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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154
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What is a Distributed Storage System

Scalegrid

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130
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Redis vs Memcached in 2024

Scalegrid

Redis Data Types and Structures The design of Redis’s data structures emphasizes versatility. It is designed to cache plain text values, offering fast read and write access to frequently accessed data. Advanced Redis Features Showdown Big data center concept, cloud database, server power station of the future.

Cache 130
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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Finally, we show that Seer can identify application level design bugs, and provide insights on how to better architect microservices to achieve predictable performance. ASPLOS’19.

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

Dynatrace

Data lakehouses deliver the query response with minimal latency. While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses.

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Helios: hyperscale indexing for the cloud & edge – part 1

The Morning Paper

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104
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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

ITOps refers to the process of acquiring, designing, deploying, configuring, and maintaining equipment and services that support an organization’s desired business outcomes. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Performance. What does IT operations do? ITOps vs. AIOps.