The Nuclio Serverless-Functions Service
Overview
Iguazio's Nuclio Enterprise Edition serverless-functions framework — a leading open-source project for converging and simplifying data management — is integrated into the platform. Nuclio is a high-performance low-latency framework that supports execution over CPUs or GPUs and a wide array of tools and event triggers, providing users with a complete cloud experience of data services, ML, AI, and serverless functionality — all delivered in a single integrated and self-managed offering at the edge, on-premises ("on-prem"), or in a hosted cloud.
You can use Nuclio functions, for example, to:
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Collect and ingest data into the platform and consume (query) the data on an ongoing basis. Nuclio offers built-in function templates for collecting data from common sources, such as Apache Kafka streams or databases, including examples of data enrichment and data-pipeline processing.
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Run machine-learning models in the serving layer, supporting high throughput on demand and elastic resource allocation.
Nuclio can be easily integrated with Jupyter Notebook, enabling users to develop their entire code (model, feature vector, and application) in Jupyter Notebook and use a single command to deploy the code as a serverless function that runs in the serving layer. For examples, see the platform's tutorial Jupyter notebooks.
Nuclio is provided as a default (pre-deployed) shared single-instance tenant-wide platform service (nuclio).
Users can disable, enable, and restart this service, as well as configure the Docker Registry for storing the Nuclio function images.
See also the Nuclio restrictions in the Software Specifications and Restrictions documentation.
Configuring the Nuclio Service
Pod Priority for User Jobs
Pods (services, or jobs created by those services) can have priorities, which indicate the relative importance of one pod to the other pods on the node. The priority is used for
scheduling: a lower priority pod can be evicted to allow scheduling of a higher priority pod. Pod priority is relevant for all pods created
by the service.
Eviction uses these values to determine what to evict with conjunction to the pods priority. See more details in Interactions between Pod priority and quality of service.
Pod priority is specified through Priority classes, which map to a priority value. The priority values are: High, Medium, Low. The default is Medium.
Configure the default User functions default priority for a service, which is applied to the service itself or to all subsequently created user-jobs in the service's Common Parameters tab, User jobs defaults section, Priority class drop-down list.
The priority applies to the pods of the Nuclio-created functions.
Resources for User Jobs
When you create a pod in a Nuclio function, the pod has default CPU and memory limits. When the job runs, it can consume
resources up to the limits defined. The default limits are set at the service level. You can change the default limit for the service, and
also overwrite the default when creating a function.
See more about Resource Management for Pods and Containers.
When creating a service, set the Memory and CPU in the Common Parameters tab, under User jobs defaults. When creating a function, overwrite the default Memory, CPU, or GPU in the Configuration tab, under Resources.
Node Selection
With node selection, Kubernetes only schedules the pod on nodes that have each of the labels you specify. See Node Selector.
External System Docker Registry
By default, the Nuclio service on the default tenant is configured to work with a predefined, tenant-wide Docker Registry service, which uses a pre-deployed, local, on-cluster Docker Registry. You can change the configuration of the Nuclio service to work with an off-cluster Custom User Docker Registry service. See Docker Registry.