KNIME Community Hub has become the go-to place for anyone using the KNIME Analytics Platform to upskill, share their expertise, and collaborate on data science.
Users often rely on its vast repository of community-contributed blueprints as building blocks to speed up their analytics projects. They also use KNIME Community Hub as a central place to upload their analytics workflows, keep track of changes, and share them with others in the community.
With the features introduced in the Team plan on KNIME Community Hub recently, the community can now collaborate in small teams and run their workflows easily in the cloud - automatically on a schedule, ad hoc, or as data apps.
In this article, we have gathered some FAQs and answers that users tend to have when they first start exploring these new capabilities. We also discussed many of these in a recent webinar. You can re-watch it anytime here.
KNIME Community Hub FAQs
What is a team on KNIME Community Hub?
The Team plan allows you to create a team on KNIME Hub to collaborate on a project with your colleagues in private spaces, accessible only to the team members. Additionally, you can add execution capabilities to your team enabling workflow execution and automation.
How does billing work?
The total amount you pay is the monthly cost of the team subscription and the cost for execution, based on consumption. You will pay for your team subscription once every month, at the beginning of your billing cycle. On top of the billed subscription you will be charged for execution only based on consumption in the past billing cycle. You will be charged when the execution context is up and running. We offer various execution context sizes, each with different execution power, which will consume different credit amounts per minute. Price per credit is € 0.05, billed per started minute.
What executor configurations are available?
Available configurations, tailored to different processing needs, include: Small (2 vCores - 8 GB RAM) consuming 2 credits per minute, Medium (4 vCores - 16 GB RAM) consuming 4 credits per minute, and Large (8 vCores - 32 GB RAM) consuming 8 credits per minute.
Can I run more than one workflow in an execution context at the same time? Will the cost change?
Yes, you can run multiple workflows in parallel on the same execution context, it does not incur additional charges. Execution performance may vary depending on the execution power of the execution context and the amount and type of workflows executing in parallel.
How is the total execution consumption calculated? How can I control it?
Total execution consumption is based on the time the execution context is active. Its active time depends on multiple factors, including workflow execution time and minimal additional time for context stopping. The execution context starts automatically when a workflow is executed, either ad-hoc or through a schedule. Once all running workflows are finished, the context stops automatically.
How can I optimize the costs and performance?
You can run multiple workflows simultaneously, paying only for the time the execution context is up running. Also, we provide different execution context configurations to optimize both costs and performance.
Can I limit the duration of workflow execution when scheduling deployments?
Yes, maximum execution time can be configured for each workflow schedule, allowing flexibility in managing execution duration. Find more about how to schedule the execution of your workflow and set up its maximum execution time in the KNIME Community Hub Guide.
What kind of workflows can I run?
Once you upload your workflow you will be able to use an execution context to run your workflows. Workflows can be executed ad-hoc, as a data app, or scheduled for automatic execution at specified intervals.
Which extensions are supported on KNIME Community Hub for execution?
All the extensions developed by KNIME are available to run workflows on KNIME Community Hub. Find more information in the KNIME Community Hub Guide.
What is disk space used for? How much disk space should I buy?
Disk space stores team workflows and data files, with a recommended starting point of 30GB, expandable as needed (at extra cost).
What are the supported data sources and targets?
You can up- and download your data directly to the team’s spaces to use them. Additionally you can connect to any data sources accessible by the KNIME Community Hub, for example via our Google or Azure cloud connector nodes.
Can I use the KNIME Python integration? Will there be conflicts with Python virtual environments or Conda environments I use in the KNIME Analytics Platform?
Yes, the Python extension is available. Using our pre-shipped Python environment or the Conda Propagation node should alleviate any concerns about conflicts. Please note that pulling the environment will occur each time the execution context starts up, potentially leading to a slight delay, especially for larger Conda environments.
Start automating your workflows on KNIME Community Hub
Try out the new capabilities on KNIME Community Hub for yourself by subscribing to a Team plan here.