If you’re an IBM Tivoli Netcool user, you have likely reached a point where the product can no longer support your needs. It’s outdated, expensive to maintain, and it can’t integrate with your newest data sources.
Naturally, you address this problem by looking into the ‘latest and greatest’ — IBM Netcool Operations Insight (NOI). The upgrade is essentially free, and the team at IBM ensures you that the new product incorporates bleeding-edge machine learning to detect anomalies and correlate alerts. Great!
What might surprise you is that NOI is still built upon the same outdated technology that Phil Tee and I created in the ‘90s, and was never built for modern, web-scale, and highly-dynamic IT environments.
Historical Models Only Tell You What You’ve Seen Before, at Best
If you have a [put on your best Trump voice imitation] ‘UGE set of historical Netcool Omnibus data (more than 90 days of it), then it might just show you what you already know (with a little [a LOT of] manual ‘underfitting’ and ‘overfitting’). With Netcool, humans must manually adjust their ‘AI’ to get a somewhat insightful set of alerts.
However, it will not give you insights into what you’ve never seen before.
But Wait, That’s OK if You Don’t Intend to Change Your IT or Your Network
As long as you have no intention of implementing Cloud, DevOps, or any kind of self-healing infrastructures, and you can handle getting Netcool Omnibus and Netcool Impact working first, you’re golden.
But, if you have plans to become agile, adopt DevOps and Cloud (private or public), then NOI will be incapable of detecting impact.
What’s Required to get IBM NOI Running?
- Get Netcool Omnibus working (6 months if you’re lucky)
- Get Netcool Impact working (uhhh…how long is that piece of string?)
- Collect a ‘UGE set of data (at least 3 months…but how much time is ever enough when the behavior that causes Incidents changes all the time?)
- Get IBM NOI learning from your ‘UGE set of data (including a second version of DB2 — clearly an innovation standard!)
- Create Baselines with historic data in NOI (well, anyone who has tried it knows that one month of data is not enough to create baselines, you need at least 90 days)
- Do everything again when you change anything (folks — things change, Baselines are irrelevant, that’s why IBM NOI has a ‘UGE costs of ownership, and that’s why IBM NOI doesn’t work)
Now, try using NOI in an elastic / Cloud / DevOps environment…it doesn’t see new things! Remember… things change, people.
You’ll notice that your IBM account team will come in and tell you that, for IBM NOI to have the best chance of demonstrating anything, they recommend you start over with your entire Netcool architecture.
RISK WARNING: How long has it taken you to get Netcool Omnibus and Impact working? It’s taken years! (These are 25-year-old products that we invented way back when we had no experience.)
How Can Moogsoft AIOps Help?
I’ve spent a lot of time criticizing an outdated product, but what’s the alternative for Netcool users who really care about their service quality?
If you want to get more value out of Netcool Omnibus and Impact today, then just install Moogsoft AIOps on top of your existing Netcool Suite. Guaranteed, the benefits of Moogsoft (earlier detection, fewer tickets, reduced MTTR) alone will more than compensate for the costs of Moogsoft and the maintenance fees of your existing Netcool fabric.
However, if you have your old infrastructure assured by Netcool and your new infrastructure and applications assured by many different tools (Splunk, Elastic, AppDynamics, Dynatrace, vRealize, vCenterOps, Zabbix, Nagios, Datadog, etc.), and you have Amazon AWS CloudWatch, Microsoft Azure OMS and other Cloud monitoring tools — you know, the kind of stuff you cannot feed into Netcool because it is not agile enough — then feed all of that into Moogsoft AIOps and reap the benefits of a collaborative, AI-driven IT Operations and IT Service Management suite.
You’ll also benefit from the lowest total cost of ownership (TCO) in the assurance industry. So go agile, and change to your heart’s content. Remember, we designed Moogsoft to address today’s IT and Telecommunications issues:
- Constant change, which increases TCO and reduces value of IT Operations tools
- Disassociated silos of support, which increase the volume of spam tickets
- Layers of expertise separated by non-informative tickets with increased MTTR
Moogsoft AIOps uses real-time AI innovations (16 patents so far!) to drive business value outcomes — earlier warnings, reduced tickets, reduced ‘all-hands’ war rooms, and reduced MTTR.
We didn’t just tack reflective AI onto our existing already outdated portfolio!
About the author Mike Silvey
An expert in IT operational management and technology commercialization, Mike launched SunNet Manager in the UK for Sun Microsystems before founding an open systems service management business at Micromuse where he brought several innovative service management tools into the European market (such as Remedy) and established key OEM relationships (Cisco, HP, Intel) that led to successful IPOs for both Micromuse and RiverSoft. Today, Mike is focused on and scaling Moogsoft by overseeing strategic business relationships with key partners around the globe.