In my last post, we discussed the importance of measuring Private Server throughput, using an Alteryx workflow to collect concrete metrics about a Server and use those metrics to guide Server scale out. Although exact performance gains are dependent on many variables (remember, "it depends"), we learned that scaling horizontally by adding additional Queue Workers may have a significant positive impact on total throughput.
In this post, we’ll see just how straightforward it is to expand a Server’s capacity by adding a new Queue Worker. In fact, it requires just five short steps.
The first step in scaling a Private Server is provisioning hardware of sufficient quality to ensure high performance. Using the Alteryx recommendations as a starting point, choose a machine with at least 16 GB memory, 4 physical cores, and, ideally, SSDs.
If possible, prefer physical hardware over virtualized hardware to ensure maximum throughput. If virtualized hardware is your only option, add your new virtual Queue Worker on a Virtual Machine (VM) running on physical hardware that is well within its capacity, and ensure that the VM is dedicated to running the Server only.
In order to communicate securely with the Controller, the new Queue Worker needs the Controller Token, which in turn requires Administrator-level access on the Controller.
After intalling Alteryx, it's time to configure the new Queue Worker.
The final step in scaling out your Private Server is verifying that the new Queue Worker is retrieving marching orders from the Controller and processing workflows correctly.
We’ve seen just how straightforward it is to add capacity to a Private Server, and hopefully your scale-out goes smoothly.
After adding another Queue Worker, how did your Server throughput change? Feel free to share your experiences in the comments, we always enjoy hearing from clients.
Happy New Year to all and thanks for reading. Stay tuned for more Server-related posts in 2016.
Steve is a Distinguished Engineer at Alteryx on the Architecture team, working largely in C++ but dabbling in other languages and technologies. His contributions include backend components of the Alteryx Server, Hadoop connectors (HDFS/Avro), JavaScript integration in both the Designer and Engine (CEF), Spark Direct functionality, Cloud execution for desktop (CEfD), etc. He currently lives on the fringe of Desktop and Cloud, and is committed to bringing our Desktop/Server customers forward into the Cloud.
Steve is a Distinguished Engineer at Alteryx on the Architecture team, working largely in C++ but dabbling in other languages and technologies. His contributions include backend components of the Alteryx Server, Hadoop connectors (HDFS/Avro), JavaScript integration in both the Designer and Engine (CEF), Spark Direct functionality, Cloud execution for desktop (CEfD), etc. He currently lives on the fringe of Desktop and Cloud, and is committed to bringing our Desktop/Server customers forward into the Cloud.
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