Whizard 性能测试说明
- 性能测试工具
  - 性能测试关键指标描述
  - 性能测试报告

Whizard 性能测试说明

对于 Whizard 的性能测试，通常可以从以下几个方面入手：

数据接收性能：测试 Whizard 在数据接受方面的性能表现，包括数据摄入速度、数据处理时间、数据存储性能等方面。
数据查询性能：测试 Whizard 在查询和分析数据方面的性能表现，包括查询响应时间、查询吞吐量、查询结果的准确性等方面。
可扩展性测试：测试 Whizard 在处理多租户数据时的性能表现，包括水平扩展性和租户管理等方面。

性能测试工具

Prometheus-benchmark allows testing data ingestion and querying performance for Prometheus-compatible systems on production-like workload.

The prometheus-benchmark scrapes metrics from node_exporter and pushes the scraped metrics to the configured Prometheus-compatible remote storage systems. These systems must support Prometheus remote_write API for measuring data ingestion performance. Optionally these systems may support Prometheus querying API for measuring query performance.

The helm chart deploys the following pods:

vmagent with the following containers:
- nodeexporter - collects real metrics from Kubernetes node where it runs.
- nginx - caches responses from nodeexporter for 1 second in order to reduce load on it when scraping big number of targets.
- vmagent-config-updater - generates config for target scraping. It is also responsible for generating time series churn rate via periodic updating of the generated targets.
- vmagent - scrapes nodeexporter metrics via nginx for targets generated by vmagent-config-updater.
vmalert with the following containers:
- vmalert - periodically executes alerting rules (aka read queries) against the testes remote storage.
- alertmanager - receives notifications from vmalert. It is configured as a blackhole for the received notifications. vmalert pod is optional - it is used for generating read query load.
vmsingle - this pod runs a single-node VictoriaMetrics, which collects metrics from vmagent and vmalert pods, so they could be analyzed during benchmark execution.

性能测试关键指标描述

Data ingestion rate
99th percentile for the duration to execute queries
99th percentile for the duration to push the collected data to the configured remote storage systems

性能测试报告

当前版本：

历史版本: