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Optimize your observability pipeline for AWS Lambda serverless functions

Dynatrace

With the growing complexity of application architectures which can rely on tens of thousands of microservices, end-2-end observability is a requirement to optimize application performance and to deliver intelligent root-cause analysis. This makes it easier to apply/enforce monitoring policies as fewer teams are involved (e.g.

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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 observability and data observability The importance of effective AI data analysis to organizational success places a burden on leaders to better ensure that the data on which algorithms are based is accurate, timely, and unbiased.

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Seamless AI-powered observability for multicloud serverless applications

Dynatrace

Cloud vendors such as Amazon Web Services (AWS), Microsoft, and Google provide a wide spectrum of serverless services for compute and event-driven workloads, databases, storage, messaging, and other purposes. AI-powered automation and deep, broad observability for serverless architectures. Dynatrace news.

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IT teams seek observability for, and control over, serverless architecture

Dynatrace

Key takeaways from this article on modern observability for serverless architecture: As digital transformation accelerates, organizations need to innovate faster and continually deliver value to customers. Companies often turn to serverless architecture to accelerate modernization efforts while simplifying IT management.

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Dynatrace extends distributed tracing for serverless on AWS Lambda (GA)?

Dynatrace

With our enhanced AWS Lambda extension , we bring the power of Dynatrace PurePath 4 automatic tracing technology to serverless function observability. Serverless can accelerate innovation (and introduce blind spots). However, while they provide significant benefits, serverless functions also pose several challenges.

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Conducting log analysis with an observability platform and full data context

Dynatrace

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations. Grail enables 100% precision insights into all stored data.

Analytics 196
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

The number and variety of applications, network devices, serverless functions, and ephemeral containers grows continuously. Still, it is critical to collect, store, and make easily accessible these massive amounts of log data for analysis. Current analytics tools are fragmented and lack context for meaningful analysis.

Analytics 243