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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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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

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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., Using network queue depths alone is enough to signal a large fraction of QoS violations, although smaller than when the full instrumentation is available. ASPLOS’19. Distributed tracing and instrumentation.

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Redis vs Memcached in 2024

Scalegrid

Benchmarking Cache Speed Memcached is optimized for high read and write loads, making it highly efficient for rapid data access in a basic key-value store. Advanced Redis Features Showdown Big data center concept, cloud database, server power station of the future. Data transfer technology.

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Web Performance Bookshelf

Rigor

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. High Performance Browser Networking. Fail, and you can kiss your customers and profits goodbye.” Time is Money.

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World’s Top Web Performance Leaders To Watch

Rigor

One of the top players in web performance, Ilya is a web performance engineer at Google, co-chair of the W3C Web Performance Working Group , and author of High Performance Browser Networking. Would you like to be a part of Big Data and this incredible project? MDN (Mozilla Developers Network) @MozDevNet. Fastly @ fastly.