The News: Software intelligence platform vendor Dynatrace has added deeper data analytics and management tools to its Dynatrace Software Intelligence Platform that will unify observability data as well as security and business data stored in siloed cloud-native and multicloud environments. The new features, called Grail, are a homegrown core technology built to unify and contextualize observability and security data at scale to smooth out operations for users. Read the full Press Release about Grail from the Dynatrace website.

Software Intelligence Vendor Dynatrace Boosts Data with Grail

Analyst Take: For software intelligence specialist Dynatrace, adding these specialized and versatile capabilities to its platform via Grail helps solve some of the biggest configuration challenges for enterprises – how to make their huge stores of data work effortlessly with the software applications they are using.

By providing integrated Grail tools that can streamline this process of unifying observability data, security data, and business data from both cloud-native and multicloud environments, Dynatrace is making the lives of its enterprise customers easier, which is sure to win users and praise.

This strategy of introducing needed add-on tools to make off-the-shelf applications work better and provide the biggest bang for the buck for enterprises is reminiscent of a long history of big applications, where smaller niche vendors added the specific tools that individual enterprises needed. It was how Lotus Notes and other huge applications worked 15 years ago and even today, and this still makes sense.

Kudos to Dynatrace to take the initiative and implement these major improvements to its software intelligence platform to help its customers better use their own data and resources.

So far, the implementation of Grail into the Dynatrace platform focuses on unifying log analytics and management, but additional and broader capabilities are expected in the future in other areas of enterprise IT, development, security, and business analytics, according to the company.

What Grail Delivers for Enterprise Users

One of Grail’s biggest strengths for users is that it takes an enterprise’s critical business data and unifies it while retaining its context and delivering immediate and precise AI-powered answers and automation so enterprises can gain deeper insights from that data.

I believe that capabilities like these again show the value of integrating AI into a wide range of enterprise applications to deepen their capabilities and help to solve customer pain points. It is a laudable and appreciated mashup for enterprises and one that I believe will continue to inspire similar trends across the IT ecosystem.

Multicloud and cloud-native architectures typically silo their data into diverse parts of the cloud ecosystem where it originates, according to Dynatrace, but that is not how enterprise customers want to use their data.

Instead of using the manual procedures of the past to bring that data together for use, Grail will now do this automatically for users of the Dynatrace platform, improving efficiencies, processes, and data integration for users. Grail is essentially described by the company as a purpose-built data lakehouse with massively parallel processing (MPP) analytics engine that provides speed, scale, and instant analytics.

The nascent Grail software intelligence capabilities leverage a new Dynatrace Query Language (DQL) that creates context-rich log analytics and works with other core Dynatrace platform technologies, including OneAgent, Smartscape, PurePath, and Davis.

The Grail capabilities for log management and analytics will be available to Dynatrace SaaS users on AWS starting in about one month, according to the company.

Grail Overview

This Dynatrace announcement of Grail is big news for enterprise users because it will make the company’s software intelligence platform easier to use and more powerful to create deeper insights and value from an enterprise’s essential data.

And meeting those goals is a core need of every enterprise that maintains and uses large stores of data. These kinds of steps are evolutionary for businesses which already experience this problem and are revolutionary for other enterprises that have not yet realized how important these steps will be for their operations.

This is an area to continue to watch closely and Dynatrace is wisely making progress delivering these important features to its customers today. That is great news for the data analysts who must deal with dramatically increasing stores of useful business data.

Disclosure: Futurum Research is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum Research as a whole.