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Best Practices for Designing Resilient APIs for Scalability and Reliability

DZone

Over the last 15+ years, Ive worked on designing APIs that are not only functional but also resilient able to adapt to unexpected failures and maintain performance under pressure. In this article, Ill share practical strategies for designing APIs that scale, handle errors effectively, and remain secure over time.

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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.

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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. Architecture. Component Design. There are two major processes which gets executed when a user posts a photo on Instagram. API Design. Problem Statement.

Design 334
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Ready for changes with Hexagonal Architecture

The Netflix TechBlog

by Damir Svrtan and Sergii Makagon As the production of Netflix Originals grows each year, so does our need to build apps that enable efficiency throughout the entire creative process. We decided to build our app based on principles behind Hexagonal Architecture and Uncle Bob’s Clean Architecture.

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Grafana Loki Fundamentals and Architecture

DZone

It is designed for simplicity and cost-efficiency. Logs can also be transformed appropriately for presentation, for example, or further pipeline processing. Grafana Loki is a horizontally scalable, highly available log aggregation system. Loki can provide a comprehensive log journey.

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New integrations announced at AWS re:Invent enhance cloud performance, security, and automation

Dynatrace

This year’s AWS re:Invent will showcase a suite of new AWS and Dynatrace integrations designed to enhance cloud performance, security, and automation. This integration simplifies the process of embedding Dynatrace full-stack observability directly into custom Amazon Machine Images (AMIs).

AWS 298
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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.