# Using the Deadline Cloud monitor
The AWS Deadline Cloud monitor provides you with an overall view of your visual compute jobs. You can use it to monitor and manage jobs, view worker activity on fleets, track budgets and usage, and to download a job's results.
Each queue has a job monitor that shows you the status of jobs, steps, and tasks. The monitor provides ways to manage jobs directly from the monitor. You can make prioritization changes, cancel jobs, requeue jobs, and resubmit jobs.
The Deadline Cloud monitor has a table that shows summary status for a job, or you can select a job to see detailed task logs that help troubleshoot issues with a job.
You can use the Deadline Cloud monitor to download the results to the location on your workstation that was specified when the job was created.
The Deadline Cloud monitor also helps you monitor usage and manage costs. For more information, see [Track spending and usage for Deadline Cloud farms](manage-costs.md).
**Topics**
+ [Create monitors in additional Regions](monitors-additional-regions.md)
+ [Share the Deadline Cloud monitor URL](share-monitor-url.md)
+ [Open the Deadline Cloud monitor](open-deadline-cloud-monitor.md)
+ [Submit a job bundle](submit-job-bundle-monitor.md)
+ [View queue and fleet details in Deadline Cloud](view-queue-and-fleet.md)
+ [Manage jobs, steps, and tasks in Deadline Cloud](view-jobs-steps-tasks.md)
+ [View and manage job details in Deadline Cloud](view-a-job.md)
+ [View a step in Deadline Cloud](view-a-step.md)
+ [View a task in Deadline Cloud](view-a-task.md)
+ [View session and worker logs in Deadline Cloud](view-logs.md)
+ [View worker details in the worker dashboard](view-worker-dashboard.md)
+ [Download finished output in Deadline Cloud](download-finished-output.md)
+ [Automate Deadline Cloud monitor desktop deployment and workflows](monitor-automate-desktop.md)
# Create monitors in additional Regions
Each Deadline Cloud monitor manages resources in a single AWS Region. To manage resources in additional Regions, you can create a separate monitor in each Region.
If your IAM Identity Center instance is not available in the Region where you want to create a monitor, you have the following options:
+ **Cross-Region IAM Identity Center access** – Create a monitor in a different Region, and Deadline Cloud reads IAM Identity Center identity data from the Region where your IAM Identity Center instance is located. This option requires no changes to your IAM Identity Center configuration.
+ **IAM Identity Center multi-Region replication** – Replicate your IAM Identity Center instance to additional Regions so that monitors in those Regions use an IAM Identity Center replica in the same Region. This option provides lower latency and regional availability, but requires additional IAM Identity Center configuration.
The following diagram shows how each approach works.
![\[Diagram comparing cross-Region IAM Identity Center access and IAM Identity Center multi-Region replication for Deadline Cloud monitors.\]](http://docs.aws.amazon.com/deadline-cloud/latest/userguide/images/monitors-additional-regions.png)
The following table compares the two approaches.
**Comparison of multi-Region approaches**
| Consideration | Cross-Region IAM Identity Center access | IAM Identity Center multi-Region replication |
| --- | --- | --- |
| Setup requirements | No additional IAM Identity Center setup required | Requires configuring IAM Identity Center replication |
| Identity data location | Remains in the IAM Identity Center Region only | Replicated to each configured Region |
| Latency | Depends on distance to the IAM Identity Center Region | Lower latency when an IAM Identity Center replica is in the same Region |
| Regional availability | Depends on IAM Identity Center Region availability | Continues to work if the IAM Identity Center primary Region is unavailable |
## Cross-Region IAM Identity Center access
With cross-Region IAM Identity Center access, you create an Deadline Cloud monitor in a different Region than your IAM Identity Center instance. Deadline Cloud reads IAM Identity Center identity data from the Region where your IAM Identity Center instance is located.
When you create a monitor using the Deadline Cloud console, the console automatically detects your IAM Identity Center instance and connects the monitor to it, even if the instance is in a different Region. When you create a monitor using an AWS SDK, specify the Region where your IAM Identity Center instance is located.
### Considerations
+ Cross-Region IAM Identity Center access requires your IAM Identity Center instance to be in a commercial AWS Region. IAM Identity Center instances in opt-in Regions aren't supported.
+ You can't change the IAM Identity Center Region after you create the monitor.
## IAM Identity Center multi-Region replication
IAM Identity Center multi-Region replication synchronizes your IAM Identity Center identity store data, including users, groups, and group memberships, to additional AWS Regions. After you enable replication to a Region, you can connect your monitor in that Region to the IAM Identity Center replica.
Multi-Region replication is useful in the following scenarios:
+ You need lower latency for users closer to the replicated Region.
+ You need monitors that continue to work if the IAM Identity Center primary Region is unavailable.
To enable multi-Region replication, see [Using IAM Identity Center across multiple AWS Regions](https://docs.aws.amazon.com/singlesignon/latest/userguide/multi-region-iam-identity-center.html) in the *IAM Identity Center User Guide*. After you enable replication for a Region, you can create Deadline Cloud monitors there by using the console or an AWS SDK.
# Share the Deadline Cloud monitor URL
When you set up the Deadline Cloud service, by default you create a URL that opens the Deadline Cloud monitor for your account. Use this URL to open the monitor in your browser or on your desktop. Share the URL with other users so that they can access the Deadline Cloud monitor.
Before a user can open the Deadline Cloud monitor, you must grant the user access. To grant access, either add the user to the list of authorized users for the monitor or add them to a group with access to the monitor. For more information, see [Managing users in Deadline Cloud](managing-users.md).
**To share the monitor URL**
1. Open the [Deadline Cloud console](https://console.aws.amazon.com/deadlinecloud/home).
1. From **Get started**, choose **Go to Deadline Cloud dashboard**.
1. On the navigation pane, choose **Dashboard**.
1. In the **Account overview** section, choose **Account details**.
1. Copy and then securely send the **URL** to anyone who needs to access the Deadline Cloud monitor.
# Open the Deadline Cloud monitor
You can open the Deadline Cloud monitor by any of the following ways:
+ **Console** – Sign in to the AWS Management Console and open the Deadline Cloud console.
+ **Web** – Go to the monitor URL that you created when you set up Deadline Cloud.
+ **Monitor** – Use the desktop Deadline Cloud monitor.
When you use the console, you must be able to sign in to AWS using an AWS Identity and Access Management identity, and then sign in to the monitor with AWS IAM Identity Center credentials. If you only have IAM Identity Center credentials, you must sign in using the monitor URL or the desktop application.
**To open the Deadline Cloud monitor (web)**
1. Using a browser, open the monitor URL that you created when you set up Deadline Cloud.
1. Sign in with your user credentials.
**To open the Deadline Cloud monitor (console)**
1. Open the [Deadline Cloud console](https://console.aws.amazon.com/deadlinecloud/home).
1. In the navigation pane, select **Farms**.
1. Select a farm, then choose **Manage jobs** to open the **Deadline Cloud monitor** page.
1. Sign in with your user credentials.
**To open the Deadline Cloud monitor (desktop)**
1. Open the [Deadline Cloud console](https://console.aws.amazon.com/deadlinecloud/home).
-or-
Open the Deadline Cloud monitor - web from the monitor URL.
1.
+ On the Deadline Cloud console, do the following:
1. In the monitor, choose **Go to Deadline Cloud dashboard**, and then choose **Downloads** from the left menu.
1. From **Deadline Cloud monitor**, choose the monitor version for your desktop.
1. Choose **Download**.
+ On the Deadline Cloud monitor - web, do the following:
+ From the left menu, choose **Workstation setup**. If the **Workstation setup** item isn't visible, use the arrow to open the left menu.
+ Choose **Download**.
+ From **Select an OS**, choose your operating system.
1. Download the Deadline Cloud monitor - desktop.
1. After you download and install the monitor, open it on your computer.
+ If this is your first time opening the Deadline Cloud monitor, you must provide the monitor URL and create a profile name. Next you sign in to the monitor with your Deadline Cloud credentials.
+ After you create a profile, you open the monitor by selecting a profile. You might need to enter your Deadline Cloud credentials.
## Change your language settings
After you create and open your Deadline Cloud monitor, you can change your language settings. By default, the monitor language is set to your system's language settings.
**To change your language settings from Deadline Cloud monitor (desktop)**
1. From your user profile, select **Settings**, then choose **Language**.
1. From the dropdown menu, select one of the available languages.
1. Confirm that your chosen language is the listed option, then choose **Confirm and apply** to apply the change.
After the monitor refreshes, it displays in the chosen language.
After you change the language setting, it is the default upon opening and remains the default until you change it again or uninstall the desktop application.
**To change the Deadline Cloud monitor language on the web, change the preferred language in your browser settings.**
**Note**
If your browser or operating system is set to a language that is not supported by Deadline Cloud, English becomes the default language for Deadline Cloud monitor.
# Submit a job bundle
You can submit a job bundle directly from the AWS Deadline Cloud monitor desktop application. A job bundle is a directory that contains the files and information needed to submit a job to Deadline Cloud. For sample job bundles, see the [deadline-cloud-samples](https://github.com/aws-deadline/deadline-cloud-samples) repository on GitHub.
**To submit a job bundle**
+ In the Deadline Cloud monitor desktop application, choose **File**, **Submit Job Bundle**. This feature is not available in the Linux AppImage or MacOS x64 builds.
# View queue and fleet details in Deadline Cloud
You can use the Deadline Cloud monitor to view the configuration of the queues and fleets in your farm. You can also use the monitor to see a list of the jobs in a queue or the workers in a fleet.
You must have `VIEWING` permission to view queue and fleet details. If the details don't display, contact your administrator to get the correct permissions.
**To view queue details**
1. [Open the Deadline Cloud monitor](open-deadline-cloud-monitor.md).
1. From the list of farms, choose the farm that contains the queue that you're interested in.
1. In the list of queues, choose a queue to display its details. To compare the configuration of two or more queues, select more than one check box.
1. To see a list of jobs in the queue, choose the queue name from the list of queues or from the details panel.
If the monitor is already open, you can select the queue from the **Queues** list in the left navigation pane.
**To view fleet details**
1. [Open the Deadline Cloud monitor](open-deadline-cloud-monitor.md).
1. From the list of farms, choose the farm that contains the fleet that you're interested in.
1. In **Farm resources**, choose **Fleets**.
1. In the list of fleets, choose a fleet to display its details. To compare the configuration of two or more fleets, select more than one check box.
1. To see a list of workers in the fleet, choose the fleet name from the list of fleets or from the details panel.
If the monitor is already open, you can select the fleet from the **Fleets** list in the left navigation pane.
# Manage jobs, steps, and tasks in Deadline Cloud
When you select a queue, the job monitor section of the Deadline Cloud monitor shows you the jobs in that queue, the steps in the job, and the tasks in each step. When you select a job, step, or task, you can use the **Actions** menu to manage each.
To open the job monitor, follow the steps to view a queue in [View queue and fleet details in Deadline Cloud](view-queue-and-fleet.md), then select the job, step, or task to work with.
For jobs, steps, and tasks, you can do the following:
+ Change the status to **Requeued**, **Succeeded**, **Failed**, or **Canceled**.
+ Download the processed output from the job, step, or task.
+ Copy the ID of the job, step, or task.
For the selected job, you can:
+ Archive the job.
+ Modify the job properties, including name, description, priority, or max worker count.
+ View step to step dependencies.
+ View additional details using the job's parameters.
+ Resubmit the job.
For for more information, see [View and manage job details in Deadline Cloud](view-a-job.md).
For each step, you can:
+ View the dependencies for the step. The dependencies for a step must be completed before the step runs.
For details, see [View a step in Deadline Cloud](view-a-step.md).
For each task, you can:
+ View logs for the task.
+ View task parameters.
For more information, see [View a task in Deadline Cloud](view-a-task.md).
# View and manage job details in Deadline Cloud
The **Job monitor** page in the Deadline Cloud monitor provides you with the following:
+ An overall view of the progress of a job.
+ A view of the steps and tasks that make up the job.
Choose a job from the list to view a list of steps for the job, and then choose a step from the list of steps to view the tasks for the job. After you choose an item, you can use the **Actions** menu for that item to view details.
**To view job details**
1. Follow the steps to view a queue in [View queue and fleet details in Deadline Cloud](view-queue-and-fleet.md).
1. In the navigation pane, select the queue where you submitted your job.
1. Select a job using one of the following methods:
1. From the **Jobs** list, select a job to view its details.
1. From the **search** field, enter any text associated with the job, such as the job name or user that created the job. From the results that display, select the job you want to view.
The details of a job include the steps in the job and the tasks in each step. You can use the **Actions** menu to do the following:
+ Change the status of the job.
+ View and modify the properties of a job.
+ You can view the dependencies between steps in the job.
+ You can change the priority of the job in a queue. Jobs with higher number priority are processed before jobs with lower number priority. Jobs can have a priority between 1 and 100. When two jobs have the same priority, the oldest job is scheduled first.
+ View the parameters for the job that were set when the job was submitted.
+ Download the output of a job. When you download the output of a job, it contains all of the output generated by the steps and tasks in the job.
## Archive a job
To archive a job, it must be in a terminal state, `FAILED`, `SUCCEEDED`, `SUSPENDED`, or `CANCELED`. The `ARCHIVED` state is final. After a job is archived, it can't be requeued or modified.
The job's data is not affected by archiving the job. The data is deleted when the inactivity timeout is reached, or when the queue containing the job is deleted.
Other things that happen to archived jobs:
+ Archived jobs are hidden in the Deadline Cloud monitor.
+ Archived jobs are visible in a read-only state form the Deadline Cloud CLI for 120 days before deletion.
## Requeue a job
When you requeue a job, all of the tasks without step dependencies switch to `READY`. The status of steps with dependencies switch to `READY` or `PENDING` as they are restored.
+ All jobs, steps, and tasks switch to `PENDING`.
+ If a step doesn't have a dependency, it switches to `READY`.
## Resubmit a job
There might be times when you want to run a job again, but with different properties and settings. For example, you might submit a job to render a subset of testing frames, verify the output, then run the job again with the full frame range. To do this, resubmit the job.
When you resubmit a job, new tasks without dependencies become `READY`. New tasks with dependencies become `PENDING`.
+ All new jobs, steps, and tasks become `PENDING`.
+ If a new step doesn't have a dependency, it becomes `READY`.
When you resubmit a job, you can only change properties that were defined as configurable when the job was first created. For example, if the name of a job is not defined as a configurable property of the job when first submitted, then the name cannot be edited on resubmission.
# View a step in Deadline Cloud
Use the AWS Deadline Cloud monitor to view the steps in your processing jobs. In the **Job monitor**, the **Steps** list shows the list of steps that make up the selected job. When you select a step, the **Tasks** list shows the tasks in the step.
**To view a step**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select a job from the **Jobs** list.
1. Select a step from the **Steps** list.
You can use the **Actions** menu to do the following:
+ Change the status of the step.
+ Download the output of the step. When you download the output of a step, it contains all of the output generated by the tasks in the step.
+ View the dependencies of a step. The dependencies table shows a list of steps that must be complete before the selected step starts, and a list of steps that are waiting for this step to complete.
# View a task in Deadline Cloud
Use the AWS Deadline Cloud monitor to view the tasks in your processing jobs. In the **Job monitor**, the **Tasks** list shows the tasks that make up the step selected in the **Steps** list.
**To view a task**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select a job from the **Jobs** list.
1. Select a step from the **Steps** list.
1. Select a task from the **Tasks** list.
You can use the **Actions** menu to do the following:
+ Change the status of the task.
+ View task logs. For more information, see [View session and worker logs in Deadline Cloud](view-logs.md).
+ View that parameters that were set when the task was created.
+ Download the output of the task. When you download the output of a task, it only contains the output generated by the selected task.
# View session and worker logs in Deadline Cloud
Logs provide you with detailed information about the status and processing of tasks. In the AWS Deadline Cloud monitor, you can see the following two types of logs:
+ Session logs detail the timeline of actions, including:
+ Setup actions, such as attachment syncing and loading the software environment
+ Running a task or set of tasks
+ Closure actions, such as shutting down the environment on a worker
A session includes processing of at least one task, and can include multiple tasks. Session logs also show information about Amazon Elastic Compute Cloud (Amazon EC2) instance type, vCPU, and memory. Session logs also include a link to the log for the worker used in the session.
+ Worker logs provide details for the timeline of actions that a worker processes during its lifecycle. Worker logs can contain information about multiple sessions.
You can download session and worker logs so that you can examine them offline.
**To view session logs**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select a job from the **Jobs** list.
1. Select a step from the **Steps** list.
1. Select a task from the **Tasks** list.
1. From the **Actions** menu, choose **View logs**.
The **Timelines** section shows a summary of the actions for the task. To see more tasks run in the session and to see the shutdown actions for the session, choose **View logs for all tasks**.
**To view worker logs from a task**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select a job from the **Jobs** list.
1. Select a step from the **Steps** list.
1. Select a task from the **Tasks** list.
1. From the **Actions** menu, choose **View logs**.
1. Choose **Session info**.
1. Choose **View worker log**.
**To view worker logs from fleet details**
1. Follow the steps in [View queue and fleet details in Deadline Cloud](view-queue-and-fleet.md) to view a fleet.
1. Select a **Worker ID** from the **Workers** list.
1. From the **Actions** menu, choose **View worker logs**.
# View worker details in the worker dashboard
The *worker dashboard* provides details for the worker that processes a task. You can see:
+ Metadata, such as the instance type, for the worker
+ The session actions that the worker performed
+ Worker performance, including CPU, memory and disk usage
+ A graph of the CPU, memory, and disk usage over time
+ A graph of the disk speed over time
+ The worker log for the task
**To view the worker dashboard from a task**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select a job from the **Jobs** list.
1. Select a step from the **Steps** list.
1. Select a task from the **Tasks** list.
1. In the task table, from the **Actions** menu, choose **View worker dashboard**.
**To view the worker dashboard from fleet details**
1. Follow the steps in [View queue and fleet details in Deadline Cloud](view-queue-and-fleet.md) to view a fleet.
1. Select a **Worker** from the **Workers** list.
1. From the **Actions** menu, choose **View worker dashboard**.
## Use cases
### Detecting under-provisioned instances
When renders take longer than expected, the worker dashboard can help determine if your instances are adequately sized for your workloads. While 100% vCPU utilization is normal for many renderers, consistently high memory usage near maximum capacity and elevated disk space utilization may indicate that your instances are under-provisioned. In such cases, upgrading your fleet's instance configuration can reduce render errors and significantly improve render times. However, it's important to continue monitoring worker performance after upgrading to ensure you've found the optimal balance - upgrading too aggressively can lead to unnecessary costs through over-provisioning.
### Detecting over-provisioned instances
Even when tasks are completing successfully, there may be opportunities to optimize your costs. The worker dashboard can reveal if you're paying for more compute power than your workloads require. If you see that the worker has low average vCPU usage, minimal memory utilization, and excess unused disk space, you can downsize the instance configuration of your fleet.
### Troubleshooting failed tasks
When investigating failed tasks, the worker dashboard serves as a valuable diagnostic tool. Pay particular attention to peak memory usage and disk space utilization - if these metrics approach or reach 100%, they're likely the root cause of your task failures. Such resource exhaustion indicates that your current instances lack the capacity to handle your workloads effectively. In these cases, provisioning instances with increased memory or disk space will help ensure successful task completion.
### Optimal instance utilization rate
**vCPU Utilization**
**Target range: 70–90%**
+ **Below 70%**: Likely underutilizing compute resources, meaning you're paying for more CPU than your workload needs
+ **70–90%**: Optimal range where you're efficiently using resources without hitting bottlenecks
+ **Consistently at 100%**: Could indicate CPU bottlenecks that might slow down renders
Keep in mind that some render tasks will naturally be more CPU-intensive than others, and 100% vCPU usage may not be an issue. Real-time visualization tasks might show more consistent CPU utilization, while tasks with changing computational requirements might have varying patterns.
**Memory Utilization**
**Target range: 70–85%**
+ **Below 50%**: Potentially oversized instances for your workload
+ **70–85%**: Optimal utilization with enough headroom for spikes
+ **Above 90%**: Risk of performance degradation or out-of-memory errors
Memory requirements can vary significantly depending on scene complexity, texture resolution, and simulation data. Monitoring memory trends over time is important to identify if your workloads are growing in memory requirements.
**Disk Space Utilization**
**Target range: 60–80%**
+ **Below 40%**: Likely over-provisioned storage
+ **60–85%**: Good utilization with room for temporary files and caches
+ **Above 85%**: Risk of running out of space during large renders
Remember that disk I/O performance can be just as important as capacity, especially for workloads that read/write large texture or cache files during rendering.
# Download finished output in Deadline Cloud
After a job is finished, you can use the AWS Deadline Cloud monitor to download the results to your workstation. The output file is stored with the name and location that you specified when you created the job.
Output files are stored indefinitely. To reduce storage costs, consider creating an S3 Lifecycle configuration for your queue's Amazon S3 bucket. For more information, see [ Managing your storage lifecycle](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html) in the *Amazon Simple Storage Service User Guide*.
**To download the finished output of a job, step, or task**
1. Follow the steps in [View and manage job details in Deadline Cloud](view-a-job.md) to view a list of jobs.
1. Select the job, step, or task that you want to download the output for.
+ If you select a job, you can download all of the output for all of the tasks in all of the steps for that job.
+ If you select a step, you can download all of the output for all of the tasks in that step.
+ If you select a task, you can download the output for that individual task.
1. From the **Actions** menu, choose **Download output**.
1. The output will be downloaded to the location set when the job was submitted.
**Note**
Downloading output using the menu is currently only supported for Windows and Linux. If you have a Mac and you choose the **Download output** menu item, a window shows the AWS CLI command that you can use to download the rendered output.
# Automate Deadline Cloud monitor desktop deployment and workflows
The AWS Deadline Cloud monitor desktop application includes a command-line interface (CLI) that administrators can use to set up profiles for users and that artists and developers can use to integrate the monitor into automated workflows on their workstations.
## Finding the Deadline Cloud monitor executable
To use the CLI commands, run the Deadline Cloud monitor executable from a terminal. The default installation location depends on your operating system and installation method.
Windows
```
%LOCALAPPDATA%\DeadlineCloudMonitor\DeadlineCloudMonitor.exe
```
macOS
```
/Applications/DeadlineCloudMonitor.app/Contents/MacOS/DeadlineCloudMonitor
```
Linux (deb or RPM package)
```
/usr/bin/deadline-cloud-monitor
```
Linux (AppImage)
Run the AppImage file directly from the location where you downloaded it.
In the following examples, replace `DeadlineCloudMonitor` with the full path to the executable for your operating system.
## Setting up a profile for streamlined user access
Administrators use the `create-profile` command to create Deadline Cloud monitor profiles for users. This command configures a profile so that users can open the monitor, log in, and start working without additional configuration or profile selection.
The `create-profile` command accepts the following flags:
+ `--enable-auto-login` – Configures the monitor to automatically log in with the most recently used profile when the application starts.
+ `--set-as-deadline-default` – Sets the profile as the default for Deadline Cloud tools, including the Deadline Cloud submitter, the Deadline CLI, and the Deadline Cloud GUI applications. This flag does not affect the AWS Command Line Interface (AWS CLI).
When both flags are enabled, users open the monitor and are logged in automatically with no other configuration or profile selection required.
**To create a profile**
Run the following command, replacing the placeholder values with your monitor details.
```
DeadlineCloudMonitor create-profile \
--profile profile-name \
--monitor-id monitor-id \
--monitor-url https://monitorName.region.deadlinecloud.amazonaws.com \
--enable-auto-login \
--set-as-deadline-default
```
The command creates the profile and writes the configuration to the Deadline Cloud configuration files on the user's workstation. The monitor URL must be in the format `https://monitorName.region.deadlinecloud.amazonaws.com`.
**Note**
The `create-profile` command exits after creating the profile. To open the monitor with the new profile, run the `login` command or open the Deadline Cloud monitor desktop application.
## Integrating the Deadline Cloud monitor into your workflows
Use the `login`, `logout`, and `handle-url` commands to integrate the Deadline Cloud monitor into scripts and automated workflows on your workstation.
### Logging in and logging out
Use the `login` and `logout` commands to control authentication as part of a workflow. For example, a script that submits jobs can use the `login` command to ensure the user is authenticated before submission begins.
When you use the `login` command, the monitor opens directly to the specified profile, skipping the profile selection screen. After authentication completes, the monitor minimizes to the system tray so that your workflow can continue. If the monitor is already running for the specified profile, the existing window comes to the foreground instead of starting a new instance.
**To log in to a profile**
Run the following command, replacing *profile-name* with the name of your Deadline Cloud monitor profile.
```
DeadlineCloudMonitor login --profile profile-name
```
**To log out of a profile**
Run the following command to clear the credentials for a profile and signal any running monitor instance for that profile to exit.
```
DeadlineCloudMonitor logout --profile profile-name
```
### Opening the monitor to a specific page
Use the `handle-url` command to open the Deadline Cloud monitor to a specific page. This command is useful when a script performs an action, such as creating a job, and you want to automatically open the monitor to show the result. For example, after a script submits a job, the script can call `handle-url` to open the monitor directly to the job details page.
You can also use the `deadline-cloud-monitor://` URL as a link on company websites, wikis, or task trackers to let users open the monitor directly to a specific page.
The URL uses the `deadline-cloud-monitor://` protocol scheme with a `launch` command. The URL includes the profile name and the monitor page URL to open.
**To open the monitor to a specific page**
Run the following command, replacing *monitor-page-url* with the URL-encoded monitor page URL and *profile-name* with your profile name.
```
DeadlineCloudMonitor handle-url --url "deadline-cloud-monitor://launch?url=monitor-page-url&profile=profile-name"
```