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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Such frameworks support software engineers in building highly scalable and efficient applications that process continuous data streams of massive volume. ShuffleBench i s a benchmarking tool for evaluating the performance of modern stream processing frameworks. We designed experimental scenarios inspired by chaos engineering.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. These essential data points heavily influence both stability and efficiency within the system.

Metrics 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. Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. It is designed to cache plain text values, offering fast read and write access to frequently accessed data.

Cache 130
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Maximizing Performance of AWS RDS for MySQL with Dedicated Log Volumes

Percona

A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables. This separation aims to streamline transaction write logging, improving efficiency and consistency. 2xlarge c5.2xlarge MySQL 8.0.31 2xlarge c5.2xlarge MySQL 8.0.31

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Plan Your Multi Cloud Strategy

Scalegrid

They can also bolster uptime and limit latency issues or potential downtimes. Choosing the Right Cloud Services Choosing the right cloud services is crucial in developing an efficient multi cloud strategy. They simplify how you orchestrate everything across the diverse ecosystem of cloud services.

Strategy 130
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What Is a Workload in Cloud Computing

Scalegrid

This article analyzes cloud workloads, delving into their forms, functions, and how they influence the cost and efficiency of your cloud infrastructure. Simply put, it’s the set of computational tasks that cloud systems perform, such as hosting databases, enabling collaboration tools, or running compute-intensive algorithms.

Cloud 130
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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. In early January a related paper was published by Satoshi Matsuoka et. petaflops, which is 0.8%