GAMS Engine comes with a highly flexible model- and user management system that allows you to restrict the activities of your users according to your organizational hierarchy. To understand this in its entirety, we need to address a few concepts in more detail: models, namespaces, permissions and user types.

When submitting a GAMS job, it usually consists of model files and data files. While the latter usually differ with each job, the actual GAMS model remains mostly unchanged. In order to avoid submitting the same files to Engine with each job, models can be registered with Engine. Files of registered models are stored by Engine and used for subsequent jobs. You only need to provide the name under which the model is registered and send the dynamic data.

• Job with unregistered model
  The user provides both the model files as well as the data to run the model with.

• Job with registered model
  The GAMS model is registered with Engine and the user only provides the model name and dynamic data to run the model with.

Models are organized in namespaces, which you can think of as file directories. Models are always registered in a namespace and submitted GAMS jobs are also executed there. Each model name can only occur once within a namespace. If two models with the same name are to be registered, this must be done in different namespaces. Apart from the ability to manage multiple models with the same name, namespaces are particularly useful for representing hierarchical (user) structures. This is due to an important property of namespaces, namely the concept of permissions.

• Read Permission
  Users can download GAMS models registered in this namespace
• Write Permission
  Users can register new models in this namespace
• Execute Permission
  Users can execute models in this namespace

In the following example, two namespaces are used by three people with different permissions to represent the structure and workflow of a company with a customer.

• Developer:
  The Model Developer is responsible for maintaining existing models and developing future models. He only accesses the namespace R&D provided for this purpose, in which he has all permissions.
• Manager:
  The manager has read and execute permissions on the namespace R&D. There she checks the models for customer suitability. If a model (update) is ready, then the manager registers it in the namespace production.
• Customer:
  The customer has read and execute permissions on the namespace production. With these permissions she can submit jobs with her data and receive the results.

Tip:

After setting up GAMS Engine, there is a single namespace available with the name: global. Adding namespaces as well as registering models can easily be done via the Engine UI in the Models view.

After first installing the system, there is a single default user available with the name: admin and password: admin.

If you are administrator, you can invite other users. If you are using Engine UI, you will find an invite user button in the upper right corner of the Users section.

GAMS Engine distinguishes three types of users:

• Users
• Inviters
  Inviters are users with the additional privilege to invite new users to use GAMS Engine. However, inviters can only invite users who have the same or fewer permissions than themselves. For example, if an inviter has read and execute permissions on the namespace global, she is not allowed to invite a user with write permission on this namespace. Inviters can invite other inviters, but not admins.
• Administrators
  Administrators are the most privileged users. They have full permissions for each namespace and are allowed to invite new users, even new administrators. Administrators can also add new namespaces or remove existing ones.

In order to add a new user to GAMS Engine, you need to generate an invitation code. Users can then register themselves by providing this invitation code, a username and a password. Invitation codes can be generated by administrators and inviters. When creating an invitation code, permissions to namespaces can be assigned so that the new user can start interacting with the system directly. Note that the invitee's permissions may be lower than the inviter's, but not higher. Furthermore, inviters are able to manage - i.e. modify permissions and delete - their children (invitees) as well as any grandchildren. In this way, you can set up several hierarchy levels.

User hierarchy example:

Users can be assigned to user groups. A user group is a collection of users with any role (user, iviter, or administrator). A user group is always assigned to a namespace and has a unique label/name within that namespace. To create or remove a user group, you must be an inviter with write permission in that namespace (or an administrator).

Any member of a group can see all other members within that group. In addition, inviters can see the mebbers of all their invitees' groups. Only inviters and admins can add and remove members from a group. While admins can remove any member from any group, inviters can only remove their invitees. Also, inviters can only remove members from groups that they are either a member of themselves or that belong to an invitee.

User groups can be used to restrict the visibility of models in a namespace. When registering a new model (or updating an existing model), you can specify which user groups can see that model. All users who can see at least one of the user groups to which the model is assigned can see the model. If a model is not assigned to a user group, the model is visible to anyone who has any permission (read, write, and/or execute) in that namespace.

Jobs can also be shared with user groups. When you submit a new (Hypercube) job, you can specify which user groups have access to the job. Anyone who has access to the user group can then access the job (view the job details, cancel the job, download/delete the results, etc.). The access groups of a job can be edited even after the job has been submitted (via the PUT /jobs/{token}/access-groups endpoint).

To interact with GAMS Engine, you must authenticate yourself. Engine currently supports two ways to authenticate: Basic authentication as well as authentication using JSON Web Tokens (JWT).

With basic authentication, you send your username and password with each request. You can use basic authentication only if GAMS Engine is your identity provider. With JWT, a token is used for authentication. JWT tokens are only valid for a certain period of time. If your identity provider is GAMS Engine, you can specify the time period when creating a new token (using POST /auth/login endpoint), otherwise your identity provider may allow you to specify a time period depending on its security policy.

Whenever your username or password is changed (either by yourself or by an administrator), all your JWT are automatically invalidated and you have to generate new ones. You can also manually invalidate all your JWT via the POST /auth/logout endpoint. It is not possible to invalidate individual tokens.

One advantage of JWT authentication over basic authentication is that instead of storing a user's password (which is often reused for multiple services), a random-looking token is stored if you want to implement a "stay logged in" feature on your client (in fact, this is what Engine UI, GAMS Studio and GAMS MIRO do). In addition, you can restrict access of a certain token by making use of "access scopes":

In GAMS Engine, you can specify what you can do with a particular token: You can make a token accessible only to GET endpoints with the READONLY access scope, or you can specify which API endpoints (for example, JOBS or NAMESPACES) can be accessed with that particular token. This allows you to ensure, for example, that a particular CI job can only add/update/delete models but cannot submit new jobs, etc.

If you have an LDAP server or identity platform that supports OAuth2, you can integrate Engine with it. This transfers the responsibility for authentication (also authorization if OAuth2) to your identity provider. With an external identity provider, you can have:

• Centralized management for your users
• Additional security policies such as multi-factor authentication
• Single user account for many applications

The default identity provider of GAMS Engine is called gams_engine and it cannot be removed. The first admin must always use that identity provider. The term "external" identity provider refers to any identity provider other than the default identity provider. Adding, updating or deleting identity providers require admin privileges.

If no external identity providers have been added to Engine, you can continue to use the Engine identity provider as you always have. Engine will be the only place where passwords are stored.

Adding an identity provider does not bypass the invitation mechanism that we have in Engine. A user can have an identity in an external identity provider, but in order for them to log in, they have to be invited. So by default, users cannot log in to Engine without being invited.

In this tutorial, for the LDAP examples, we used jumpcloud but we have also tested with OpenLDAP and Active Directory. For the OAuth 2.0 examples, we used okta but we have also tested with Azure Active Directory (Azure AD).

In the following sections, we will talk about LDAP and OAuth 2.0 identity providers. In Engine API, you can list identity providers with GET /auth/providers endpoint. This endpoint does not require authentication because it contains information that is required for authentication. Also, this endpoint does not expose any secret fields. We consider following fields to be secret:

• Any LDAP information besides name and label
• web_ui_client_secret field for OAuth 2.0 providers

Many organizations use the Lightweight Directory Access Protocol (LDAP) servers to store user information and authentication. Engine can integrate with your LDAP server.

In a general authentication flow with LDAP, you must pass the LDAP credentials to the application, and the application talks to the LDAP server and authenticates you. This means that you trust the application, in this case GAMS Engine, with your credentials. This is why we prefer using OAuth2 over LDAP, because with OAuth2 you do not have to give your credentials. It is also very important that your communication is encrypted. Otherwise, your credentials will be transmitted insecurely and this is a big security risk.

Here is how an LDAP identity provider can be used in Engine:

1. Admin adds the identity provider to Engine
   • Adding an LDAP Identity Provider
2. Admin gives permission to an inviter to invite with this identity provider
   • Giving Permissions to Inviters to Invite with Identity Providers
3. The inviter invites a user with this identity provider
   • Inviting with an LDAP Identity Provider
4. User registers to Engine using the invitation token (only to get a username in Engine)
   • Registering when using an identity provider
5. User logs in to Engine using that identity provider
   • Login via an LDAP Identity Provider

Here is an example of adding jumpcloud as an LDAP identity provider. POST /auth/ldap-providers with body:

{
  "name": "jumpcloud-ldap",
  "label": "Login via jumpcloud",
  "hidden": false,
  "host": "ldap.jumpcloud.com",
  "port": 389,
  "uid": "uid",
  "bind_dn": "uid=readonlyadmin,ou=Users,o=YOUR_ORG_ID,dc=jumpcloud,dc=com",
  "encryption": "start_tls",
  "active_directory": false,
  "base": "ou=Users,o=YOUR_ORG_ID,dc=jumpcloud,dc=com",
  "user_filter": "(objectClass=inetOrgPerson)",
  "verify_certificates": true
}

If Engine is your only identity provider, inviters in your system can invite with Engine without specifying which identity provider the invitee can log in with.

Users with admin role can invite with any identity provider available in Engine. Inviters can invite only with identity providers for which they have permissions. Using an identity provider at login does not mean that the inviter can invite with it.

To query the list of identity providers a user can invite with, you can use the GET /users/inviters-providers/{username} endpoint. If you are an inviter, you can query users in your subtree. If you are an administrator, you can query everyone.

Similarly, to update the list of identity providers a user can invite with, you can use the PUT /users/inviters-providers/{username} endpoint. If you are an inviter, you can update inviters in your subtree. If you are an admin, you can update allowed identity providers for each inviter.

Let's say we have an inviter named johndoe, then we can give the inviter permissions to the new identity provider.
PUT /users/inviters-providers/johndoe with body:

{
    "name": ["gams_engine", "jumpcloud-ldap"]
}

Inviting with an identity provider is similar to inviting before the introduction of the identity providers feature. In addition to the fields you have already specified, you must specify identity_provider_name and identity_provider_user_subject.

POST /users/invitation with body:

{
    "namespace_permissions": ["7@global"],
    "identity_provider_name": "jumpcloud-ldap",
    "identity_provider_user_subject": "burak"
}

{
    "invitation_token": "15cd5eff-c503-4ae8-9f15-e83ab5f0afbc"
}

In this example, Engine will search for the user in the Distinguished Name "ou=Users,o=YOUR_ORG_ID,dc=jumpcloud,dc=com" with the filter "(&(objectClass=inetOrgPerson)(uid=burak))" at login because the uid field of the registered identity provider is "uid". For example, another uid field name commonly used in Active Directory is "sAMAccountName". In this case, the filter would be "(&(objectClass=inetOrgPerson)(sAMAccountName=burak))".

We have invited the user "burak" from jumpcloud LDAP, but the user cannot log in to Engine because he has to register first. Registering with Engine is necessary because the unique identifier of the user "burak" may already exist in Engine. Therefore, the username in Engine may be different from the username in LDAP.

The new user registers with a request to POST /users/ with body:

{
    "invitation_code": "15cd5eff-c503-4ae8-9f15-e83ab5f0afbc",
    "username": "burak_engine"
}

Now that our user has registered, he can log in to Engine with his credentials. It might be advantageous to remember the image from the introduction.

The URL for LDAP login is /auth/ldap-providers/{provider_name}/login. First, the user sends his credentials to Engine with a POST request to /auth/ldap-providers/jumpcloud-ldap/login with body:

{
    "username": "burak",
    "password": "verysecureldappassword",
    "scope": "NAMESPACES JOBS USERS HYPERCUBE USAGE"
}

{
    "token": "eyJhbGciOiJIUzUxMiIsInR5cCI6ImF0K2p3dCJ9.eyJpc3MiOiJodHRwOi8vbG9jYWxob3N0L2FwaSIsImV4cCI6MTY3MzAzMTQ3MiwiYXVkIjoiaHR0cDovL2xvY2FsaG9zdC9hcGkiLCJzdWIiOiIzIiwiY2xpZW50X2lkIjoicHVibGljIiwiaWF0IjoxNjcyNDI2NjcyLCJqdGkiOiIyYjY0MGI0YS1lYmVlLTQzZGUtOTkwYy02ZTNmZWYwYTU0ODQiLCJsZGFwX2lkIjoiNDdjM2M1ODEtN2ViOC00ZjMzLWFjZjgtNDVjZDljYTkyNDYxIn0.xxx",
}

You can also use Engine UI to log in through your identity provider. If you have set the hidden parameter to true, the LDAP Tab is not displayed on the login page. You can still view the tab by appending the query "provider=your_provider_name" to your login URL, for example: "https://your_engine_url.com/login?provider=jumpcloud"

Communication between Engine and your LDAP Provider

Troubleshooting LDAP Identity Provider

OAuth2 Identity Providers

1. Configuring your OAuth 2.0 provider and Engine hostname

{
    "hostname": "https://engine.somecompanynamehere.com/api"
}

2. Adding an OAuth 2.0 Identity Provider

{
    "name": "okta",
    "label": "Login via Okta",
    "hidden": false,
    "web_ui_client_id": "0oac41eda688759EE1C7",
    "issuer": "https://dev-xxxxxxxx.okta.com/oauth2/default",
    "authorization_endpoint": "https://dev-xxxxxxxx.okta.com/oauth2/default/v1/authorize",
    "token_endpoint": "https://dev-xxxxxxxx.okta.com/oauth2/default/v1/token",
    "jwks_uri": "https://dev-xxxxxxxx.okta.com/oauth2/default/v1/keys",
    "response_types_supported": [
                                    "code",
                                    "id_token",
                                    "code id_token",
                                    "code token",
                                    "id_token token",
                                    "code id_token token"
                                ],
    "grant_types_supported": ["authorization_code", "implicit", "refresh_token"],
    "end_session_endpoint": "https://dev-xxxxxxxx.okta.com/oauth2/default/v1/logout",
    "request_scope_NAMESPACES": "NAMESPACES",
    "request_scope_JOBS": "JOBS",
    "request_scope_USERS": "USERS",
    "request_scope_HYPERCUBE": "HYPERCUBE",
    "request_scope_CLEANUP": "CLEANUP",
    "request_scope_LICENSES": "LICENSES",
    "request_scope_USAGE": "USAGE",
    "request_scope_AUTH": "AUTH",
    "request_scope_CONFIGURATION": "CONFIGURATION"
}

{
    "name": "okta",
    "label": "Login via Okta",
    "hidden": false,
    "web_ui_client_id": "0oac41eda688759EE1C7",
    "issuer": "https://dev-xxxxxxxx.okta.com/oauth2/default",
    "use_oidc_discover": true
}

3. Giving Permissions to Inviters to Invite with Identity Providers

{
    "name": ["gams_engine", "okta"]
}

4.a.1 Inviting with an OAuth 2.0 Identity Provider with subject

{
    "namespace_permissions": ["7@global"],
    "identity_provider_name": "okta",
    "identity_provider_user_subject": "jane@somecompanymail.com"
}

{
    "invitation_token": "257bec97-8454-4f56-bedb-9e5ab23ca0a7"
}

4.a.2 Registering when using an OAuth 2.0 identity provider with subject

{
    "invitation_code": "257bec97-8454-4f56-bedb-9e5ab23ca0a7",
    "username": "jane"
}

4.b.1 Inviting with an OAuth 2.0 Identity Provider without subject

{
    "namespace_permissions": ["7@global"],
    "identity_provider_name": "okta",
}

{
    "invitation_token": "a5940eff-6837-4799-b477-646f32f9daca"
}

4.b.2 Registering when using an OAuth 2.0 identity provider without subject

{
    "invitation_code": "a5940eff-6837-4799-b477-646f32f9daca",
    "username": "jane",
    "identification_token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFt....."
}

5. Login via an OAuth 2.0 Identity Provider

Login via an OAuth 2.0 Identity Provider with private client

Troubleshooting OAuth 2.0 Identity Provider

OpenID Connect, OIDC, Identity Providers

1. Configuring your OIDC provider

2. Adding an OIDC Identity Provider

{
    "name": "google",
    "label": "Login via Google",
    "hidden": false,
    "web_ui_client_id": "0oac41eda688759EE1C7.apps.googleusercontent.com",
    "web_ui_client_secret": "some_client_secret",
    "device_client_id": "0ofc41edaAIKF59EE1C8.apps.googleusercontent.com",
    "device_client_secret": "anothersecuresecret",
    "issuer": "https://accounts.google.com",
    "authorization_endpoint": "https://accounts.google.com/o/oauth2/v2/auth",
    "token_endpoint": "https://oauth2.googleapis.com/token",
    "jwks_uri": "https://www.googleapis.com/oauth2/v3/certs",
    "device_authorization_endpoint": "https://oauth2.googleapis.com/device/code",
    "scopes": ["openid", "profile", "email"]
}

{
    "name": "google",
    "label": "Login via Google",
    "hidden": false,
    "web_ui_client_id": "0oac41eda688759EE1C7",
    "web_ui_client_secret": "some_client_secret",
    "device_client_id": "0ofc41edaAIKF59EE1C8",
    "device_client_secret": "anothersecuresecret",
    "issuer": "https://accounts.google.com",
    "use_oidc_discover": true,
    "scopes": ["openid", "profile", "email"]
}

3. Giving Permissions to Inviters to Invite with Identity Providers

{
    "name": ["gams_engine", "google"]
}

4.a.1 Inviting with an OIDC Identity Provider with subject

{
    "namespace_permissions": ["7@global"],
    "identity_provider_name": "google",
    "identity_provider_user_subject": "geralt@somecompanymail.com"
}

{
    "invitation_token": "85fbc868-654d-4a12-a323-58610b26c644"
}

4.a.2 Registering when using an OIDC identity provider with subject

{
    "invitation_code": "85fbc868-654d-4a12-a323-58610b26c644",
    "username": "geralt"
}

4.b.1 Inviting with an OIDC Identity Provider without subject

{
    "namespace_permissions": ["7@global"],
    "identity_provider_name": "google",
}

{
    "invitation_token": "f13f0a78-5b2f-4721-857f-610ee985d030"
}

4.b.2 Registering when using an OIDC identity provider without subject

{
    "invitation_code":  "f13f0a78-5b2f-4721-857f-610ee985d030",
    "username": "geralt",
    "identification_token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFt....."
}

5. Login via an OIDC Identity Provider

GAMS Engine allows you to limit the solve time as well as the disk usage of individual users or groups of users.

Let's take the user hierarchy from the previous section on user management to give you an example of how quotas work:

Only admins and inviters can update quotas of users. While admins can update the quotas of all users, inviters can only update the quotas of direct/indirect invitees (we also call this the "subtree" of an inviter). An inviter cannot assign a quota larger than his own

There are three types of quotas that can be assigned: volume_quota, disk_quota and parallel_quota (only used in Engine Kubernetes version).

If "Admin" sets the volume_quota of "Student 1" to 60 seconds, the student can only run jobs for one minute. If the quota is exceeded, new jobs submitted by "Student 1" are rejected by Engine. In addition, currently active jobs are canceled (using SIGKILL) when the volume quota of the user who submitted the job is exhausted.

If "Admin" sets the volume_quota of "Teacher" to 1800 seconds, it means that the "Teacher", "Student 1", "Student 2", "Assistant" and anyone invited by the "Assistant" can run GAMS for a total of 1800 seconds. This allows administrators to invite new "entities" by creating a new inviter that has quotas assigned to it. Both the inviter and anyone invited by that inviter are now limited by those quotas.

Quotas allow further restrictions. Imagine the case where "Admin" has assigned 1800 seconds of volume_quota to "Teacher". As an inviter, "Teacher" can give students any volume_quota that is less than or equal to 1800 seconds. "Teacher" could give "Student 1" and "Student 2" each 600 seconds and "Assistant" 800 seconds. In this case, "Student 1" can use up to 600 seconds, "Student 2" can use up to 600 seconds, and "Assistant" can use up to 800 seconds.

Quotas allow for overbooking. An attentive reader may have noticed that in the last example, the teacher had 1800 seconds, but she provided a total of 2000 seconds for her invitees. This does not mean that the teacher's subtree had a total of more than 1800 seconds. When "Student 1" and "Student 2" have used up their entire allotment, the "Assistant" still has 600 seconds left. Therefore, he can no longer use up the full 800 seconds allocated to him by the teacher.

disk_quota is used to limit the disk usage of a user as well as the user's invitees (if any). The following files contribute to disk usage:

• Temporary/unregistered models
• Additional data provided with the (Hypercube) job
• Inex files provided with the (Hypercube) job
• (Hypercube) job results

If the disk_quota is exceeded, GAMS Engine rejects all new jobs submitted by users who have exceeded their quotas. When a worker receives a job from a user whose disk_quota is exceeded, it is cancelled.

The disk space used during solving does not contribute to the disk_quota. A job could use more disk space during solving, but only upload a small portion (perhaps a result GDX file) and would not violate the quota.

Unlike volume_quota, disk_quota has a grace space. When a job is solved, it might be undesirable to refuse to upload the result because the disk_quota is exceeded. In this scenario, the result will be uploaded if it does not exceed disk_quota + 1GB. If the grace space is also exceeded, the job is marked as "Corrupted" and the results are not available.

disk_quota allows you to limit unregistered files. To limit registered files, such as registered models, inex files, etc. admins can assign a disk_quota to namespaces (available via the /namespaces/{namespace}/disk-quota API).

Similar to the volume_quota, the disk_quota allows further restrictions for invited users as well as overbooking.

While jobs in Engine One share available resources, in Engine SaaS you must assign resource requests to a job. Engine then takes care of scheduling these heterogeneous jobs on the available hardware. Assigning resource requests is done via the labels field in the POST /jobs/ / POST /hypercube/ endpoints.

The labels field is an array of key=value pairs. The following table lists the available keys for assigning resource requests:

Assigning resource requests directly to a job is very powerful and flexible. However, you may want to limit which resources your users can use. Also, users usually don't need this level of flexibility. This is where the concept of instances comes into play, which will be described in the next chapter.

Instances are a way to bundle resource requests under a single label. For example, we could define a new instance with 4 vCPU, 4000 MiB of memory and a workspace size of 10000 MiB and assign it the label small. Instead of assigning the resource requests directly to the job, we can assign the instance label instead (e.g. "small"). Internally, this label is then replaced by the corresponding resource requirements. We do this using the key: instance; in our example: instance=small. If you use the instance label, you cannot use one of the labels to specify resources directly at the same time, and vice versa.

Instances can be assigned to users via the PUT /usage/instances/{username} endpoint. When a user is assigned instances, they can no longer use the raw resource requests (cpu_request, memory_request etc.). Instead, they must select from one of the instances assigned to them. When instances are assigned to a user, a default instance should also be selected. If the user does not specify an instance for a job, this default instance is used. Users can update their own default instance via the PUT /usage/instances/{username}/default endpoint.

If a user has no instances assigned, she inherits the instances from her inviter. If the inviter itself has no instances assigned or inherits them from its inviter, the user can use raw resource requests or select an arbitrary instance. The list of all available instances can be queried via the GET /usage/instances endpoint. Users who do not have instances assigned can still select a default instance for convenience. Admins cannot be assigned instances.

When you invite new users, you cannot assign instances to which you do not have access yourself. Thus, the invitees can only be further restricted in terms of permissible instances.

Below is an example of how instances are inherited. Boxes with a dashed gray border indicate that instances are not directly assigned to the user, but he inherits them from his inviter. Boxes with a solid black border indicate that instances are explicitly assigned to the user.

When creating a new instance, you have to specify both a multiplier as well as a multiplier_idle. Every second that a job runs on this instance, the multiplier is subtracted from the volume quota of the user who created that job. While a worker is idle in an instance pool, the multiplier_idle is subtracted from the volume quota of the user who created the pool.

When you create a new job on Engine SaaS, a new worker (a Kubernetes job) is created with the specified resources. Depending on whether or not the required resources already exist in the cluster, new resources may need to be added to the cluster first (if the cluster supports this, e.g. in cloud environments such as Engine SaaS). Adding resources to the cluster, as well as creating a worker, involves some overhead that may be undesirable, especially if you have time-critical or short-running jobs.

In such situations, you may prefer to create an instance pool: a number of workers with a homogeneous instance and a custom label to uniquely identify the pool. Instance pools can be created (via the POST /usage/pools endpoint) for any instance you have access to and can be scaled up or down at any time. When creating an instance pool, the specified number of workers is created (with the overhead mentioned above). These workers continue to run until the instance pool is either scaled down (via the PUT /usage/pools endpoint) or deleted (via the DELETE /usage/pools endpoint).

To run a job in an instance pool, simply specify the label of the pool as the instance. For example, to run a job in a pool named my_pool, specify: instance=my_pool. If there are free workers in the pool, the job is started immediately. If all workers in the pool are busy, the job is queued.

When you reduce the number of workers in a pool, Engine will first try to shut down workers that are not busy. If there are not enough free workers available, busy workers are shut down. The jobs on these workers are re-queued.

While a job is running, the multiplier of the instance is subtracted from your volume quota every second. If a worker is idle, the multiplier_idle is used instead.

Instance pools can be assigned and inherited just like instances. When you create an instance pool, your inviter (and all its ancestors) can access your pool.

To retrieve all instance pools that a user has access to, use the GET /usage/pools/{username} endpoint (admins can also retrieve all instance pools using the GET /usage/pools endpoint).

An instance pool can be set as a default instance just like a normal instance using the PUT /usage/instances/{username}/default endpoint.

Over time, the amount of disk space required on the server can grow accordingly. It is the responsibility of the admin to ensure that the result data is deleted when required. Engine API provides a cleanup endpoint for this purpose.

When working with Engine UI, you can reduce the amount of disk space used by GAMS Engine using the Cleanup view. You can either remove result files of individual jobs one by one or clean up multiple files at once using the Run housekeeping dialog. This allows you to remove all files created more than x days ago and/or files created by users who have been removed from the system.

For production servers, we recommend tracking logs of GAMS Engine to ensure system stability. You can use solutions such as EFK or ELK stack. Regardless of which solution you use, you need to familiarize yourself with GAMS Engine's core parts and their logging formats.

In GAMS Engine, we chose RabbitMQ as the message broker solution. When the cluster is first spun up, RabbitMQ creates the necessary queues, exchanges, and users. This part of the process creates non-standard protocols. However, it is usually okay to skip this part as it is only done once. After that, the logging format is standard. An example of a RabbitMQ log entry: 2021-10-20 11:46:16.006 [info] <0.941.0> accepting AMQP connection <0.941.0> (172.19.0.5:46598 -> 172.19.0.2:5672)

We chose PostgreSQL to store most of the structured data. Similar to RabbitMQ, PostgreSQL also creates the required tables and users on the first run, so it creates non-default logs. Skipping these logs should not be a problem either, as they are only issued once. An example of a PostgreSQL log entry: 2021-10-20 11:46:02.076 UTC [1] LOG: database system is ready to accept connection

MongoDB stores some of the structured data and all of the unstructured data. Its bootstrap process is also similar to RabbitMQ and PostgreSQL. A sample log of MongoDB looks like this: 2021-10-20T11:46:07.054+0000 I NETWORK [initandlisten] waiting for connections on port 27017

The logging format of the Worker,Cleaner,Hypercube Unpacker,Hypercube Appender, Dependency Checker,Job Watcher,Job Spawner, Job Cleaner,Job Canceler containers is standardized. An example log a worker is [20/10/2021 11:46:16] INFO #: Waiting for job.. The hash sign (#) after the severity (INFO) indicates which job is associated with this log. In this case, no job is associated with this log. Another log of a worker: [20/10/2021 12:11:54] INFO 1: Job Received indicates that the worker got the job with id 1. For Hypercubes, the log format is different. For example [20/10/2021 12:13:18] DEBUG 4@617007d8917cb774979dab76: Working directory cleaned this log refers to the the 4th job of the Hypercube job 617007d8917cb774979dab76. This log format facilitates the retrieval of logs that refer to a single job from multiple containers.

REST API backend log format is different from the other log formats. We should address that the backend is reverse proxied by nginx. nginx log format is different from the backend log format but it is widely-known. An example log is 172.22.0.1 - - [20/Oct/2021:12:12:58 +0000] "GET /api/jobs/status-codes HTTP/1.1" 200 385 "http://localhost:30001/" "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:93.0) Gecko/20100101 Firefox/93.0" "-" Backend is a WSGI app and here is an example log [pid: 13] 172.22.0.1 (admin 1) [20/Oct/2021:12:13:01 +0000] apis.ns_users INFO User 'admin' listed all the users. We also log the user ID after the user name because it is possible to change the user name. However, the logs that come from uWSGI do not log the user ID. [pid: 13] 172.22.0.1 (-) [20/Oct/2021:12:11:49 +0000] uwsgi INFO {36 vars in 401 bytes} [Wed Oct 20 12:11:49 2021] GET /api/version => generated 72 bytes in 6 msecs (HTTP/1.1 200) 3 headers in 108 bytes (1 switches on core 0)

Instead of polling Engine for specific events, such as when a particular job has finished, Engine also supports sending this information in the form of webhooks: HTTP POST requests to a specified URL. Per default, webhooks are disabled. However, you can enable it either for administrators only or for everyone via the configuration API. A webhook configuration consists of the following components:

URL

The URL that receives the payload of the HTTP POST request.

Content Type

The media type used to serialize the data. Possible values are form (default) and json. When choosing form, the content type will be set to application/x-www-form-urlencoded, when choosing json, the content type will be application/json.

Secret

If a secret is specified, an additional header: X-ENGINE-HMAC is sent, which contains the HMAC (SHA-256) of the (raw) request body. The secret must be at least 8 characters long. Below is an example of HMAC validation in Node.js:

const crypto = require('crypto');
const validateHmac = (requestHeaders, requestBody, secret) => {
  if (!('x-engine-hmac' in requestHeaders)) {
    return false;
  }
  const hmac = crypto.createHmac('sha256', secret);
  const signature = Buffer.from(requestHeaders['x-engine-hmac'], 'utf8');
  const digest = Buffer.from('sha256=' + hmac.update(requestBody).digest('hex'), 'utf8');
  return crypto.timingSafeEqual(digest, signature);
}

Recursive

When the recursive flag is set, the webhook applies not only to events of the webhook owner, but also to all her invitees. If the webhook owner is an administrator, a recursive webhook applies to each user's events.

Events

The events to subscribe to. A list of possible events and their payloads is given below. The special ALL event can be specified to subscribe to all events.

Parameterized Events

Certain events (e.g. reaching a certain volume quota threshold or order duration) require parameters. These events must be specified in the form EVENT_NAME=EVENT_PARAMETER (e.g. VOLUME_QUOTA_THRESHOLD=3600 to be notified when the remaining volume quota falls below a threshold of 3600 seconds).

Insecure SSL

If this flag is set, no SSL certificate validation is performed when the webhook is sent over SSL. We strongly recommend that you do NOT disable certificate validation for security reasons.

The request body of a webhook always has the same structure: a JSON-encoded object with the fields: event (string), which specifies the name of the event, username (string), which specifies the name of the user who registered the webhook, payload (object), which contains the payload of the event as well as text (string) and content (string) that both contain a human-readable representation of the event (useful, for example, for getting notified via business communication tools such as Slack, Microsoft Teams, Discord). The payloads for all supported event types are described in detail below.

In case the content type of the webhook is set to form, the entire JSON payload is sent as a form parameter called payload.

An example of a webhook payload of a JOB_FINISHED event is shown below:

{
  "event": "JOB_FINISHED",
  "username": "shanghai",
  "text": "GAMS Engine job of the user: 'shanghai' and token: '46bbf80d-262f-4257-86ee-4881164d6b0c' finished.",
  "content": "GAMS Engine job of the user: 'shanghai' and token: '46bbf80d-262f-4257-86ee-4881164d6b0c' finished.",
  "payload": {
    "token": "46bbf80d-262f-4257-86ee-4881164d6b0c",
    "model": "trnsport",
    "is_temporary_model": true,
    "is_data_provided": false,
    "status": 10,
    "process_status": 0,
    "stdout_filename": "log_stdout.txt",
    "namespace": "global",
    "arguments": [
      "LP=CBC",
      "--bla=def"
    ],
    "labels": null
    "submitted_at": "2022-03-23T09:43:42.783211",
    "finished_at": "2022-03-23T09:43:43.056074",
    "user": {
      "username": "shanghai",
      "deleted": false,
      "old_username": null
    }
  }
}
                  

HC_JOB_DURATION_THRESHOLD

This event is triggered when a job of a Hypercube job runs for a certain time. The threshold value is specified when setting up the webhook.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": false,
  "status": 10,
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted": "2022-03-17T17:01:37.406000+00:00",
  "finished": "2022-03-17T17:01:39.878000+00:00",
  "job_count": 2,
  "completed": 2,
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  },
  "threshold_level": 7200
}
    

HC_JOB_FINISHED

This event is triggered when a Hypercube job is finished.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": false,
  "status": 10,
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted": "2022-03-17T17:01:37.406000+00:00",
  "finished": "2022-03-17T17:01:39.878000+00:00",
  "job_count": 2,
  "completed": 2,
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  }
}
    

HC_JOB_OUT_OF_RESOURCES

This event is triggered when a Hypercube job ran out of resources. Note that this event is triggered as soon as the resource is exhausted. This can be before or after the `HC_JOB_FINISHED` event is triggered.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": false,
  "status": 10,
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted": "2022-03-17T17:01:37.406000+00:00",
  "finished": "2022-03-17T17:01:39.878000+00:00",
  "job_count": 2,
  "completed": 2,
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  }
}
    

JOB_DURATION_THRESHOLD

This event is triggered when a job runs for a certain time. The threshold value is specified when setting up the webhook.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": true,
  "status": 10,
  "process_status": 0,
  "stdout_filename": "log_stdout.txt",
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted_at": "2022-03-17T17:01:37.406000+00:00",
  "finished_at": "2022-03-17T17:01:39.878000+00:00",
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  },
  "threshold_level": 7200
}
    

JOB_FINISHED

This event is triggered when a job (not a Hypercube job) is finished.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": true,
  "status": 10,
  "process_status": 0,
  "stdout_filename": "log_stdout.txt",
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted_at": "2022-03-17T17:01:37.406000+00:00",
  "finished_at": "2022-03-17T17:01:39.878000+00:00",
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  }
}
    

JOB_OUT_OF_RESOURCES

This event is triggered when a job (not a Hypercube job) ran out of resources. Note that this event is triggered as soon as the resource is exhausted. This can be before or after the `JOB_FINISHED` event is triggered.

Webhook payload object

Webhook payload example

{
  "token": "332f6438-6485-416c-b893-089524259153",
  "model": "trnsport",
  "is_temporary_model": true,
  "is_data_provided": true,
  "status": 10,
  "process_status": 0,
  "stdout_filename": "log_stdout.txt",
  "namespace": "global",
  "arguments": [
    "LP=CBC",
    "--mode=ENGINE"
  ],
  "labels": {
    "cpu_request": 23.7,
    "memory_request": 188100,
    "workspace_request": 50000,
    "tolerations": [],
    "node_selectors": [
      {
        "key": "gams.com/instanceType",
        "value": "z1d.6xlarge"
      }
    ],
    "instance": "z1d.6xlarge",
    "multiplier": 2.5,
    "resource_warning": "memory"
  },
  "submitted_at": "2022-03-17T17:01:37.406000+00:00",
  "finished_at": "2022-03-17T17:01:39.878000+00:00",
  "user": {
    "username": "admin",
    "deleted": false,
    "old_username": null
  }
}
    

VOLUME_QUOTA_THRESHOLD

This event is triggered when a certain threshold value of the volume quota is reached. The threshold value is specified when setting up the webhook.

Webhook payload object

Webhook payload example

{
  "threshold_level": 3600,
  "quota_user": {
    "username": "janedoe",
    "deleted": false,
    "old_username": null
  },
  "trigger_user": {
    "username": "johndoe",
    "deleted": false,
    "old_username": null
  },
  "trigger_type": "job"
}