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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130
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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. When the server receives a request for an action (post, like etc.) The streaming data store makes the system extensible to support other use-cases (e.g. System Components.

Design 334
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Building Resiliency With Effective Error Management

DZone

Building resilient systems requires comprehensive error management. Errors could occur in any part of the system / or its ecosystem and there are different ways of handling these e.g. Datacenter - data center failure where the whole DC could become unavailable due to power failure, network connectivity failure, environmental catastrophe, etc.

Hardware 243
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment.

Big Data 321
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Master MySQL Point in Time Recovery

Scalegrid

This article delivers a practical roadmap for using backups and binary logs to achieve accurate MySQL recovery, detailed steps for setting up your server, and tips for managing recovery and backups effectively without overwhelming you with complexity. Insert the ‘log-bin’ directive into your server’s configuration file (my.cnf or my.ini).

Database 162
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Redis vs Memcached in 2024

Scalegrid

Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load. This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice.

Cache 130
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Why growing AI adoption requires an AI observability strategy

Dynatrace

An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance. AI requires more compute and storage. Training AI data is resource-intensive and costly, again, because of increased computational and storage requirements. AI performs frequent data transfers.

Strategy 230