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Dynatrace SaaS on Azure now Generally Available

Dynatrace

In September, we announced the availability of the Dynatrace Software Intelligence Platform on Microsoft Azure as a SaaS solution and natively in the Azure portal. Today, we are excited to provide an update that Dynatrace SaaS on Azure is now generally available (GA) to the public through Dynatrace sales channels. Dynatrace news.

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Batch Processing for Data Integration

DZone

In the labyrinth of data-driven architectures, the challenge of data integration—fusing data from disparate sources into a coherent, usable form — stands as one of the cornerstones. As businesses amass data at an unprecedented pace, the question of how to integrate this data effectively comes to the fore.

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2. Diving Deeper into Psyberg: Stateless vs Stateful Data Processing

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

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1. Streamlining Membership Data Engineering at Netflix with Psyberg

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

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Analyze all AWS data in minutes with Amazon CloudWatch Metric Streams available in Dynatrace

Dynatrace

Amazon CloudWatch gathers metric data from various services that run on AWS. Dynatrace ingests this data to perform root-cause analysis using the Dynatrace Davis® AI engine. This allows for fast and direct push of metric data from the source to Dynatrace. Currently Dynatrace requests CloudWatch data every five minutes.

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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. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0: available, and more are in the pipeline. Extensions 2.0