Dynatrace launches Grail

New core platform technology unifies data while retaining its context to deliver fast, scalable, and cost-effective AI-powered answers and automation.

  • 2 years ago Posted in

Dynatrace has launched its Grail™ core technology within the Dynatrace® Software Intelligence Platform. Grail will revolutionize data analytics and management by unifying observability data as well as security and business data from cloud-native and multicloud environments, retaining its context, and delivering instant, precise, and cost-efficient AI-powered answers and automation. Initially, Dynatrace is leveraging Grail to power log analytics and management. Going forward, the company expects to extend the technology to power additional IT, development, security, and business analytics solutions.

Multicloud and cloud-native architectures, the backbone of modern digital transformation, produce an explosion of data. This data is siloed, reflecting the diverse parts of the cloud ecosystem where it originated. To extract value from this data using traditional solutions, ITOps, DevOps, SRE, and security teams need to structure it to reflect questions they expect to ask in the future. They rely on time-consuming manual procedures, including data indexing and rehydration, in addition to managing multiple data repositories, which cannot react quickly enough to rapidly changing application and cloud environments or evolving security threats. The cost and overhead of maintaining antiquated procedures and fractured toolsets outpace the business value. Modern clouds demand a new approach.

According to Stephen Elliot, Group Vice President, I&O, Cloud Operations, and DevOps at IDC, “Sprawling and dynamic cloud-native and multicloud environments are an ecosystem of various technologies and services, and the composition changes by the second. This paradigm makes it critical for organizations to acquire a platform with advanced AI, analytics, and automation capabilities. The platform must be able to ingest all observability, security, and business data, put it in an accurate context in real time, and facilitate access to data-backed insights when needed.”

Adding Grail to its platform positions Dynatrace to address these needs. Grail is a causational data lakehouse with a massively parallel processing (MPP) analytics engine. It leverages the new Dynatrace Query Language (DQL) for context-rich log analytics. It works in concert with other core Dynatrace platform technologies, including:

OneAgent® services to automatically discover, activate, and instrument applications, microservices, infrastructure, and any dependency in modern cloud environments;

Smartscape® continuously updated full-stack topology;

PurePath® distributed tracing and code-level analysis; and

Davis® causal AI to process data and deliver precise answers prioritized by business impact.

Philip Mendez, Product Owner – IT Performance Monitoring at Toyota Financial Services, said, “We’re on a mission to accelerate digital transformation. Success requires real-time insights from the enormous quantity of data streaming from our clouds. Grail takes our analytics capabilities to the next level by presenting logs in the context of user experience, traces, and related events. Our teams no longer have to decide which data to keep or what to do before storing it. And we no longer have to pay an arm and a leg for fast queries. Grail enables us to deliver more value to our customers with always-optimized systems and user experience.”

Bernd Greifeneder, Founder and Chief Technical Officer at Dynatrace, said, “Organizations are painfully in need of a revolutionary approach to observability, security, and business data analytics that transcends the performance limits of their existing solutions by as much as 100X for complex use cases while relieving existing cost constraints for managing cloud-native and multicloud environments. Grail delivers by boosting the Dynatrace-approach to causal AI, which retains data-context with precision and at massive scale. Starting with logs, Grail makes it possible for teams to leverage instant analytics for any query or question cost-effectively.”

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