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Helping customers unlock the Power of Possible

Dynatrace

Dynatrace transforms this unstructured data into a strategic advantage, processing it automatically—no manual tagging required. By automating root-cause analysis, TD Bank reduced incidents, speeding up resolution times and maintaining system reliability. With over 2.5 The result?

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Automating DevOps practices fuels speed and quality

Dynatrace

Still, while DevOps practices enable developer agility and speed as well as better code quality, they can also introduce complexity and data silos. Software development is often at the center of this speed-quality tradeoff. Automating DevOps practices boosts development speed and code quality.

DevOps 290
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Cut costs and complexity: 5 strategies for reducing tool sprawl with Dynatrace

Dynatrace

Break data silos and add context for faster, more strategic decisions Data silos : When every team adopts their own toolset, organizations wind up with different query technologies, heterogeneous datatypes, and incongruous storage speeds. Follow the “Dynatrace for Executives” blog series. See the overview on the homepage.

Strategy 262
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New continuous compliance requirements drive the need to converge observability and security

Dynatrace

Carefully planning and integrating new processes and tools is critical to ensuring compliance without disrupting daily operations. Visibility of all business processes starting from the back end and ending with customer experience is perhaps the biggest challenge.

Analytics 289
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Speed up your security investigations with DPL Architect

Dynatrace

The best thing: the whole process is performed on read when the query is executed, which means you have full flexibility and don’t need to define a structure when ingesting data. >> DPL Architect enables you to quickly create DPL patterns, speeding up the investigation flow and delivering faster results.

Speed 235
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Transform data into insights with Dynatrace Dashboards and Notebooks

Dynatrace

Our latest enhancements to the Dynatrace Dashboards and Notebooks apps make learning DQL optional in your day-to-day work, speeding up your troubleshooting and optimization tasks. Kickstarting the dashboard creation process is, however, just one advantage of ready-made dashboards.

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.