# General capacity of a RPi3

**URL:** https://discourse.nodered.org/t/general-capacity-of-a-rpi3/8965
**Category:** Hardware
**Created:** [14 March 2019 08:55 UTC](https://discourse.nodered.org/t/general-capacity-of-a-rpi3/8965 "2019-03-14T08:55:26Z")
**Posts on this page:** 1
**Showing post:** 3

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### Author: ![Paul-Reed](https://sea2.discourse-cdn.com/flex026/user_avatar/discourse.nodered.org/paul-reed/32/66906_2.png) [@Paul-Reed](https://discourse.nodered.org/u/Paul-Reed)
#### Post date: [14 March 2019 09:44 UTC](https://discourse.nodered.org/t/general-capacity-of-a-rpi3/8965/3 "2019-03-14T09:44:24Z")

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Rather than upgrade at this stage, is your system running optimally?

For example [see this thread](https://discourse.nodered.org/t/ras-pi-supply-voltage/8791) about throttled CPU due to low supply voltage.

Also look at the demands made on the pi, can they be optimised.  
I also run numerous iot interactions + Influx + Grafana + Mosquitto etc, and just one such example of optimisation is;

I monitor power used, solar power generated & power diverted from a 5 second feed, and was then running a query to crunch that data to get energy per day (kWh/d). This was done every 5 seconds. That's almost 52,000 individual power/timeframe calculations, which were then added together, every 5 seconds.

Instead, I moved the power/timeframe calculation to node-RED, and converted the feeds realtime to W/s - just 1 calculation per feed per 5 seconds. This was then saved to Influx.  
To then get kWh/d, all Grafana needs to do is grab the W/s datapoints for previous 24hrs and simply add them together.

This dropped system demands dramatically, and made a significant difference to the speed at which Grafana presented the dashboards.

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