Fusion Microservices

Table of Contents

Overview
Ports used by Fusion
Transport Layer Security (TLS)

Overview

The table below lists the Fusion microservices deployed by the Helm chart.

Fusion is a complex distributed application composed of many stateful and stateless services designed to support demanding search-oriented workloads at high scale.

For Docker image versions associated with microservices, see the list of Docker images and versions for each Fusion release.

Microservice Required for Fusion Protocol Deployment or StatefulSet Node Pool Assignment Autoscaling Supported Description

Microservice	Required for Fusion	Protocol	Deployment or StatefulSet	Node Pool Assignment	Autoscaling Supported	Description
`admin`	Yes	REST/HTTP	Deployment	system	Not required. Minimum of 1, but 2 pods are recommended for high availability.	Exposes endpoints for admin tasks, such as creating applications and running jobs.
`admin-ui`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Serves static Web assets for the admin UI.
`async-parsing`	No	HTTP	Deployment	system	Not required. One pod is enough for most clusters.	Separates document crawling and parsing.
`auth-ui`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Serves static Web assets for the login form.
`connector-plugin-<connector_plugin>`	No	HTTP/TCP	Deployment	analytics or system	Yes (CPU or custom metric).	Deployment for each connector plugin type. Note: There is a base deployment, connector-plugin with 0 replicas. This is used as a deployment template for each connector plugin type. It should not be deleted or scaled.
`connectors`	No	REST/HTTP	Deployment	analytics or system	Not required. One pod is enough for most clusters.	Routes REST API requests to classic-rest-service and connectors-rpc.
`connectors-backend`	No	gRPC	Deployment	analytics or system	Yes (CPU or custom metric).	gRPC service for managing SDK-based connector plugins.
`connectors-classic`	No	REST/HTTP	StatefulSet	analytics or system	Not supported.	REST service for supporting non-RPC connector plugins.
`{fusion-namespace}-argo-argo-ui`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Stores logs and prior Argo workflow runs.
`{fusion-namespace}-kafka`	No	HTTP	StatefulSet	system	placeholder	placeholder
`{fusion-namespace}-kafka-headless`	No	HTTP	StatefulSet	system	placeholder	placeholder
`{fusion-namespace}-ml-model-service-ambassador`	No	Web	Deployment	system	Not required. Minimum of 1, but 2 pods are recommended for high availability.	Load balancing and proxy for Seldon Core deployments.
`{fusion-namespace}-ml-model-service-mysql`	No	Web	Deployment	system	Not required. Minimum of 1, but 2 pods are recommended for high availability.	Load balancing and proxy for Seldon Core deployments.
`{fusion-namespace}-reverse-search-headless`	Yes	HTTP	StatefulSet	At least 3 nodes in search, 2 in analytics, and 2 in system	Yes (CPU or custom metric).	Search engine.
`{fusion-namespace}-reverse-search-svc`	Yes	HTTP	StatefulSet	At least 3 nodes in search, 2 in analytics, and 2 in system	Yes (CPU or custom metric).	Search engine.
`{fusion-namespace}-solr-headless`	Yes	HTTP	StatefulSet	At least 3 nodes in search, 2 in analytics, and 2 in system	Yes (CPU or custom metric).	Search engine.
`{fusion-namespace}-solr-svc`	Yes	HTTP	StatefulSet	At least 3 nodes in search, 2 in analytics, and 2 in system	Yes (CPU or custom metric).	Search engine.
`{fusion-namespace}-zookeeper`	Yes	TCP	StatefulSet	system	No. You need to run 1, 3, or 5 ZooKeeper pods to keep quorum. Do not use HPA for scaling ZooKeeper.	Stores centralized configuration and performs distributed coordination tasks.
`{fusion-namespace}-zookeeper-headless`	Yes	TCP	StatefulSet	system	No. You need to run 1, 3, or 5 ZooKeeper pods to keep quorum. Do not use HPA for scaling ZooKeeper.	Stores centralized configuration and performs distributed coordination tasks.
`indexing`	Yes	REST/HTTP	Deployment	search or analytics depending on write-volume	Yes (CPU or custom metric).	Processes indexing requests.
`insights`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Serves the App Insights UI
`job-launcher`	No	REST/HTTP	Deployment	analytics	Not required. One pod is enough for most clusters.	Configures and launches the Spark driver pod for running Spark jobs
`job-rest-server`	No	REST/HTTP	Deployment	analytics	Not required. One pod is enough for most clusters.	Performs admin tasks for creating and running Spark jobs.
`milvus`	No	REST/HTTP	Deployment	analytics or system	Not required. One pod is enough for most clusters.	Dense Vector Search Engine for ML models active.
`ml-model-grpc`	No	REST/HTTP and gRPC	Deployment	search	Yes (CPU or custom metric).	Exposes gRPC endpoints for generating predictions from ML models.
`ml-model-service`	No	REST/HTTP and gRPC	Deployment	search	Yes (CPU or custom metric).	Exposes gRPC endpoints for generating predictions from ML models.
`pm-ui`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Serves static Web assets for the Predictive Merchandiser app.
`proxy / api-gateway`	Yes	HTTP	Deployment	search	Not required. Minimum of 1, but 2 pods are recommended for high availability.	Performs authentication, authorization, and traffic routing.
`query`	Yes	REST/HTTP	Deployment	search	Yes (CPU or custom metric).	Processes query requests.
`rules-ui`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Serves static Web assets for the Rules UI.
`seldon-webhook-service`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Maintains Seldon Core deployments for ML model serving active.
`templating`	No	Web	Deployment	system	Not required. One pod is enough for most clusters.	Retrieves and renders Predictive Merchandiser templates.
`webapps`	No	REST/HTTP	Deployment	system	Not required. One pod is enough for most clusters.	Serves App Studio-based Web apps.

admin

Yes

REST/HTTP

Deployment

system

Not required. Minimum of 1, but 2 pods are recommended for high availability.

Exposes endpoints for admin tasks, such as creating applications and running jobs.

admin-ui

Web

Deployment

system

Not required. One pod is enough for most clusters.

Serves static Web assets for the admin UI.

async-parsing

HTTP

Deployment

system

Not required. One pod is enough for most clusters.

Separates document crawling and parsing.

auth-ui

Web

Deployment

system

Not required. One pod is enough for most clusters.

Serves static Web assets for the login form.

connector-plugin-<connector_plugin>

HTTP/TCP

Deployment

analytics or system

Yes (CPU or custom metric).

Deployment for each connector plugin type. Note: There is a base deployment, connector-plugin with 0 replicas. This is used as a deployment template for each connector plugin type. It should not be deleted or scaled.

connectors

REST/HTTP

Deployment

analytics or system

Not required. One pod is enough for most clusters.

Routes REST API requests to classic-rest-service and connectors-rpc.

connectors-backend

gRPC

Deployment

analytics or system

Yes (CPU or custom metric).

gRPC service for managing SDK-based connector plugins.

connectors-classic

REST/HTTP

StatefulSet

analytics or system

Not supported.

REST service for supporting non-RPC connector plugins.

{fusion-namespace}-argo-argo-ui

Web

Deployment

system

Not required. One pod is enough for most clusters.

Stores logs and prior Argo workflow runs.

{fusion-namespace}-kafka

HTTP

StatefulSet

system

placeholder

{fusion-namespace}-kafka-headless

HTTP

StatefulSet

system

placeholder

{fusion-namespace}-ml-model-service-ambassador

Web

Deployment

system

Not required. Minimum of 1, but 2 pods are recommended for high availability.

Load balancing and proxy for Seldon Core deployments.

{fusion-namespace}-ml-model-service-mysql

Web

Deployment

system

Not required. Minimum of 1, but 2 pods are recommended for high availability.

Load balancing and proxy for Seldon Core deployments.

{fusion-namespace}-reverse-search-headless

Yes

HTTP

StatefulSet

At least 3 nodes in search, 2 in analytics, and 2 in system

Yes (CPU or custom metric).

Search engine.

{fusion-namespace}-reverse-search-svc

Yes

HTTP

StatefulSet

At least 3 nodes in search, 2 in analytics, and 2 in system

Yes (CPU or custom metric).

Search engine.

{fusion-namespace}-solr-headless

Yes

HTTP

StatefulSet

At least 3 nodes in search, 2 in analytics, and 2 in system

Yes (CPU or custom metric).

Search engine.

{fusion-namespace}-solr-svc

Yes

HTTP

StatefulSet

At least 3 nodes in search, 2 in analytics, and 2 in system

Yes (CPU or custom metric).

Search engine.

{fusion-namespace}-zookeeper

Yes

TCP

StatefulSet

system

No. You need to run 1, 3, or 5 ZooKeeper pods to keep quorum. Do not use HPA for scaling ZooKeeper.

Stores centralized configuration and performs distributed coordination tasks.

{fusion-namespace}-zookeeper-headless

Yes

TCP

StatefulSet

system

No. You need to run 1, 3, or 5 ZooKeeper pods to keep quorum. Do not use HPA for scaling ZooKeeper.

Stores centralized configuration and performs distributed coordination tasks.

indexing

Yes

REST/HTTP

Deployment

search or analytics depending on write-volume

Yes (CPU or custom metric).

Processes indexing requests.

insights

Web

Deployment

system

Not required. One pod is enough for most clusters.

Serves the App Insights UI

job-launcher

REST/HTTP

Deployment

analytics

Not required. One pod is enough for most clusters.

Configures and launches the Spark driver pod for running Spark jobs

job-rest-server

REST/HTTP

Deployment

analytics

Not required. One pod is enough for most clusters.

Performs admin tasks for creating and running Spark jobs.

milvus

REST/HTTP

Deployment

analytics or system

Not required. One pod is enough for most clusters.

Dense Vector Search Engine for ML models active.

ml-model-grpc

REST/HTTP and gRPC

Deployment

Yes (CPU or custom metric).

Exposes gRPC endpoints for generating predictions from ML models.

ml-model-service

REST/HTTP and gRPC

Deployment

Yes (CPU or custom metric).

Exposes gRPC endpoints for generating predictions from ML models.

pm-ui

Web

Deployment

system

Not required. One pod is enough for most clusters.

Serves static Web assets for the Predictive Merchandiser app.

proxy / api-gateway

Yes

HTTP

Deployment

Not required. Minimum of 1, but 2 pods are recommended for high availability.

Performs authentication, authorization, and traffic routing.

query

Yes

REST/HTTP

Deployment

Yes (CPU or custom metric).

Processes query requests.

rules-ui

Web

Deployment

system

Not required. One pod is enough for most clusters.

Serves static Web assets for the Rules UI.

seldon-webhook-service

Web

Deployment

system

Not required. One pod is enough for most clusters.

Maintains Seldon Core deployments for ML model serving active.

templating

Web

Deployment

system

Not required. One pod is enough for most clusters.

Retrieves and renders Predictive Merchandiser templates.

webapps

REST/HTTP

Deployment

system

Not required. One pod is enough for most clusters.

Serves App Studio-based Web apps.

Ports used by Fusion

Below you will find the list of pod ports for intra-cluster communications.

Service	Port
`admin`	8765
`admin-ui`	8080
`async-parsing`	9005
`argo-argo-ui`	2746
`auth-ui`	8080
`connector-plugin`	9020, 5701
`connectors`	9010
`connectors-backend`	8771
`connectors-classic`	9000
`{fusion-namespace}-argo-argo-ui`	2746
`{fusion-namespace}-kafka`	9092
`{fusion-namespace}-kafka-headless`	9092, 9093
`{fusion-namespace}-ml-model-service-ambassador`	80, 443
`{fusion-namespace}-ml-model-service-mysql`	3306
`{fusion-namespace}-reverse-search-headless`	8983
`{fusion-namespace}-reverse-search-svc`	8983
`{fusion-namespace}-solr-headless`	8983
`{fusion-namespace}-solr-svc`	8983
`{fusion-namespace}-zookeeper`	2181, 2281
`{fusion-namespace}-zookeeper-headless`	2181, 3888, 2888, 2281
`indexing`	8765
`insights`	8080
`job-launcher`	8083
`job-rest-server`	8081
`milvus`	19530, 19121
`ml-model-grpc`	6565
`ml-model-service`	8086
`pm-ui`	8080
`proxy`	6764
`query`	8787
`rules-ui`	8080
`seldon-webhook-service`	443
`templating`	5250
`webapps`	8780

Transport Layer Security (TLS)

Fusion microservices can be configured to use Transport Layer Security (TLS).

When enabled, Fusion generates a TLS certificate for each pod when the pod starts. This allows Fusion to use the Kubernetes endpoints API to reach each pod by its IP address and perform load balancing, circuit breaking, and retries in the Fusion microservices.