In June, the research firm GigaOm, published the 2022 edition of their annual Radar for AIOps Solutions, having had time to digest the contents, it seems a good time to summarize the key takeaways from the Moogsoft perspective. Firstly, in case you are not familiar with GigaOm, here’s a brief introduction.
GigaOm is a research company that provides technical, operational, and business advice for IT’s strategic digital enterprise and business initiatives. As an engineer, one aspect of GigaOm's research methodology that I appreciate is the technical depth of the primary research. The GigaOm analysts interview businesses that have implemented and put into production, the solutions being reviewed, and in many cases, the analysts themselves have had first hand practical experience with the products being reviewed.
The criteria for assessing products is based on GigOm’s own “Key Criteria for Evaluating AIOps Solutions”, and forms a matrix where each vendor is ranked based on the individual criterion.
The most visual, and easy to digest takeaway from the report, is the Radar graphic, which positions each vendor on a quadrant that resembles a RADAR display (as a sailor, I appreciate the analogy). The proximity to the center identifies leaders in the AIOps space, with challengers and new entrants being further out. The classification of “leadership” is therefore determined by the vendor's relative “bearing” on the graph (the cartesian coordinate). They are ranked by maturity and innovation, as well as whether GigaOm considers them a platform, or feature play.
A third visual element is in the form of an arrow (or vector) that indicates how significantly the vendor is moving towards the center, which is the ideal.
What can we take away from the Radar? Well, we see a lot of mature solutions in the top vertical. These vendors, while being “forward moving” are most suited for enterprises that value stability over transformation, as the platforms are adding AIOps capabilities as features rather than core capabilities. As you move to the right, you’ll see vendors that are more likely to be described as legacy platforms, where you need to invest heavily in a comprehensive platform (or suite of products) in order to gain access to the AIOps capabilities.
But the real news is in the arrows. Of the 24 vendors included in the report, only 3 garnered the coveted “Outperformer” designation, BMC, Splunk, and yes, Moogsoft (with Moogsoft’s arrowhead closest to the ideal). The implication is clear, if you’re taking your AIOps investment seriously, you absolutely need to include Moogsoft in your strategy.
Given the practical, hands-on nature of the analysis, we couldn’t be happier about how we are positioned.
But what do GigaOm say about us specifically? Well, as an engineer, two areas of strength they’ve highlighted go a long way to explaining the success of our approach. Firstly, the strength and variety of the machine learning capabilities in the product. As a practitioner, I particularly appreciate the value of the unique Natural Language Processing. The other being the flexibility, and comprehensive nature of the data ingestion.
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