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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. The MPP system leverages a shared-nothing architecture to handle multiple operations in parallel.

Big Data 321
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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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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

The Netflix TechBlog

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. I developed many batch and real-time data pipelines using open source technologies for AOL Advertising and eBay. What is your favorite project?

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Path to NoOps part 1: How modern AIOps brings NoOps within reach

Dynatrace

Early implementations of NoOps were just ‘lift and shift’ efforts that replicated existing systems to the cloud. AIOps , a term coined by Gartner in 2016, combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination.

DevOps 206
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What is IT automation?

Dynatrace

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. When monitoring tools release a stream of alerts, teams can easily identify which ones are false and assess whether an event requires human intervention.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being evolved and optimized to meet and exceed customer and product expectations. This technique facilitates validation on multiple fronts.

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