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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. This blog post lists the important database metrics to monitor. Effective monitoring of key performance indicators plays a crucial role in maintaining this optimal speed of operation.

Metrics 130
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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

2022 was an exciting year for Percona Monitoring and Management (PMM). Planning for resources of a PMM Server host instance can be tricky because the numbers can change depending on the DB instances being monitored by PMM. VictoriaMetrics maintains an in-memory cache for mapping active time series into internal series IDs.

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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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The Most Important MySQL Setting

Percona

To illustrate this, I ran the Sysbench-TPCC synthetic benchmark against two different GCP instances running a freshly installed Percona Server for MySQL version 8.0.31 To illustrate this, I ran the Sysbench-TPCC synthetic benchmark against two different GCP instances running a freshly installed Percona Server for MySQL version 8.0.31

Tuning 135
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MySQL Key Performance Indicators (KPI) With PMM

Percona

A monitoring tool like Percona Monitoring and Management (PMM) is a popular choice among open source options for effectively monitoring MySQL performance. In this blog, we will explore various MySQL KPIs that are basic and essential to track using monitoring tools like PMM.

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The Return of the Frame Pointers

Brendan Gregg

The problem is that this system has a default libc that has been compiled without frame pointers, so any stack walking stops at the libc layer, producing a partial stack that's missing the application frames. It shouldn't be 10%, unless it's cache effects. Don't blame the straw, in this case, don't blame the frame pointers.

Java 145
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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