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DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. The evolution of DevOps automation Since the concept of DevOps emerged around 2007 and 2008 in response to pain points with Agile development, DevOps automation has been continuously evolving. But it doesn’t stop there.

DevOps 209
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World’s Top Web Performance Leaders To Watch

Rigor

Reading time 16 min Whether you’re a web performance expert, an evangelist for the culture of performance, a web engineer incorporating performance into your process, or someone new to the web performance entirely, you probably identify as curious, excited about new ideas, and always learning. Rick Byers.

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Is MongoDB Open Source? Is Planet Earth Flat?

Percona

MongoDB started out in 2007 as 10gen, a New York-based company looking to create a Platform as a Service (PaaS) solution. They came up with a horizontally scalable NoSQL database. Atlas revenue grew 82% year-over-year, representing 60% of revenue. ” Nothing nefarious there. Just a positive outlook for investors.

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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

Egnyte is a secure Content Collaboration and Data Governance platform, founded in 2007 when Google drive wasn't born and AWS S3 was cost-prohibitive. Infrastructure Optimization. Egnyte was founded in 2007. Our only option was to roll up our sleeves and build basic cloud file system components such as object store ourselves.

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Transforming enterprise integration with reactive streams

O'Reilly Software

Build a more scalable, composable, and functional architecture for interconnecting systems and applications. Software today is not typically a single program—something that is executed by an operator or user, producing a result to that person—but rather a service : something that runs for the benefit of its consumers, a provider of value.

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Scaling Media Machine Learning at Netflix

The Netflix TechBlog

Our goal in building a media-focused ML infrastructure is to reduce the time from ideation to productization for our media ML practitioners. Even after gaining access, one needed to deal with the challenges of homogeneity across different assets in terms of decoding performance, size, metadata, and general formatting.

Media 290
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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. Reloaded was well-architected, providing good stability, scalability, and a reasonable level of flexibility. Video Inspection Service (VIS): This service takes a mezzanine as the input and performs various inspections.