Product Selector

Fusion 5.9
    Fusion 5.9

    Fusion Microservices

    Fusion is comprised of microservices that drive features and functionality within a deployment. The services running in your deployment depend on the version of Fusion and the features you have enabled.

    Get deployment details

    You can view your deployment details using kubectl.

    1. First, verify that you have access to your cluster, replacing the example values with your parameters. This example is for a Fusion instance deployed using GKE.

      gcloud container clusters get-credentials EXAMPLE-CLUSTER --region EXAMPLE-REGION --project EXAMPLE-PROJECT

    2. Get the ports and services:

      kubectl get svc -n EXAMPLE-NAME

    3. Get the StatefulSets:

      kubectl get statefulsets -n EXAMPLE-NAME

    4. Get the deployments:

      kubectl get deploy -n EXAMPLE-NAME

    Overview

    The table below lists the Fusion microservices deployed by the Helm chart. It also include Kubernetes services that manage traffic to microservices.

    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.

    Microservices

    Below is a list of microservices used in Fusion 5.10.

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

    admin-ui

    No

    Web

    Deployment

    system

    Not required. One pod is enough for most clusters.

    Serves static Web assets for the admin UI.

    apps-manager

    Yes

    REST/HTTP

    Deployment

    analytics or system

    Not required. One pod is enough for most clusters.

    Tracks Fusion entitlement license and consumption.

    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 connectors-classic 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. This microservice was previously named classic-rest-service.

    fusion-admin

    Yes

    REST/HTTP

    Deployment

    system

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

    Exposes endpoints for admin tasks, such as creating applications and running jobs. This microservice was previously named admin.

    fusion-indexing

    Yes

    REST/HTTP

    Deployment

    search or analytics depending on write-volume

    Yes (CPU or custom metric).

    Processes indexing requests. This microservice was previously named indexing.

    {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

    Required. One pod is enough for most clusters.

    Contains incoming data for Solr.

    {fusion-namespace}-kafka-headless

    No

    HTTP

    StatefulSet

    system

    Required. One pod is enough for most clusters.

    Contains incoming data for Solr.

    {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.

    Handles metadata for Milvus service.

    {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.

    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.

    milvus-mysql

    No

    REST/HTTP

    Deployment

    analytics or system

    Not required. One pod is enough for most clusters.

    Handles metadata for Milvus service 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-pipeline

    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.

    Ports used by Fusion

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

    Service Port

    admin

    8765

    admin-ui

    8080

    apps-manager

    9025

    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, 9093

    {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