From 1455b19c0384974db8264ca190c7a76957aaeac8 Mon Sep 17 00:00:00 2001 From: rodrigolourencolopes Date: Thu, 17 Oct 2024 14:04:23 +0200 Subject: [PATCH] feat: add new chaos day experiment. 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+ +
+ +| G3 - BasePackage HA | CPU Limit | Memory Limit in GB | +|-----------------------|-----------|--------------------| +| operate | 1 | 1 | +| operate.elasticsearch | 3 | 4.5 | +| optimize | 1 | 1.6 | +| tasklist | 1 | 1 | +| zeebe.broker | 1.5 | 4.5 | +| zeebe.gateway | 0.6 | 1 | +| zeebeAnalytics | 0.2 | 0.3 | +| connectorBridge | 0.4 | 1 | +| **TOTAL** | **8.7** | **14.9** | +[Cluster Plan](https://accounts.cloud.dev.ultrawombat.com/consoleadmin/clusterplans/9b8b444a-636e-48cf-be83-2387a0d11aba) +
+ + + +##### Reduction in Resources for our Minimal Viable Cluster + +| | CPU Reduction (%) | Memory Reduction (%) | +|:----------------------|--------------------:|-----------------------:| +| zeebe.broker | 47.92 | 62.5 | +| zeebe.gateway | 33.33 | -25.0 | +| operate.elasticsearch | 50.00 | 25.0 | + + +Total cluster reduction: + +| | G3-S HA | G3 - BasePackage HA | Reduction (%) | +|:----------------------|--------:|--------------------:|--------------:| +| CPU Limits | 16.58 | 8.7 | 48 | +| Memory Limits | 25.762 | 14.9 | 42 | + + +The process of reducing the hardware requirements was donne initially by +scaling down the resources of the zeebe-broker, gateway and elasticSearch. +The other components were left untouched, as they had no impact in our key +metrics, and were scaled down later in separate experiences to maintain +user experience. + +#### Scaling out the Cluster + +Now for the scaling procedure we intend to see if we can linearly increase +the allocated resources and having a corresponding performance increase, +while keeping the backpressure low, low latency, and user experience. + +For this we started with the G3 - BasePackage HA configuration and +incremented the load again until we saw any increase in backpressure, +capture our key metrics and repeated the process for the cluster +configuration resources respectively multiplied by 2x, 3x, and 4x. + +This means that the resources allocated for our clusters were: + +| | Base 1x | Base 2x | Base 3x | Base 4x | +|:--------------|----------:|----------:|----------:|----------:| +| CPU Limits | 8.7 | 17.4 | 26.1 | 34.8 | +| Memory Limits | 14.9 | 29.8 | 44.7 | 59.6 | + +The results in the table bellow show the performance of our several cluster +configurations: + +| | Base 1x | Base 2x | Base 3x | Base 4x | +|:-------------------------|--------:|--------:|--------:|--------:| +| Process Instances/s | 2 | 6 | 9 | 20 | +| Tasks/s | 40 | 108 | 160 | 360 | +| Average Backpressure | 0% | 5% | 9% | 2% | +| Write-to-Import Latency | 2.8s | 9s | 3s | 2.5min | +| Write-to-Process Latency | 40ms | 200ms | 240ms | 15ms | +| Records Processed | 750 | 2100 | 3700 | 6750 | +| Records Exported | 700 | 1900 | 3200 | 5700 | + +This first observations is that the performance scales particularly well by +just adding more resources to the cluster, particularly for a linear +increase of the resources the performance as measured by tasks completed +increases slightly more than linearly. This might be due to the fact that +for a 2x of the resources the application overhead of the system is +reduced in proportion to the resources added. + +This a very good result as it means that we can scale our system linearly +(at least initially) to handle the expected increase in loads. + +Importantly, the backpressure is kept low, and the write-to-import latency +only increases significantly at the last 4x configuration when kept at this +max rate. This might imply that a 4x configuration the amount records +generated starts to be too much for either elasticSearch or our web apps +that import these records to handle. Some further investigation could be +done here to investigate the bottleneck. + +Another metric also relevant but not shown in this table is the backlog of +records not exported, which kept at almost null through all the experiments +conducted. + +### Bugs found + +During the initial tests, we had several OOM errors in the gateways pods. +After some investigation, we found that this was exclusive to the Camunda 8. +6.0 version, which consumes more memory in the gateway than the previous versions. This +explains why the gateway memory limits were the only resource that was +increased in the new reduced cluster configuration. +