What is NLP Natural Language Processing is a specialized subdomain of Machine Learning which is generally concerned with the interactions between the human and machine using a human verbal or written language. NLP helps in processing huge volumes of text which would take a significant amount of time for a human to comprehend and process otherwise. Hence a lot of organizations take advantage of NLP to gain useful insights out of their text and free formatted data.

Gartner Market Guide for AIOps Platforms, Pankaj Prasad, Padraig Byrne, Josh Chessman, April 6, 2021 Gartner Market Guides are used extensively by end-users building out their vendor shortlists for I&O leaders focused on Infrastructure, Operations and Cloud Management initiatives.

At PagerDuty, we have been heavily focused on developing our Artificial Intelligence for IT Operations (AIOps) solution. This has involved a lot of investment in our platform and a continued commitment to ensuring it delivers value to our customers as quickly as possible. With that, we’re delighted that Gartner named PagerDuty as a Representative Domain-Agnostic AIOps Vendor in its 2021 Market Guide for AIOps Platforms.

With so many IT vendors claiming they provide AIOps platforms, how do you understand the differences between them, and decide what flavor of AIOPs to choose for your organization? Join us in a CTO Perspective discussion with Elik Eizenberg, CTO and co-founder at BigPanda, to find the answer. Read the skinny for a brief summary, then either lean back and watch the interview, or if you prefer to continue reading, take a few minutes to read the transcript. Enjoy!

Industry analyst firm Gartner recently released a new report entitled Market Guide for AIOps Platforms. It’s a 20-page document that offers their perspective on the AIOps market. Unlike a Gartner Magic Quadrant, the Market Guides are not vendor comparisons. Market Guides are often precursors to MQs - they are used for emerging markets that may eventually have an MQ.

AIOps isn’t an IT magic wand, but it sometimes works like one. One day last fall, our IT ops team was heads down on a major cloud migration project. Meanwhile, ServiceNow Event Management detected a high volume of alerts from the monitoring system—600% more than usual. That typically means a lot of unplanned work for our IT team, not to mention a delay in our cloud migration schedule.

In this blog, we will walk through the scenario of sending or E-bonding ServiceNow incidents to 5 destinations simultaneously, using Robotic Data Automation and AIOps Studio. E-bonding refers to a scenario where data is delivered (one-way) or synchronized (two-way) between two or different systems, which are typically under different administrative boundaries. E-Bonding term originally appeared in Service Provider and Telco space (see: ATT E-Bonding).

I don’t know about you, but April traveled at the speed of light. A blink and it happened. Our teams have been working at the same speed throughout one of our favorite months of the year. With an incredible amount of updates, we’ve made our product even more transparent and easier to use. It’s not just our world-class documentation that enables you, it’s also the in-product visualizations and enablement that help guide you without you even realizing it.

Coined by Gartner in 2016, the term ‘AIOps’ refers to the combining of big data AI and machine learning to automate and improve IT operations processes. Back then, this very broad definition led to some confusion, with different IT vendors characterizing AIOps differently, depending on what they were actually offering.

Implementing any IT project requires time, planning, and effort and AIOps probably requires even more planning and stakeholder involvement, because of the breadth of coverage and potential to bring profits to multiple IT domains/functions (ex: ITOps/ITSM/NOCOps). Customers have high expectations from AIOps, but, even after taking such major projects, most AIOps vendors are only able to support a few core AIOps use cases, which severely limits the utility and potential of AIOps.