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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. All these contribute significantly towards ensuring smooth functioning.

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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

The VictoriaMetrics team has also published some best practices , which can also be referred to while planning for resources for setting up PMM2. VictoriaMetrics maintains an in-memory cache for mapping active time series into internal series IDs. We have tested PMM version 2.33.0

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MySQL Key Performance Indicators (KPI) With PMM

Percona

This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index. query cache: Disable (query_cache_size: 0, query_cache_type:OFF) innodb_adaptive_hash_index: Check adaptive hash index usage to determine its efficiency.

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

Percona

Enhanced User Experience Whether you operate an e-commerce platform, a content management system, or any other application reliant on MySQL, users will notice and appreciate the improved speed and responsiveness. Resource contention emerges when multiple database operations vie for the same system resources simultaneously.

Tuning 52
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Average Page Load Times for 2020 – Are you faster?

MachMetrics

Google’s best practice is to have a speed index under 3 seconds. Google’s best practice is to be below 0.5 However, Google’s best practice is to keep the number of requests below 50, so there is still work to be done. Google’s best practice is to achieve a time under 1.3

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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. Connection pooling: Minimizing connection overhead and improving response times for frequently accessed data by implementing mechanisms for connection pooling and caching strategies.

Tuning 52
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Understanding MySQL Triggers: Exploring How Triggers Impact MySQL Memory Allocation

Percona

This can affect the overall performance of your database system, potentially leading to slower response times. This can introduce maintenance overhead, particularly in large and complex database systems. Testing and Benchmarking : Thoroughly test triggers in a staging environment to evaluate their impact on performance.

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