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USENIX LISA 2018: CFP Now Open

Brendan Gregg

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more.

DevOps 43
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USENIX LISA 2018: CFP Now Open

Brendan Gregg

Today's LISA attracts attendees working on all sizes of production systems, and its attendees include sysadmins, systems engineers, SREs, DevOps engineers, software engineers, IT managers, security engineers, network administrators, researchers, students, and more.

DevOps 40
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World’s Top Web Performance Leaders To Watch

Rigor

Rick is a software engineer on the Google Chrome team, “leading an effort to make the web just work for developers.” Patrick is a London-based software developer who specializes in web performance and who describes himself as enjoying “working the entire stack, back-end to front-end, CDN to server.”

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Conducting log analysis with an observability platform and full data context

Dynatrace

Causal AI—which brings AI-enabled actionable insights to IT operations—and a data lakehouse, such as Dynatrace Grail , can help break down silos among ITOps, DevSecOps, site reliability engineering, and business analytics teams. Business leaders can decide which logs they want to use and tune storage to their data needs.

Analytics 187
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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

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Incremental Processing using Netflix Maestro and Apache Iceberg

The Netflix TechBlog

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing.

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202