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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization. Understanding the context.

Analytics 195
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Overseeing SaaS security with AWS AppFabric and Dynatrace

Dynatrace

To address these challenges, Amazon Web Services (AWS) has introduced AWS AppFabric , an AWS service that quickly connects SaaS applications across an organization for enhanced security and employee productivity. This section shows how to analyze AWS AppFabric logs with Notebooks and DQL.

AWS 246
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AWS re:Invent 2023 guide: Generative AI takes a front seat

Dynatrace

At the AWS re:Invent 2023 conference, generative AI is a centerpiece. In this AWS re:Invent 2023 guide, we explore the role of generative AI in the issues organizations face as they move to the cloud: IT automation, cloud migration and digital transformation, application security, and more.

AWS 210
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Accelerate your cloud journey with Dynatrace observability for AWS S3 logs

Dynatrace

Many AWS services and third party solutions use AWS S3 for log storage. We hear from our customers how important it is to have a centralized, quick, and powerful access point to analyze these logs; hence we’re making it easier to ingest AWS S3 logs and leverage Dynatrace Log Management and Analytics powered by Grail.

AWS 198
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

Visibility into system activity and behavior has become increasingly critical given organizations’ widespread use of Amazon Web Services (AWS) and other serverless platforms. These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor.

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Implementing AWS well-architected pillars with automated workflows

Dynatrace

If you use AWS cloud services to build and run your applications, you may be familiar with the AWS Well-Architected framework. This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem.

AWS 247