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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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Extend the AI and automation core of Dynatrace with host extensions to resolve infrastructure problems

Dynatrace

A single instance of OneAgent can handle the monitoring of many types of entities , including servers, applications, services, databases, and more. All the data bound to hosts is analyzed by the Davis AI causation engine and made available on custom dashboards and events pages. Dynatrace news. What’s next.

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Automating Success: Building a better developer experience with platform engineering

Dynatrace

Check out the following use cases to learn how to drive innovation from development to production efficiently and securely with platform engineering observability. According to Deinhammer, once software is released into production, it’s usually deployed at a large scale—often in complex multicloud or hybrid setups.

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Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. They enable IT teams to identify and address the precise cause of application and infrastructure issues.

Analytics 246
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Designing Instagram

High Scalability

FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. We will use a graph database such as Neo4j to store the information. Sample Queries supported by Graph Database. System Components.

Design 334
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MLOps and DevOps: Why Data Makes It Different

O'Reilly

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. In effect, the engineer designs and builds the world wherein the software operates. What: The Modern Stack of ML Infrastructure.

DevOps 145
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Sponsored Post: PerfOps, InMemory.Net, Triplebyte, Etleap, Stream, Scalyr

High Scalability

Triplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Join Etleap , an Amazon Redshift ETL tool to learn the latest trends in designing a modern analytics infrastructure. Who's Hiring? Make your job search O (1), not O ( n ).