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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. A reduced throughput could generally indicate that the server gets fewer queries.

Metrics 130
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. This not only enhances performance but also enables you to make more efficient use of your hardware resources, potentially resulting in cost savings on infrastructure.

Tuning 52
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

PostgreSQL performance optimization aims to improve the efficiency of a PostgreSQL database system by adjusting configurations and implementing best practices to identify and resolve bottlenecks, improve query speed, and maximize database throughput and responsiveness. Why is PostgreSQL performance tuning important?

Tuning 52
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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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Ten years of page bloat: What have we learned?

Speed Curve

And we need to have strategies in place to understand and manage our pages. These numbers should not be taken as a benchmark for your own site. You can see this by looking at the synthetic test result for Sears.com (again, available via our Industry Benchmarks ). Don't assume hardware and networks will mitigate page bloat.

Mobile 145
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The Ultimate Guide to MySQL Partitions

Percona

Each partition holds data that falls within a specific range, optimizing data handling and query speed. This version also notably integrates native backing for range and list partitioning of spatial indexes, amplifying geospatial query speed for substantial datasets. Additionally, MySQL 8.0

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Beyond data and model parallelism for deep neural networks

The Morning Paper

To me that means the “simple” object access protocol, but not here: We introduce SOAP, a more comprehensive search space of parallelization strategies for DNNs that includes strategies to parallelize a DNN in the Sample, Operator, Attribute, and Parameter dimensions. compared to state-of-the-art approaches.

Network 81