Xray HA OpenShift Installation

Xray on OpenShift is available from version 3.80.9 onwards.

Before you proceed with the installation, review the system requirements.

Xray's system requirements are dependent on the scale of your environment.

Sizings

Non-Kubernetes Deployment

Up to 100K indexed artifacts. No High Availability

Up to 1M indexed artifacts

Up to 2M indexed artifacts

Up to 10M indexed artifacts

Over 10M indexed artifacts

Contact JFrog Support.

For Xray HA (High Availability) installations (more than one node and 100k indexed artifacts), it is recommended to install RabbitMQ and Xray on separate servers using split mode. For further details, please refer to our page here.

RabbitMQ Note

RabbitMQ is a crucial component of the Xray architecture, acting as a message broker for communication between various application services. Multiple queues facilitate communication channels between producers and consumers. For more information, please refer to our page here.

Kubernetes Deployment

We have included YAML files with different sizing configurations for Artifactory, Xray, and Distribution in our GitHub pages. You can use these YAML files when you set up your cluster.

Note: From Helm chart 103.124 version of JFrog Xray, JFrog added support for Quorum Queues in RabbitMQ. This requires a minimum of three nodes of RabbitMQ and ensures fault tolerance of at least one node.  A non-HA setup of 1 node is also supported.

Note: We recommend a three-node cluster of RabbitMQ for Xray. Large clusters increase the overhead of replication and could affect the throughput. Our application has been tuned to work in a three-node setup.

To mitigate performance bottlenecks, avoid port conflicts, and prevent unusual configurations, use a dedicated node for Xray and RabbitMQ with no other software running.Scalability

Xray

You can create a high-availability cluster by adding multiple nodes (1, 2, 3, ...n) to distribute the workload and increase capacity.

RabbitMQ

An odd number of servers is required for RabbitMQ to work effectively for Quorum Queues. We recommend a three-node cluster for RabbitMQ, and if additional capacity is needed, this can be met through vertical scaling. Connect with us if you see a need for this.

Quorum Queues Notes

Starting with version 3.124.x Xray supports Quorum Queues.RabbitMQ has discontinued support for Classic Queue mirroring in version 3.0 and deprecated it in version 4.0. With this, JFrog will be deprecating Classic Queue support in upcoming releases.

A highly available RabbitMQ cluster with Quorum Queues requires a minimum of three nodes.A two-node cluster with RabbitMQ Quorum Queues will not be fault-tolerant.More than three node clusters won’t add fault tolerance and can weaken RMQ performance.

For more information, please refer to the RabbitMQ Quorum Queues documentation here.

In most cases, our recommendation is to use an SSD drive for Xray to have better performance and it is not recommended to use an NFS drive, as it is a disk I/O-intensive service, a slow NFS server can suffer from I/O bottlenecks and NFS is mostly used for storage replication.

Xray stores node-specific files, such as configuration and temporary files, to the disk. These files are exclusively used by Xray and not shared with other services. Since the local storage used for Xray services is temporary, it does not require replication between the different nodes in a multi-node/HA deployment.

Use the following command to determine the current file handle allocation limit.

cat /proc/sys/fs/file-max

Then, set the following parameters in your /etc/security/limits.conf file to the lower of 100,000 or the file handle allocation limit determined above.

The example shows how the relevant parameters in the /etc/security/limits.conf file are set to 100000. The actual setting for your installation may be different depending file handle allocation limit in your system.

root hard nofile 100000
root soft nofile 100000
xray hard nofile 100000
xray soft nofile 100000
postgres hard nofile 100000
postgres soft nofile 100000

The following table lists the supported operating systems and their versions:

📘

Note

Debian 12.x and Ubuntu 24.04 are supported from Artifactory 7.104 and Distribution 2.28.

Windows 2022 is supported from Artifactory 7.125.

Supported Platforms

The following table lists the supported platforms:

Installation on Kubernetes environments is through Helm Charts. Supported Helm version is Helm 3.17+.

✅

Kubernetes Sizing Requirements

We have included YAML files with different sizing configurations for Artifactory , Xray, and Distribution in our GitHub pages. You can use these YAML files when you set up your cluster.

📘

ARM64 Support for Container-Based Installations

Artifactory, Xray and Distribution supports installation on ARM64 architecture specifically through Helm and Docker installations. When deploying a product on an ARM64 platform, an external database must be set up as Artifactory does not support the bundled database for ARM64 installations. The appropriate ARM64 Container Image is automatically pulled during the Helm or Docker installation process.

Database

Every artifact and build indexed by Xray is broken down into multiple components. These components and their interrelationships are represented in a checksum-based components graph. Xray uses PostgreSQL to store and query this component's graph.

Xray supports the following PostgreSQL versions:

RabbitMQ

RabbitMQ is installed as part of the Xray installation for every node. In an HA architecture, Xray utilises queue mirroring and replication between different RabbitMQ nodes. The recommended installation method involves using split mode and setting up a separate 3-node RabbitMQ cluster with Xray HA.

Note: JFrog has added support for RabbitMQ Quorum Queues, available as an optional parameter in the system.yaml, because RabbitMQ has deprecated Classic Queue mirroring in version 4.x. Consequently, JFrog will also deprecate Classic Queue support and transition to Quorum Queues. It is recommended to enable Quorum Queues in Xray, as JFrog plans to fully transition to RabbitMQ 4.x and discontinue Classic Queue support in upcoming versions.

Xray encompasses multiple flows, including scanning, impact analysis, and database synchronisation. These flows require processing by various Xray microservices. Flows comprise multiple steps completed by the Xray services. Xray uses RabbitMQ to manage these different flows and track synchronous and asynchronous communication between microservices.

Erlang

Xray incorporates Erlang and DB-Util as third-party dependencies. These packages are bundled with all Xray installers except for the Linux Archive.

Please ensure you are using the correct Erlang version corresponding to your Xray version:

• Xray versions 3.124.x requires Erlang 26. For more information on RabbitMQ and Erlang compatibility, please refer to the RabbitMQ and Erlang/OTP Compatibility Matrix.
• Xray 3.124 and later versions need Erlang 27 if we have enabled the RabbitMQ 4.x using properties.

Xray uses the 8082 port by default for external communication.

Xray uses the following internal ports by default for communication with JFrog Platform microservices.

📘

Note

Currently, it is not possible to connect a JFrog product that is within a Kubernetes cluster with another JFrog product that is outside of the cluster, as this is considered a separate network. Therefore, JFrog products cannot be joined together if one of them is in a cluster.

📘

Note

External RabbiMQ instances are not officially supported; the recommended method of installation is to use the bundled RabbitMQ.

Follow these steps to install the product:

📘

Note

In our documentation, we use oc commands for code snippets related to OpenShift installation, but kubectl commands will also work.

1. Add the charts.jfrog.io to your Helm client.

   Bash

   helm repo add jfrog https://charts.jfrog.io

2. Update the repository.

   Bash

   helm repo update

3. Next, create a unique master key. JFrog Xray requires a unique master key to be used by all micro-services in the same cluster. By default the chart has one set in values.yaml (xray.masterKey).

📘

Note

For production grade installations it is strongly recommended to use a custom master key. If you initially use the default master key it will be very hard to change the master key at a later stage This key is for demo purpose and should not be used in a production environment.

Generate a unique key and pass it to the template during installation/upgrade.

# Create a key
export MASTER_KEY=$(openssl rand -hex 32)
echo ${MASTER_KEY}

You can pass this master key to the Helm installation through the Helm command or through the values.yaml file.

The following example shows the values.yaml file with the master key.

xray:
  masterKey: <master key value>

Alternatively, you can create a secret containing the master key manually and pass it to the template during installation/upgrade.

 # Create a secret containing the key. The key in the secret must be named master-key
oc create secret generic masterkey-secret --from-literal=master-key=${MASTER_KEY}

You can pass this master key secret to the Helm installation through the Helm command (by passing masterkey-secret) or through the values.yaml file.

The following example shows the values.yaml file with the master key secret.

xray:
  masterKeySecretName: masterkey-secret

📘

Note

In either case, make sure to pass the same master key on all future calls to helm install and helm upgrade. In the first case, this means always passing --set xray.masterKey=${MASTER_KEY}. In the second, this means always passing --set xray.masterKeySecretName=masterkey-secret and ensuring the contents of the secret remain unchanged.

You can also provide the master key or master key secret inside a values.yaml file and pass it along during the installation.

4. Installation requires a join key.

   You can pass the join key along with the Helm install/upgrade command or pass it in a values.yaml file.

   The following sample shows how to provide join key in the values.yaml file.

   Bash

   xray:
     joinKey: <join key value>

   Alternatively, you can manually create a secret containing the join key and then pass it to the template during install/upgrade. The key must be named join-key.

   Bash

   oc create secret generic joinkey-secret --from-literal=join-key=<YOUR_PREVIOUSLY_RETRIEVED_JOIN_KEY>

   The following example shows the values.yaml file with the join key secret.

   Bash

   xray:
     joinKeySecretName: joinkey-secret

📘

Note

In either case, make sure to pass the same join key on all future calls to helm install and helm upgrade. This means always passing --set xray.joinKey=<YOUR_PREVIOUSLY_RETRIEVED_JOIN_KEY>. In the second, this means always passing --set xray.joinKeySecretName=joinkey-secret and ensuring that the contents of the secret remain unchanged.

5. You need to enter the JFrog URL.

   You can either pass the JFrog URL along with the Helm install/upgrade command or pass it along with the values.yaml file.

   The following example shows the values.yaml file with the JFrog URL.

   Bash

   xray:
     jfrogUrl: <JFrog URL>

6. For an HA Xray installation, set the replicaCount value as >1 (the recommended is 3).

   You can either pass the value along with the Helm install/upgrade command or pass it along with the values.yaml file.

   The following example shows the values.yaml file with the replicaCount values.

   YAML

   replicaCount: 3

7. When you deploy Xray helm chart on an OpenShift cluster, you need to disable the podSecurityContext and containerSecurityContext. Default OpenShift functionality automatically assigns and arbitrary UID block associated with the project.

   Set the following values in the values.yaml so that you can pass it along with the installation.

   YAML

   containerSecurityContext:
     enabled: false
   podSecurityContext:
     enabled: false
   
   rbac:
     create: true
   serviceAccount:
     create: true
   
   rabbitmq:
     rbac:
       create: true
     podSecurityContext:
       enabled: false
     containerSecurityContext:
       enabled: false

8. To make PostgreSQL work on OpenShift, disable the securityContext in the pod and container level in the values.yaml file, and set the following values.

   YAML

     postgresql:
       postgresqlPassword: password
       securityContext:
         enabled: false
       containerSecurityContext:
         enabled: false
       serviceAccount:
         enabled: true

9. Create a values.yaml file with all the required configuration if you want to proceed with an installation that holds all the configurations in a values.yaml file.

   You can also use separate configuration files for each configuration and pass them as separate yaml files.

   The following sample shows an example values.yaml file with join key and JFrog URL.

   replicaCount: 3
   xray:
     jfrogUrl: http://artifactory.rt:8082
     joinKey: joinkey-secret
     masterKey: masterkey-secret
   
   containerSecurityContext:
     enabled: false
   podSecurityContext:
     enabled: false
   
   rbac:
     create: true
   serviceAccount:
     create: true
   
   rabbitmq:
     rbac:
       create: true
     podSecurityContext:
       enabled: false
     containerSecurityContext:
       enabled: false
     replicaCount: 1
   postgresql:
     postgresqlPassword: password
     securityContext:
       enabled: false
     containerSecurityContext:
       enabled: false
     serviceAccount:
       enabled: true
   ```text
   
   The following sample shows an example `values.yaml` file with join key as a secret and JFrog URL.
   

   replicaCount: 3 xray: jfrogUrl: http://artifactory.rt:8082 joinKeySecretName: joinkey-secret masterKeySecretName: masterkey-secret

   containerSecurityContext: enabled: false podSecurityContext: enabled: false

   rbac: create: true serviceAccount: create: true

   rabbitmq: rbac: create: true podSecurityContext: enabled: false containerSecurityContext: enabled: false replicaCount: 1 postgresql: postgresqlPassword: password securityContext: enabled: false containerSecurityContext: enabled: false serviceAccount: enabled: true

10. Run the Helm install command to proceed with the installation.

    The following command shows how you can pass the required values through a values.yaml file.

    Bash

    helm upgrade --install xray --namespace xray -f values.yaml

11. To access the logs, find the name of the pod using the following command.

    Bash

    oc --namespace <your namespace> get pods

12. To get the container logs, run the following command.

    Bash

    oc --namespace <your namespace> logs -f <name of the pod>

13. Customize the product configuration.

📘

Note

Unlike other installations, Helm Chart configurations are made to the values.yaml and are then applied to the system.yaml.

Follow these steps to apply the configuration changes.

1. Make the changes to values.yaml.

2. Run the command.

   Bash

   helm upgrade --install xray --namespace xray -f values.yaml

14. Access Xray from your browser at: http://<jfrogUrl>/ui/ and go to Xray Security & Compliance tab in the Administration module in the UI

15. Check the status of your deployed helm releases.

    Bash

    helm status xray

After installing and before running Xray, you may set the following configurations.

You can configure all your system settings using the system.yaml file located in the $JFROG_HOME/xray /var/etc folder. For more information, see Xray System YAML.

If you don't have a System YAML file in your folder, copy the template available in the folder and name it system.yaml.

For the Helm charts, the system.yaml file is managed in the chart’s values.yaml.

Xray requires a working Artifactory server and a suitable license. The Xray connection to Artifactory requires the following parameters.

• jfrogUrl

  URL to the machine where JFrog Artifactory is deployed, or the load balancer pointing to it. It is recommended to use DNS names rather than direct IPs. For example: http://jfrog.acme.com or http://10.20.30.40:8082. Note that /artifactory context is not longer required.

  Set it in the Shared Configurations section of the $JFROG_HOME/xray/var/etc/system.yamlfile.

• join.key

  This is the "secret" key required by Artifactory for registering and authenticating the Xray server.

  You can fetch the Artifactory joinKey (join Key) from the JPD UI in the User Management | Settings | Join Key.

  Set the join.key used by your Artifactory server in the Shared Configurations section of the $JFROG_HOME/xray/var/etc/system.yaml file.

Xray comes bundled with a PostgreSQL database out-of-the-box, which come pre-configured with the default credentials.

To change the default credentials:

# Access PostgreSQL as the Xray user adding the optional -W flag to invoke the password prompt
$ psql -d xraydb -U xray -W
  
# Securely change the password for user "xray". Enter and then retype the password at the prompt.
\password xray
  
# Verify the update was successful by logging in with the new credentials
$ psql -d xraydb -U xray -W

Set your PostgreSQL connection details in the Shared Configurations section of the $JFROG_HOME/xray/var/etc/system.yaml file.

Xray comes pre-installed with RabbitMQ, by setting the Erlang cookie value as the RabbitMQ password for guest users.

By default, RabbitMQ uses the short hostnames of other nodes in the cluster for communication. However, it be can be configured to use a fully qualified domain name (FQND) host name (a long hostname).

To configure RabbitMQ to use FQDN, follow these steps.

1. Install Xray , but do not start the services.

2. Modify the following files according to the installer type.

   • Common Change in All Installers

     YAML

     In system.yaml:
      
     shared:
       node:
         id: <long hostname>
         name: <long hostname>
     ## For secondary nodes only, provide the hostname of any of the active nodes where RabbitMQ service is running.
     #  shared:
     #    rabbitMq:
     #      active:
     #        node:
     #          name: <long hostname of active node>

3. Start RabbitMQ and the Xray services.

Xray enables using an external log collector such as Sumologic or Splunk.

To adjust the permissions to allow the log collection service perform read operations on the generated log files.

1. Add the log collection service user to the relevant group if needed (the user and group that installed and started Xray).

2. Apply the user and group permissions as needed on the $JFROG_HOME/xray/var/log directory using:

   Bash

   $ chmod -R 640 $JFROG_HOME/xray/var/log

3. Adjust the group read inheritance permissions setgid bit using:

   Bash

   $ chmod -R 2755 $JFROG_HOME/xray/var/log

   This command enables the generated log files to inherit the folder's group permissions.

Xray System Requirements and Platform Support

Xray's system requirements are dependent on the scale of your environment.

Sizings

Non-Kubernetes Deployment

Up to 100K indexed artifacts. No High Availability

Up to 1M indexed artifacts

Up to 2M indexed artifacts

Up to 10M indexed artifacts

Over 10M indexed artifacts

Contact JFrog Support.

For Xray HA (High Availability) installations (more than one node and 100k indexed artifacts), it is recommended to install RabbitMQ and Xray on separate servers using split mode. For further details, please refer to our page here.

RabbitMQ Note

RabbitMQ is a crucial component of the Xray architecture, acting as a message broker for communication between various application services. Multiple queues facilitate communication channels between producers and consumers. For more information, please refer to our page here.

Kubernetes Deployment

We have included YAML files with different sizing configurations for Artifactory, Xray, and Distribution in our GitHub pages. You can use these YAML files when you set up your cluster.

Note: From Helm chart 103.124 version of JFrog Xray, JFrog added support for Quorum Queues in RabbitMQ. This requires a minimum of three nodes of RabbitMQ and ensures fault tolerance of at least one node.  A non-HA setup of 1 node is also supported.

Note: We recommend a three-node cluster of RabbitMQ for Xray. Large clusters increase the overhead of replication and could affect the throughput. Our application has been tuned to work in a three-node setup.

The following table lists the supported operating systems and their versions:

📘

Note

Debian 12.x and Ubuntu 24.04 are supported from Artifactory 7.104 and Distribution 2.28.

Windows 2022 is supported from Artifactory 7.125.

Supported Platforms

The following table lists the supported platforms:

Installation on Kubernetes environments is through Helm Charts. Supported Helm version is Helm 3.17+.

✅

Kubernetes Sizing Requirements

We have included YAML files with different sizing configurations for Artifactory , Xray, and Distribution in our GitHub pages. You can use these YAML files when you set up your cluster.

📘

ARM64 Support for Container-Based Installations

Artifactory, Xray and Distribution supports installation on ARM64 architecture specifically through Helm and Docker installations. When deploying a product on an ARM64 platform, an external database must be set up as Artifactory does not support the bundled database for ARM64 installations. The appropriate ARM64 Container Image is automatically pulled during the Helm or Docker installation process.

Xray and RabbitMQ Nodes Recommendations

To mitigate performance bottlenecks, avoid port conflicts, and prevent unusual configurations, use a dedicated node for Xray and RabbitMQ with no other software running.

Scalability

Xray

You can create a high-availability cluster by adding multiple nodes (1, 2, 3, ...n) to distribute the workload and increase capacity.

RabbitMQ

An odd number of servers is required for RabbitMQ to work effectively for Quorum Queues. We recommend a three-node cluster for RabbitMQ, and if additional capacity is needed, this can be met through vertical scaling. Connect with us if you see a need for this.

Quorum Queues Notes

Starting with version 3.124.x Xray supports Quorum Queues.RabbitMQ has discontinued support for Classic Queue mirroring in version 3.0 and deprecated it in version 4.0. With this, JFrog will be deprecating Classic Queue support in upcoming releases.

A highly available RabbitMQ cluster with Quorum Queues requires a minimum of three nodes.A two-node cluster with RabbitMQ Quorum Queues will not be fault-tolerant.More than three node clusters won’t add fault tolerance and can weaken RMQ performance.

For more information, please refer to the RabbitMQ Quorum Queues documentation here.

Xray Storage Recommendations

In most cases, our recommendation is to use an SSD drive for Xray to have better performance and it is not recommended to use an NFS drive, as it is a disk I/O-intensive service, a slow NFS server can suffer from I/O bottlenecks and NFS is mostly used for storage replication.

Xray stores node-specific files, such as configuration and temporary files, to the disk. These files are exclusively used by Xray and not shared with other services. Since the local storage used for Xray services is temporary, it does not require replication between the different nodes in a multi-node/HA deployment.

Xray File Handle Allocation Limit

Use the following command to determine the current file handle allocation limit.

cat /proc/sys/fs/file-max

Then, set the following parameters in your /etc/security/limits.conf file to the lower of 100,000 or the file handle allocation limit determined above.

The example shows how the relevant parameters in the /etc/security/limits.conf file are set to 100000. The actual setting for your installation may be different depending file handle allocation limit in your system.

root hard nofile 100000
root soft nofile 100000
xray hard nofile 100000
xray soft nofile 100000
postgres hard nofile 100000
postgres soft nofile 100000

Database and Third-Party Applications in Xray

Database

Every artifact and build indexed by Xray is broken down into multiple components. These components and their interrelationships are represented in a checksum-based components graph. Xray uses PostgreSQL to store and query this component's graph.

Xray supports the following PostgreSQL versions:

RabbitMQ

RabbitMQ is installed as part of the Xray installation for every node. In an HA architecture, Xray utilises queue mirroring and replication between different RabbitMQ nodes. The recommended installation method involves using split mode and setting up a separate 3-node RabbitMQ cluster with Xray HA.

Note: JFrog has added support for RabbitMQ Quorum Queues, available as an optional parameter in the system.yaml, because RabbitMQ has deprecated Classic Queue mirroring in version 4.x. Consequently, JFrog will also deprecate Classic Queue support and transition to Quorum Queues. It is recommended to enable Quorum Queues in Xray, as JFrog plans to fully transition to RabbitMQ 4.x and discontinue Classic Queue support in upcoming versions.

Xray encompasses multiple flows, including scanning, impact analysis, and database synchronisation. These flows require processing by various Xray microservices. Flows comprise multiple steps completed by the Xray services. Xray uses RabbitMQ to manage these different flows and track synchronous and asynchronous communication between microservices.

Erlang

Xray incorporates Erlang and DB-Util as third-party dependencies. These packages are bundled with all Xray installers except for the Linux Archive.

Please ensure you are using the correct Erlang version corresponding to your Xray version:

• Xray versions 3.124.x requires Erlang 26. For more information on RabbitMQ and Erlang compatibility, please refer to the RabbitMQ and Erlang/OTP Compatibility Matrix.
• Xray 3.124 and later versions need Erlang 27 if we have enabled the RabbitMQ 4.x using properties.

Xray Network Ports

Xray uses the 8082 port by default for external communication.

Xray uses the following internal ports by default for communication with JFrog Platform microservices.