Remove Benchmarking Remove Cache Remove Hardware Remove Testing
article thumbnail

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. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

Metrics 130
article thumbnail

Impact of Querying Table Information From information_schema

Percona

A lot of useful information can be retrieved from this schema, for example, table metadata and foreign key relations, but trying to query I_S can induce performance degradation if your server is under heavy load, as shown in the following example test. The same tests have been executed in Percona Server for MySQL 5.7

Cache 105
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

How to Assess MySQL Performance

HammerDB

Therefore, before we attempt to measure our database performance, we should know the system or cloud instance to be tested in detail. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench. This allows us to know our operating environment and its capability. 4.22 %usr 38.40

article thumbnail

PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Key areas include: Configuration parameter tuning : This tuning involves altering variables such as memory allocation, disk I/O settings, and concurrent connections based on specific hardware and requirements. This not only results in cost savings by minimizing hardware requirements but also has the potential to decrease cloud expenses.

Tuning 52
article thumbnail

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.

article thumbnail

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.

article thumbnail

The Return of the Frame Pointers

Brendan Gregg

Only in extreme circumstances does the cost (in processor time and I-cache footprint) translate to a tangible benefit - circumstances which usually resort to hand-coded assembly anyway. It shouldn't be 10%, unless it's cache effects. And for leaf routines (which never establish a frame), this is a non-issue.

Java 145