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Top 5 Key Takeaways from Knowledge 18 for AIOps

From stale CMDBs to legacy systems, here’s what AIOps needs to know
After 56,000+ steps and more than 75 quality conversations, these are my top five key takeaways from the conference.

If there was ever an appropriately-titled conference, it’s definitely Knowledge. As I alluded to in my first Knowledge 18 blog, I love how ServiceNow brings IT professionals together to advance our collective skills and give glimpses into how our new technology shapes and drives markets. The quality and level of business awareness that attendees exhibited were second to none, and in our ScienceLogic booth, we could feel their need and excitement for SL1, our recently announced robust AIOps platform.

Erik Rudin, VP of Business Development, ScienceLogic

After 56,000+ steps and more than 75 quality conversations, here are my top five key takeaways from the conference:

    1. Bad data from legacy systems is costly – No matter if you’re early in your journey with ServiceNow or far down the path, customers want to ensure they’re maximizing the opportunity provided by a highly functioning deployment. Unfortunately, many deployments are suffering from antiquated systems and processes from past investments that they are trying to carry over into the new digital world. We were asked during almost every conversation how ScienceLogic could enhance and accelerate the return on their investment in ITSM and ITOM.


    1. Customers are struggling to keep their CMDB clean and current – We conducted some informal surveys on how often customers refresh the topology or CI discovery in their CMDB. Most have daily updates and some far less frequent due to manual, ad hoc processes. When we described that we automated topology mapping and CI attribute discovery and then sync those updates every 15 minutes or less for over 5000+ device types, they were ready for another conversation with our team.


    1. It’s difficult to automate in ServiceNow with inaccurate information – Most customers understand and appreciate the power of automation within their IT systems. As more and more data enters the NOW platform, trying to drive automation to decrease MTTR, increase MTBI (Mean Time Between Incidence) or just reduce the volume of incidents, requires accurate and operational data. our message of modernizing how IT operations data is collected, normalized, contextualized and synced into the various interface points to the platform in near real time resonated with almost everyone we spoke with.


      1. Everyone wants to leverage artificial intelligence and machine learning, but most aren’t ready – If you talk to any data scientist about machine learning (ML), deep learning neural nets or artificial intelligence (AI), they will tell you that it takes good training data to create meaningful insights. These complex algorithms are getting better each year. However, enterprises struggle with providing consistent, reliable, and complete data sets into their AI/ML platform of choice. If you have 25+ tools all providing different data feeds with different levels of quality and accuracy, it’s awfully difficult to derive actionable results. Sensing that market opportunity, our SL1 platform is designed to address it by providing a consistent data model, multi-level contextual data relevancy, and a sophisticated data synchronization engine.


It takes an ecosystem of platforms to get the job done – It’s clear that no single vendor can solve the broad scope of challenges to becoming a fully digital organization. We met with many of the Expo Hall partners that each complement ServiceNow in some way but also are experts in their own domain. We heard of several interesting platform-to-platform integrations that could help enrich our operational dataset with even more contextual data. I’m excited to see our ecosystem of ServiceNow integrator and ISV partners expand into 2018.

Looking back on this conference, I think this was the best Knowledge I’ve attended so far. It was the most energizing and engaging event for the ScienceLogic team and me. Much like my colleagues, I’m reenergized at the future potential for ServiceNow and ScienceLogic, and our plans to help customers alleviate their pain points. In fact, our SL1 webinar on May 16, 2018, will show how the platform brings context to data, provides real-time insights into business services, and enables operational resiliency.

We are ready and up for the task of automating the future of ITOps. Are you?

If you’re on LinkedIn and want to continue the conversation, let’s connect!