Remove Efficiency Remove Scalability Remove Software Architecture
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Building Scalable Software Solutions for Display Manufacturing Automation

DZone

As display manufacturing continues to evolve, the demand for scalable software solutions to support automation has become more critical than ever. Scalable software architectures are the backbone of efficient and flexible production lines, enabling manufacturers to meet the increasing demands for innovative display technologies.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

Without an efficient data retention strategy, this approach may struggle to scale effectively. Rollup Pipeline: Each Counter-Rollup server operates a rollup pipeline to efficiently aggregate counts across millions of counters. In the following sections, we will share key details on how efficient aggregations are achieved.

Latency 251
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.

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What Is RabbitMQ: Key Features and Uses

Scalegrid

It employs the Advanced Message Queuing Protocol (AMQP) to provide reliable, scalable message passing, crucial for modern applications dealing with large-scale, complex data flows. Additionally, the low coupling between sender and receiver applications allows for greater flexibility and scalability in the system.

IoT 130
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What is RabbitMQ Used For

Scalegrid

It offers benefits like increased reliability, efficient resource utilization, decoupling of components, and support for multiple programming languages. RabbitMQ allows consumer programs to wait and receive messages from producers, ensuring efficient message delivery and processing.

IoT 130
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ABAC on SpiceDB: Enabling Netflix’s Complex Identity Types

The Netflix TechBlog

Netflix is always looking for security, ergonomic, or efficiency improvements, and this extends to authorization tools. Over time, each node caches a subset of subproblems to support a distributed cache, reduce the datastore load, and achieve SpiceDB’s horizontal scalability.

Cache 255
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MLOps and DevOps: Why Data Makes It Different

O'Reilly

Cloud-based data warehouses, such as Snowflake , AWS’ portfolio of databases like RDS, Redshift or Aurora , or an S3-based data lake , are a great match to ML use cases since they tend to be much more scalable than traditional databases, both in terms of the data set sizes as well as query patterns. Software Architecture.

DevOps 145