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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. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures. On MySQL, we saw a 1.5X

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5.5 mm in 1.25 nanoseconds

Randon ASCII

That meant I started having regular meetings with the hardware engineers who were working with IBM on the CPU which gave me even more expertise on this CPU, which was critical in helping me discover a design flaw in one of its instructions , and in helping game developers master this finicky beast. I wrote a lot of benchmarks.

Cache 126
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MySQL Key Performance Indicators (KPI) With PMM

Percona

Indexing efficiency Monitoring indexing efficiency in MySQL involves analyzing query performance, using EXPLAIN statements, utilizing performance monitoring tools, reviewing error logs, performing regular index maintenance, and benchmarking/testing. This KPI is also directly related to Query Performance and helps improve it.

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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 reduction in latency ensures that applications and websites provide a more rapid and responsive user experience. This does not apply to read (SELECT) traffic.

Tuning 52
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Why OpenStack is like a Crowdfunded Viking Movie

VoltDB

Hardware Optimizers” want to get the maximum utilization out of hardware. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. Latency Optimizers” – need support for very large federated deployments.

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Why OpenStack is like a Crowdfunded Viking Movie

VoltDB

Hardware Optimizers” want to get the maximum utilization out of hardware. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. Latency Optimizers” – need support for very large federated deployments.