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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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Dynatrace log collection for ARM unlocks power-efficient architecture for your enterprise

Dynatrace

Without observability, the benefits of ARM are lost Over the last decade and a half, a new wave of computer architecture has overtaken the world. ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use.

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Article: Magic Pocket: Dropbox’s Exabyte-Scale Blob Storage System

InfoQ

A horizontally scalable exabyte-scale blob storage system which operates out of multiple regions, Magic Pocket is used to store all of Dropbox’s data. Adopting SMR technology and erasure codes, the system has extremely high durability guarantees but is cheaper than operating in the cloud. By Facundo Agriel

Storage 112
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The state of observability in 2024: Accelerating transformation with AI, analytics, and automation

Dynatrace

Some 85% of technology leaders say the number of tools, platforms, dashboards, and applications they rely on adds to the complexity of managing a multicloud environment. In fact, 81% of technology leaders say the effort their teams invest in maintaining monitoring tools and preparing data for analysis steals time from innovation.

Analytics 180
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. Unlike data warehouses, however, data is not transformed before landing in storage.

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The history of Grail: Why you need a data lakehouse

Dynatrace

These technologies are poorly suited to address the needs of modern enterprises—getting real value from data beyond isolated metrics. Grail architectural basics. The aforementioned principles have, of course, a major impact on the overall architecture. It’s based on cloud-native architecture and built for the cloud.

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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Teams have introduced workarounds to reduce storage costs. Stop worrying about log data ingest and storage — start creating value instead. Limited data availability constrains value creation.

Analytics 223