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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. We designed experimental scenarios inspired by chaos engineering.

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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

What is CDN Architecture?‍CDN CDN architecture serves as a blueprint or plan that guides the distribution of CDN provider PoPs. The two fundamentals of a CDN architecture revolve around distribution and capacity. Five Nines availability or 99.999%, also referred to as "the gold standard" significantly reduces downtime (5.26

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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. All data should be also available for offline analytics in Hive/Iceberg. Our service will be used by a lot of internal UI applications hence the latency for CRUD and search operations must be low.

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Optimizing CDN Architecture: Enhancing Performance and User Experience

IO River

‍What is CDN Architecture?‍CDN ‍CDN architecture serves as a blueprint or plan that guides the distribution of CDN provider PoPs. The two fundamentals of a CDN architecture revolve around distribution and capacity. A lower RTT indicates a faster network response time and happier end users.Â

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Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Redis Data Types and Structures The design of Redis’s data structures emphasizes versatility.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.

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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. Next generation architectures will use CXL3.0 Next generation architectures will use CXL3.0