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Benchmark#

The Janssen Server has been optimized with several container strategies that allow scaling microservices and orchestrating them using Kubernetes. In this tutorial we will be running a load test from three different regions on a janssen setup on three different regions. For simplicity, we will be using microk8s however we do recommend users to use the kubernetes cluster providers that they will be using in production. For instance, we run our loadtests across EKS, GKE, AKS and DOKS.

With this procedure the following with a 10 million user database is expected:

Results#

Note

The authorization code flow hits a total of 4 steps, 3 authorization steps /token, /authorize, /jans-auth/login and 1 redirect.

Flow Authentications per second
Authorization code flow 800-1000

Installation#

As mentioned in the overview we recommend using the same Kubernetes cluster as planned in production. More guides to install on different clouds can be found here.

Persistence#

We recommend your persistence in production to be HA, backup supported and point in time recovery supported. Below is a table of the persistence used and resources set for this test.

Persistence # of nodes RAM(GiB) vCPU Total RAM (GiB) Total vCPU
MySQL 1 52 8 52 8

Set up the cluster#

Kubernetes Cluster Load Test Resources#

Note

Instance type can be selected to best suit the deployment intended. Keep in mind when selecting the instance type to strive for a 10 or up to 10 network bandwidth (Gbps). Below details the exact resources needed for this tutorial. This is in addition to the persistence resources listed above.

Resourcing is critical as timeouts in connections can occur, resulting in failed authentications or cutoffs.

Regions # of nodes RAM(GiB) vCPU Total RAM (GiB) Total vCPU
US-West 1 96 48 96 48
US-East 1 96 48 96 48
EU-Central 1 96 48 96 48
Grand Total 288 GB 144

A Kubernetes cluster can be created with three nodes or more in one region and that's fine as long as the nodes are in multiple zones. We will continue with the above table and using microk8s.

  1. Create three ubuntu 22.04 nodes and run on each one the following:

    sudo snap install microk8s --classic
sudo snap alias microk8s.kubectl kubectl
    2. Designate one of the nodes as the master. We will choose the us-west node to be our master. On the master node run:

  2. Execute : 

    microk8s.enable ingress dashboard observability dns metrics-server hostpath-storage registry

  3. All the other microk8s nodes must be resolvable from within the master. If fqdns are not globally resolved (registered) open the /etc/hosts file in the master node and map each hostname of the other nodes. YThe hostname of the other nodes can be obtained by executing the command hostname.

    # If the hostnames are not globally resolvable on master
echo "192.123.123.123 ubuntu-us-east" >> /etc/hosts
echo "192.124.124.124 ubuntu-eu-central" >> /etc/hosts
    3. Execute: 

    microk8s add-node

Copy the output of the command above with --worker i.e. microk8s join 192.12.12.12:25000/88687d1cc5ecdee0db5014c4df9b82cb/adedf6a730eb --worker and execute it in the other nodes (worker nodes) to join them. Step iii ( this step) needs to be repeated for each worker node.

  1. Make sure helm is installed.

  2. Prepare your override.yaml. Copy the below into a file named override.yaml. At the time of writing this we are using image tags 1.7.0_dev which are the bleeding edge images for release 1.7.0. Stable images such as 1.7.0-1 should be used.

config:
   image:
     repository: ghcr.io/janssenproject/jans/configurator
     tag: 1.7.0_dev 
   countryCode: US
   email: support@gluu.org
   orgName: Gluu
   city: Austin
   configmap:
     cnSqlDbName: test
     cnSqlDbPort: 3306
     cnSqlDbDialect: mysql
     cnSqlDbHost: mycool.cloud.mysql
     cnSqlDbUser: root
     cnSqlDbTimezone: UTC
     cnSqldbUserPassword: Test1234#
global:
  auth-server:
    enabled: true
  config-api:
    enabled: true
  cnPersistenceType: sql
  cloud:
    testEnviroment: false
  fqdn: example.gluu.info
  isFqdnRegistered: true
  # In the event the fqdn above is not resolvable from the internet comment the above line and uncomment the below two setting your lbIp to your master ndoe ip.
  #isFqdnRegistered: false
  #lbIp: 192.12.12.12
  istio:
    enabled: false
    ingress: false
  nginx-ingress:
    enabled: true
  fido2:
    enabled: false
    ingress:
      fido2ConfigEnabled: false
  scim:
    enabled: false
    ingress:
      scimConfigEnabled: false
      scimEnabled: false
auth-server:
  image:
    pullPolicy: IfNotPresent
    repository: ghcr.io/janssenproject/jans/auth-server
    tag: 1.7.0_dev
config-api:
  image:
    pullPolicy: IfNotPresent
    repository: ghcr.io/janssenproject/jans/config-api
    tag: 1.7.0_dev
persistence:
  image:
    pullPolicy: IfNotPresent
    repository: ghcr.io/janssenproject/jans/persistence-loader
    tag: 1.7.0_dev 
nginx-ingress:
  ingress:
    path: /
    hosts:
      - example.gluu.info
    tls:
      - secretName: tls-certificate
        hosts:
          - example.gluu.info
  1. Run the following: 
     kubectl create ns jans
 helm repo add janssen https://docs.jans.io/charts
 helm repo update
 helm install janssen janssen/janssen -n jans -f override.yaml

Load-test#

Our tests used 10 million users that were loaded. We have created a docker image to load users. That same image is also used to load test Janssen using jmeter tests for the Authorization code flow. More tests will come!. This image will load users and use a unique password for each user.

Loading users#

Loading users requires a hefty but temporary amount of resources. By default, the resources ask for 10 vCPU and 5 Gis. However, to speed up the process increase the number of CPUs as the job in step two below uses parallel tasks. If left as is 10 million users would load in around 17 hours or so.

  1. Create a folder called add_users.

    mkdir -p add_users && cd add_users

  2. Copy the following yaml into the folder under the name load_users.yaml.

  3. Open the file and modify the required parameters. Note that the following environments can be used as configmaps data to configure the pod.

    ENV Description Default
    TEST_USERS_PREFIX_STRING The user prefix string attached to the test users loaded test_user
    USER_NUMBER_STARTING_POINT The user number to start from . This is appended to the username i.e test_user0 0
    USER_NUMBER_ENDING_POINT The user number to end at. 50000000
    LOAD_USERS_TO_RDBMS Enable loading users to RDBMS persistence. true or false == `` false
    USER_SPLIT_PARALLEL_THREADS The number of parallel threads to break the total number users across. This number heavily effects vCPU usage. 20
    RDBMS_TYPE RDBMS type if mysql or pgsql is the persistence to load users in. mysql
    RDBMS_DB RDBMS Database name if mysql or pgsql is the persistence to load users in. jans
    RDBMS_USER RDBMS user if mysql or pgsql is the persistence to load users in. jans
    RDBMS_PASSWORD RDBMS user password if mysql or pgsql is the persistence to load users in. . ``
    RDBMS_HOST RDBMS host if mysql or pgsql is the persistence to load users in. localhost

    Tips: To speed the loading process, increase the vCPU requests and limits of the pod.

  4. Create a namespace for load-testing.

    kubectl create ns load

  5. Create load_users.yaml

    kubectl create -f load_users.yaml -n load
cd ..

Wait until all the users are up before moving forward. Tail the logs by running kubectl logs deployment/load-users -n load.

Load testing#

Authorization code flow#

Resources needed for Authorization code client jmeter test#

The below resources were calculated when creating the nodes above.

NAME # of pods RAM(GiB) vCPU Total RAM(GiB) Total vCPU
Authorization code flow jmeter test 20 8 1.3 190 24
Grand Total 190 GiB 24
Setup Client#

Create the client needed to run the test by executing the following. Make sure to change the FQDN :

  1. Create a folder called load_test.

    mkdir -p load_test && cd load_test

  2. Create the client json file

    FQDN=example.gluu.info
cat << EOF > auth_code_client.json
{
    "dn": null,
    "inum": null,
    "displayName": "Auth Code Flow Load Test Client",
    "redirectUris": [
      "https://$FQDN"
    ],
    "responseTypes": [
      "id_token",
      "code"
    ],
    "grantTypes": [
      "authorization_code",
      "implicit",
      "refresh_token"
    ],
    "tokenEndpointAuthMethod": "client_secret_basic",
    "scopes": [
      "openid",
      "profile",
      "email",
      "user_name"
    ],
    "trustedClient": true,
    "includeClaimsInIdToken": false,
    "accessTokenAsJwt": false,
    "disabled": false,
    "deletable": false,
    "description": "Auth Code Flow Load Testing Client"
}
EOF
    3. Copy the following yaml into the folder.

  3. Download or build config-cli-tui and run:

    # Notice the namespace is jans here . Change it if it was changed during installation of janssen previously
TUI_CLIENT_ID=$(kubectl get cm cn -o json -n jans | grep '"tui_client_id":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]')
TUI_CLIENT_SECRET=$(kubectl get secret cn -o json -n jans | grep '"tui_client_pw":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]' | base64 -d)
# add -noverify if your fqdn is not registered
./config-cli-tui.pyz --host $FQDN --client-id $TUI_CLIENT_ID --client-secret $TUI_CLIENT_SECRET --no-tui --operation-id=post-oauth-openid-client --data=auth_code_client.json

  4. Save the client id and secret from the response and enter them along with your FQDN in the yaml file load_test_auth_code.yaml under AUTHZ_CLIENT_ID, AUTHZ_CLIENT_SECRET and FQDN respectively then execute :

    kubectl apply -f load_test_auth_code.yaml

  5. The janssen setup by default installs an HPA which will automatically scale your pods if the metrics server is installed according to traffic. To load it very quickly scale the auth-server manually: bash kubectl scale deploy janssen-auth-server -n jans --replicas=40

  6. Finally, scale the load test. The replica number here should be manually controlled. bash kubectl scale deploy load-testing-authz -n load --replicas=20

Resource Owner Password Credentials (ROPC) flow#

Resources needed for ROPC client jmeter test#

The below resources were calculated when creating the nodes above.

NAME # of pods RAM(GiB) vCPU Total RAM(GiB) Total vCPU
ROPC flow jmeter test 20 8 1.3 190 24
Grand Total 190 GiB 24
Setup Client#

Create the client needed to run the test by executing the following. Make sure to change the FQDN :

  1. Create a folder called load_test.

    mkdir -p load_test && cd load_test

  2. Create the client json file

    FQDN=example.gluu.info
cat << EOF > ropc_client.json
{
    "dn": null,
    "inum": null,
    "displayName": "ROPC Flow Load Test Client",
    "redirectUris": [
      "https://$FQDN"
    ],
    "responseTypes": [
      "id_token",
      "code"
    ],
    "grantTypes": [
      "authorization_code",
      "implicit",
      "refresh_token",
      "password"
    ],
    "tokenEndpointAuthMethod": "client_secret_basic",
    "scopes": [
      "openid",
      "profile",
      "email",
      "user_name"
    ],
    "trustedClient": true,
    "includeClaimsInIdToken": false,
    "accessTokenAsJwt": false,
    "disabled": false,
    "deletable": false,
    "description": "ROPC Flow Load Testing Client"
}
EOF

  3. Copy the following yaml into the folder.

  4. Download or build config-cli-tui and run:

    # Notice the namespace is jans here . Change it if it was changed during installation of janssen previously
TUI_CLIENT_ID=$(kubectl get cm cn -o json -n jans | grep '"tui_client_id":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]')
TUI_CLIENT_SECRET=$(kubectl get secret cn -o json -n jans | grep '"tui_client_pw":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]' | base64 -d)
# add -noverify if your fqdn is not registered
./config-cli-tui.pyz --host $FQDN --client-id $TUI_CLIENT_ID --client-secret $TUI_CLIENT_SECRET --no-tui --operation-id=post-oauth-openid-client --data=ropc_client.json

  5. Save the client id and secret from the response and enter them along with your FQDN in the yaml file load_test_ropc.yaml under ROPC_CLIENT_ID, ROPC_CLIENT_SECRET and FQDN respectively then execute :

    kubectl apply -f load_test_ropc.yaml

  6. The janssen setup by default installs an HPA which will automatically scale your pods if the metrics server is installed according to traffic. To load it very quickly scale the auth-server manually: bash kubectl scale deploy janssen-auth-server -n jans --replicas=40

  7. Finally, scale the load test. The replica number here should be manually controlled. bash kubectl scale deploy load-testing-ropc -n load --replicas=20

DCR flow#

Resources needed for DCR client jmeter test#

The below resources were calculated when creating the nodes above.

NAME # of pods RAM(GiB) vCPU Total RAM(GiB) Total vCPU
DCR test 20 8 1.3 190 24
Grand Total 190 GiB 24
Setup Client#

Create the client needed to run the test by executing the following. Make sure to change the FQDN :

  1. Create a folder called load_test.

    mkdir -p load_test && cd load_test

  2. Create the client json file

    FQDN=example.gluu.info
cat << EOF > dcr_client.json
{
    "dn": null,
    "inum": null,
    "displayName": "DCR Flow Load Test Client",
    "redirectUris": [
      "https://$FQDN"
    ],
    "responseTypes": [
      "id_token",
      "code"
    ],
    "grantTypes": [
      "authorization_code",
      "implicit",
      "refresh_token",
      "password"
    ],
    "tokenEndpointAuthMethod": "client_secret_basic",
    "scopes": [
      "openid",
      "profile",
      "email",
      "user_name"
    ],
    "trustedClient": true,
    "includeClaimsInIdToken": false,
    "accessTokenAsJwt": false,
    "disabled": false,
    "deletable": false,
    "description": "DCR Flow Load Testing Client"
}
EOF

  3. Copy the following yaml into the folder.

  4. Download or build config-cli-tui and run:

    # Notice the namespace is jans here . Change it if it was changed during installation of janssen previously
TUI_CLIENT_ID=$(kubectl get cm cn -o json -n jans | grep '"tui_client_id":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]')
TUI_CLIENT_SECRET=$(kubectl get secret cn -o json -n jans | grep '"tui_client_pw":' | sed -e 's#.*:\(\)#\1#' | tr -d '"' | tr -d "," | tr -d '[:space:]' | base64 -d)
# add -noverify if your fqdn is not registered
./config-cli-tui.pyz --host $FQDN --client-id $TUI_CLIENT_ID --client-secret $TUI_CLIENT_SECRET --no-tui --operation-id=post-oauth-openid-client --data=dcr_client.json

  5. You will need to load the sectorIdentifier into your persistence.For MySQL that statement would be the following taking into account the FQDN:

    INSERT INTO jansSectorIdentifier (doc_id, dn, jansId, jansRedirectURI, objectClass)
VALUES (
  'a55ede29-8f5a-461d-b06e-76caee8d40b5',
  'jansId=a55ede29-8f5a-461d-b06e-76caee8d40b5,ou=sector_identifiers,o=jans',
  'a55ede29-8f5a-461d-b06e-76caee8d40b5',
  '{"v": ["https://www.jans.org", "http://localhost:80/jans-auth-rp/home.htm", "https://localhost:8443/jans-auth-rp/home.htm", "https://$FQDN/jans-auth-rp/home.htm", "https://$FQDN/jans-auth-client/test/resources/jwks.json", "https://client.example.org/callback", "https://client.example.org/callback2", "https://client.other_company.example.net/callback", "https://client.example.com/cb", "https://client.example.com/cb1", "https://client.example.com/cb2"]}',
  'jansSectorIdentifier'
);

  6. Save the client id and secret from the response and enter them along with your FQDN in the yaml file load_test_ropc.yaml under DCR_CLIENT_ID, DCR_CLIENT_SECRET and FQDN respectively then execute :

    kubectl apply -f load_test_dcr.yaml

  7. The janssen setup by default installs an HPA which will automatically scale your pods if the metrics server is installed according to traffic. To load it very quickly scale the auth-server manually: bash kubectl scale deploy janssen-auth-server -n jans --replicas=40

  8. Finally, scale the load test. The replica number here should be manually controlled. bash kubectl scale deploy load-testing-ropc -n load --replicas=20

Last update: 2025-03-28
Created: 2023-01-02