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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. Component Design. There are two major processes which gets executed when a user posts a photo on Instagram. API Design. Problem Statement. Architecture.

Design 334
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Exploring Parallel Processing: SIMD vs. MIMD Architectures

DZone

In the landscape of computer architecture, two prominent paradigms shape the realm of parallel processing: SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction, Multiple Data) architectures. This approach enables efficient processing of large datasets by applying the same operation to multiple elements concurrently.

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Batch vs. Real-Time Processing: Understanding the Differences

DZone

The decision between batch and real-time processing is a critical one, shaping the design, architecture, and success of our data pipelines. Understanding the key distinctions between these two processing paradigms is crucial for organizations to make informed decisions and harness the full potential of their data.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.

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Data Mesh?—?A Data Movement and Processing Platform @ Netflix

The Netflix TechBlog

A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A stream processing) is one of the key factors that enable Netflix to maintain its leading position in the competition of entertaining our users.

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Best Practices for Batch Processing in IBM App Connect Enterprise as a Service

DZone

Batch processing is a capability of App Connect that facilitates the extraction and processing of large amounts of data. Sometimes referred to as data copy , batch processing allows you to author and run flows that retrieve batches of records from a source, manipulate the records, and then load them into a target system.

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Practical business process monitoring for real-time business observability

Dynatrace

One of the more popular use cases is monitoring business processes, the structured steps that produce a product or service designed to fulfill organizational objectives. The Business Flow app Business Flow, built with AppEngine, simplifies the configuration, monitoring, and analysis of business processes.