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Write Optimized Spark Code for Big Data Applications

DZone

Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. In addition, pySpark applications can be tuned to optimize performance and achieve better execution time, scalability, and resource utilization.

Big Data 161
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How Netflix uses eBPF flow logs at scale for network insight

The Netflix TechBlog

By Alok Tiagi , Hariharan Ananthakrishnan , Ivan Porto Carrero and Keerti Lakshminarayan Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. Without having network visibility, it’s difficult to improve our reliability, security and capacity posture.

Network 325
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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. In the previous section, we noted that many distributed query processing algorithms resemble message passing networks. It is conceptually similar to the in-stream processing pipelines.

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.

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What is container orchestration?

Dynatrace

But managing the deployment, modification, networking, and scaling of multiple containers can quickly outstrip the capabilities of development and operations teams. This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. How does container orchestration work?

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Ensuring Performance, Efficiency, and Scalability of Digital Transformation

Alex Podelko

Boris has unique expertise in that area – especially in Big Data applications. To facilitate discussions, in addition to Q&A, we have panels, “Meeting of the Minds” sessions, and networking events. How to select appropriate IT Infrastructure to support Digital Transformation by Boris Zibitsker, BEZNext.

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The Need for Real-Time Device Tracking

ScaleOut Software

If a cyber network agent has observed an unusual pattern of failed login attempts, it needs to alert downstream network nodes (servers and routers) to block the kill chain in a potential attack. The list goes on. The Limitations of Today’s Streaming Analytics. A New Approach: Real-Time Device Tracking.

IoT 78