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OpenTelemetry: Unifying Application and Infrastructure Observability

DZone

Veeramachaneni discusses how OTel is standardizing telemetry data and inspiring new open-source data collectors and workflows that bridge the gap between application and infrastructure monitoring. A: It’s given developers and platform teams much greater ownership of their data.

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From syslog to AWS Firehose: Dynatrace log management innovations that enhance observability

Dynatrace

Understanding that the first mile of getting data in can often be the hardest, Dynatrace continues to invest in log ingest, offering a range of out-of-the-box solutions within the Dynatrace Platform and apps. Native support for syslog messages extends our infrastructure log support to all Linux/Unix systems and network devices.

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Viking Enterprise Solutions: Empowering Modern Data Infrastructure

DZone

In today's rapidly evolving technological landscape, developers, engineers, and architects face unprecedented challenges in managing, processing, and deriving value from vast amounts of data.

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Google Cloud Next 2024: AI innovation for Google Cloud

Dynatrace

In today’s rapidly evolving landscape, incorporating AI innovation into business strategies is vital, enabling organizations to optimize operations, enhance decision-making processes, and stay competitive. The annual Google Cloud Next conference explores the latest innovations for cloud technology and Google Cloud.

Google 273
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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 236
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 199
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Accelerate Innovation by Shifting Left FinOps: Part 6

DZone

In the subsequent parts, we learned how to optimize our workload components across infrastructure, applications, and data. In the first two parts of this series, we understood the importance of cost models and how to create and refine cost models.