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Automate your work with unified observability and custom solutions

Dynatrace

In this blog post, we explore real-life scenarios shared by our customers, partners, and internal users at Dynatrace, offering inspiration to kickstart your own journey with custom solutions powered by AppEngine.

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

AI data analysis can help development teams release software faster and at higher quality. AI-enabled chatbots can help service teams triage customer issues more efficiently. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights?

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Enhance data management with Grail: Ultimate guide to custom buckets and security policies

Dynatrace

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

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Expanded Grail data lakehouse and new Dynatrace user experience unlock boundless analytics

Dynatrace

Now we’re adding Smartscape to DQL and two new data sources to Grail: Metrics on Grail and Traces on Grail. Ensuring observability across these environments requires access to data at a massive scale. You no longer need to split, distribute, or pre-aggregate your data. Grail solves this scalability issue!

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