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5 min. read
Noortje Vollenberg
Last update: 01-12-2020

Improved Machine Insight with Edge Aggregation for Cloud Logging

Machine insight is probably one of the most important assets for improved machine operations. To gain better machine insight, machine builders, system integrators and end-users want to store as much machine data in the cloud as possible. In a later stadium they analyze the machine data to uncover new machine information, which is then used to improve machine processes.

We emphasize information here and not data, because data is just a resource from which we can extract information. It’s a means to an end. Raw machine data says nothing about machine performance. It’s human interpretation that gives meaning to this data.

What is Edge Aggregation?

Imagine that you’re logging several variables for one of the machines you have out in the field. Obviously, you’d like to store as much data as possible to get a grip on your machine process. The ‘problem’ here is that low interval logging results in high amounts of data being transferred to, and stored in, the cloud. This results in higher logging costs per machine.

Edge Aggregation allows the IXrouter to log data at high speed and locally aggregate this data into one data sample, after which it is sent to the cloud for secure storage. This allows you to log accurately, while sending less data to the cloud.

Devices, Edge, Cloud Devices, Edge, Cloud

How to set things up

Once you’ve added Cloud Logging as a premium service to your IXrouter, you can start importing data variables. Data variables include information like data type and address. After adding the variables you can start to set data tags that the IXrouter should log.

This is where Edge Aggregation comes in. You can indicate which value you would like to send to the cloud using formulas. For example the last value that you’ve logged during the given time interval (e.g. at the end of every minute, ten minutes or hour). With Edge Aggregation you can send out the minimum, maximum and average value of a data tag. The IXrouter will continue logging your variable during the given interval. At the end of the interval time, the IXrouter will apply the set formula on the collected data and send out the desired aggregated value to the cloud.

The example below explains the Edge Aggregator functionality with all available formulas included. Your Cloud Logging dashboard will only show the aggregated value for your 10 second interval.

Edge aggregation interval Edge aggregation interval

The advantages of Edge Aggregation

One of the advantages is that you can send less data to the cloud, with the same or even increased information value. This means you save cost on the information that you wish to store. Take the following example. You can either log all your production data for an entire day, send everything to the cloud, and use formulas there to get your average production for the day. Or you can go with the other, cheaper option. Simply let the IXrouter determine the average at the end of an interval time, and just send that one resulting sample to the cloud. You can even aggregate one data tag multiple times, which allows you to show the minimum, maximum and average value in one graph.

The main disadvantage of Edge Aggregation for Cloud Logging

Even though Edge Aggregation allows you to better store more information with less data usage, this may not always be seen as an advantage. If you’re interested in data peaks, for example, and you use Edge Aggregation to send the maximum value, the IXrouter (edge gateway) will do exactly as it is told. It will scan the collected data and send out the maximum value to the cloud. If you have a higher interval time, this means that you won’t be able to pinpoint exactly when the peak moment took place. Let’s say that you have an interval time of one hour. The IXrouter will send out the maximum value that occurred during that hour. But when exactly did the peak moment occur within that one hour time frame? You don’t know.

Of course this isn’t of importance when you are aggregating an average value, but for minimum or maximum values you may miss out on valuable information. So, make sure you pay close attention to the desired information you wish to extract from your logged data!

Be sure to check out our Cloud Logging page to find out more on the possibilities and advantages of Cloud Logging or test it out yourself and start your free Cloud Logging trial today!

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or download the case study of Cloud Logging.