Configure enricher
Last updated
Last updated
This step is optional and the default behaviour will send the original request to the configured routes.
The Turing enricher has the ability to perform arbitrary transformations on the incoming request for feature enrichment. It can deploy any enricher image (implemented by a user) and integrate it with the rest of the system. Currently, there are 3 options available - no enricher, Docker and an external enricher that is coming soon.
Original request will be sent to configured routes without enrichment.
Turing will deploy specified Docker image as a pre-processor and will send original request to it for enrichment.
The request to the enricher is constructed from the request headers to the Router, and an identifier Turing-Req-Id that is uniquely assigned to each request received by the Router.
To configure a Docker enricher, there are 3 sections to fill.
Configure the Docker Container. There are 4 required inputs.
Docker Image: The image is formed of 2 parts. Select the registry to where your image is stored. Following that, enter the name of the image.
Endpoint: Relative URL endpoint of the enricher.
Port: Port number exposed by your container.
Timeout: Request timeout, which when exceeded, the request to enricher will be terminated
Service Account: You can optionally mount a service account for your Docker deployment.
Configure any environment variables required by the Docker container. You need to input the name and corresponding value of each input.
Configure the resources required for the enricher. There are 3 required inputs, with default values provided for each.
CPU: Total amount of CPU available for your enricher.
Memory: Total amount of RAM available for your enricher.
Min/Max Replicas: Min/max number of replicas for your enricher. Scaling of the enricher based on traffic volume will be automatically done for you.
CPU Limit: By default, Turing determines the CPU limits of all deployed components using platform-level configured values. These CPU limits is calculated as a factor of the user-defined CPU request value for each component (e.g. 2x of the CPU request value). However, you can override this platform-level configured value by setting this value explicitly on the UI (as seen above) or via the SDK.
Optionally, modify the autoscaling policy on the enricher.
Metric: The autoscaling metric to monitor. Currently, 4 metrics are supported - Concurrency, RPS, CPU and Memory.
Target: The target value of the chosen metric for each replica, after which autoscaling should be triggered.
Coming soon.
