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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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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. It depends upon your application workload and its business logic.

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How to Assess MySQL Performance

HammerDB

As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components. For the network, we can use Iperf to assess the network bandwidth between the client and the database server to ensure it will be enough to meet our peak requirement.

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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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What Adrian Did Next?—?Part 2?—?Sun Microsystems

Adrian Cockcroft

The early days at Sun Cambridge were special, I absorbed a lot about networking and the technical side of the role from my fellow systems engineer Martin Baines, and we were driving all over the region in cool company cars (I had a Citroen BX 16V) selling a really hot product.

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

The Morning Paper

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. When available, it can use hardware level performance counters.

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Why OpenStack is like a Crowdfunded Viking Movie

VoltDB

It was – like the hypothetical movie I describe above – more than a little bit odd, as you could leave a session discussing ever more abstract layers of virtualization and walk into one where they emphasized the critical importance of pinning a network interface to a specific VM for optimal performance. Where VoltDB fits. Very Well!”