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Lab Introduction

The following lab simulates a real-world engagement with a Dynatrace customer. The customer already gains significant value from features such as Distributed Traces, Memory Profiling & RUM and is now beginning to adopt Dynatrace 3rd-Generation capabilities like Explorative Analytics and Logs in Grail.

Their Classic foundations, auto-tags and Management Zones, are well established, and they are now ready to build solid 3rd-Gen foundations, including Data Access and Segments.

They recognize the power of the new platform not only in observability but also in performance, security, and administrative efficiency.

  • 🌱 Enrichment at the source will significantly improve cluster performance and scalability across their tenant.
  • 🔐 The new Data Access model aligns with their security requirements.
  • 💰 DSP Cost Allocation enables clear visibility into each team’s spending.

Objectives#

You will work with one of the customer’s application teams. Easytrade is one of their key apps. Your goal is to help implement the Dynatrace 3rd-Generation Platform end-to-end for the Easytrade team, enabling the customer to onboard additional teams effectively.

You will complete a series of critical tasks:

  • Slice & Dice: Understand customer requirements, dimensions, and technologies to define the foundational setup.
  • Metadata Enrichment: Learn about Primary Grail Fields and explore methods for enriching observability signals.
  • Data Access: Configure IAM for the 3rd-Gen platform.
  • Data Segmentation: Create meaningful, dynamic, and scalable Segments.
  • Data Partitioning: Design an efficient bucket strategy and learn how to apply it.
  • Cost Allocation: Distribute observability costs across teams and services transparently.