our journey to ensuring IBM is the preferred AIOps solution with trusted AI, out-of-the-box intelligence, fast time to value, and the ability to understand the applications you rely on every day to deliver value to your customers. 

2021 Resolution: I think this one is pretty obvious. Get smart about data sources, turn data into insights, make insights available to people who need them. I'm going to start close to home with: 

  • Data: Ever-expanding, rarely comprehensible toddler babble. 
  • Desired insight: What the heck you're trying to express?
  • Target user: Myself. 
  • Measurable outcome: Reduce local decibel levels. 
  • Goal: Take action on trusted insights to promote sanity. We all need more of that in 2021. 

Happy end of 2020 and remember to check out our webpage to learn more about IBM Watson AIOps.

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