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by BigPanda | November 8, 2017

ITOM Industry Update, Oct. 2017

ITOM Industry Update, Oct. 2017

Here at BigPanda we have a vision of using machine learning to automate and scale enterprise IT Service Operations. We’re always on the lookout for interesting insight, opinion and advice from the IT Operations Management market that might be important to you.

What’s our point of view in curating this list of ITOM Industry News You Can Use?

Cloud and DevOps have radically transformed the data center in terms of scale, fragmentation and speed. That’s left Service Ops teams – whose job it is to manage mission critical applications and infrastructure – struggling to catch up and keep their businesses running smoothly. We believe that automating manual and inefficient incident management processes helps enterprises meet the demanding IT service requirements of digital transformation. Legacy solutions for IT Event Management from the big IT vendors are no longer suitable solutions for modern and highly dynamic IT environments. So with this perspective in mind…

Here’s our roundup of the most interesting ITOM industry news articles from the last month.

 

AIOps Tools Portend Automated Infrastructure Management, TechTarget, 30 Oct 2017
Noteworthy press coverage of recent machine learning advancements in automating infrastructure monitoring.  Announcements by New Relic, BMC and Splunk are examined under the AIOps trend. BigPanda integrates with all three! We can ingest already correlated alert outputs from each system, then combine them for a more holistic understanding of clustered incidents.

Leveraging a Balance Between DevOps and ITOps, DZone, 20 Oct 2017
What’s the difference between DevOps and IT Ops? They are polar opposites, but work toward common goals. If you need a good piece to make your case, read this.

5 Ways to Squeeze more from Your IT Ops Analytics Tools, TechBeacon, 10 Oct 2017
Complex IT environments are flooded with data, and ITOA tools like BigPanda can separate the signal from the noise. IT’s ability to ensure stability, agility and innovation depend on good analytics. One of the 5 tips is to add context to machine learning algorithms by correlating data from a variety of sources, including non-IT sources. That’s what our open API is for.

Big Data Is Changing Machine Learning to a Must-have, Silicon Angle, 6 Oct 2017
We couldn’t agree more. Enough said.

Monitoring and Observability, Medium, 4 Sept 2017
This is a solid tutorial on the evolution of IT monitoring to “observability” – which is a DevOps friendly buzzword for traditional monitoring plus alerting/visualization, log analytics and systems tracing. The goals of each effort are different, and the two are complementary. Monitoring reports on the health of systems; Observability on their behavior.