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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：

  1. 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。
  2. 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。
  3. 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.

prometheus-benchmark

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​

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