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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154
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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. Auto Remediation generates recommendations by considering both performance (i.e., Multi-objective optimizations.

Tuning 210
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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics.

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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Finally, we show that Seer can identify application level design bugs, and provide insights on how to better architect microservices to achieve predictable performance. ASPLOS’19.

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Driving down the cost of Big-Data analytics - All Things Distributed

All Things Distributed

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 111
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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

ITOps refers to the process of acquiring, designing, deploying, configuring, and maintaining equipment and services that support an organization’s desired business outcomes. The primary goal of ITOps is to provide a high-performing, consistent IT environment. Performance. What does IT operations do?

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AIOps observability adoption ascends in healthcare

Dynatrace

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.