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Introducing Configurable Metaflow

The Netflix TechBlog

Imagine a ML practitioner on the Netflix Content ML team, sourcing features from hundreds of columns in our data warehouse, and creating a multitude of models against a growing suite of metrics. this could take a few minutes) All packages already cached in s3. All environments already cached in s3. nflxfastdata(2.13.5);nflx(2.13.5);metaboost(0.0.27)

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Measure What You Impact, Not What You Influence

CSS Wizardry

Most metrics are not atomic: FCP, for example, isn’t a metric we can optimise in isolation—it’s a culmination of other more atomic metrics such as connection overhead, TTFB, and more. As noted above, it’s not actually possible to improve certain metrics in their own right. mark ( ' HEAD Start ' ); performance. duration ).

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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. Redis returns a big list of database metrics when you run the info command on the Redis shell. You can pick a smart selection of relevant metrics from these.

Metrics 130
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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 In MySQL, considering the standard storage engine, InnoDB , the data cache is called Buffer Pool. In PostgreSQL, it is called shared buffers.

Tuning 145
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The evolution of single-core bandwidth in multicore processors

John McCalpin

The primary metric for memory bandwidth in multicore processors is that maximum sustained performance when using many cores. This metric is interesting because we don’t always have the luxury of parallelizing every application we run, and our operating systems almost always process each call (e.g., Details in the next blog entry.)

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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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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. Please note that the focus of these tests was around standard metrics gathering and display, we’ll use a future blog post to benchmark some of the more intensive query analytics (QAN) performance numbers. Virtual Memory utilization was averaging 48 GB of RAM.