AWS WorkSpaces Details Test
Amazon WorkSpaces enables you to provision virtual, cloud-based Microsoft Windows, Amazon Linux, or Ubuntu Linux desktops for your users, known as WorkSpaces. WorkSpaces eliminates the need to procure and deploy hardware or install complex software. You can quickly add or remove users as your needs change. Users can access their virtual desktops from multiple devices or web browsers.
The true test of the efficiency of WorkSpaces lies in their ability to deliver to users the same desktop experience as that of physical desktops, regardless of which geography the user is connecting from and which AWS region hosts the WorkSpaces. On-demand access, continuous availability, consistent good health, and near-zero latency are the qualities that users have come to expect from WorkSpaces. Consequently, users will not tolerate even a single failed WorkSpace connection attempt or the slightest delay in WorkSpace access! This in turn will result in a flood of user complaints to help desk. At such times, help desk personnel struggle to figure out which Workspace the user is complaining about and where that WorkSpace operates - i.e., in which AWS region, so they can troubleshoot the issue quickly and effectively. This is where the AWS WorkSpaces Details test helps!
This test monitors the performance of WorkSpaces per AWS region, and rapidly leads administrators to that region where most unavailable, unhealthy, latent, and unreliable WorkSpaces exist. Detailed diagnostics of the test also reveal the exact WorkSpaces in a region that are problematic. This enables administrators to speedily troubleshoot the issues and improve the overall quality of the WorkSpace experience of users.
Target of the test: Amazon Cloud
Agent deploying the test: A remote agent
Output of the test: One set of results for each AWS region hosting WorkSpaces
Parameter | Description |
---|---|
Test Period |
How often should the test be executed. |
Host |
The host for which the test is to be configured. |
Access Type |
eG Enterprise monitors the AWS cloud using AWS API. By default, the eG agent accesses the AWS API using a valid AWS account ID, which is assigned a special role that is specifically created for monitoring purposes. Accordingly, the Access Type parameter is set to Role by default. Furthermore, to enable the eG agent to use this default access approach, you will have to configure the eG tests with a valid AWS Account ID to Monitor and the special AWS Role Name you created for monitoring purposes. Some AWS cloud environments however, may not support the role-based approach. Instead, they may allow cloud API requests only if such requests are signed by a valid Access Key and Secret Key. When monitoring such a cloud environment therefore, you should change the Access Type to Secret. Then, you should configure the eG tests with a valid AWS Access Key and AWS Secret Key. Note that the Secret option may not be ideal when monitoring high-security cloud environments. This is because, such environments may issue a security mandate, which would require administrators to change the Access Key and Secret Key, often. Because of the dynamicity of the key-based approach, Amazon recommends the Role-based approach for accessing the AWS API. |
AWS Account ID to Monitor |
This parameter appears only when the Access Type parameter is set to Role. Specify the AWS Account ID that the eG agent should use for connecting and making requests to the AWS API. To determine your AWS Account ID, follow the steps below:
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AWS Role Name |
This parameter appears when the Access Type parameter is set to Role. Specify the name of the role that you have specifically created on the AWS cloud for monitoring purposes. The eG agent uses this role and the configured Account ID to connect to the AWS Cloud and pull the required metrics. To know how to create such a role, refer to Creating a New Role. |
AWS Access Key, AWS Secret Key, Confirm AWS Access Key, Confirm AWS Secret Key |
These parameters appear only when the Access Type parameter is set to Secret.To monitor an Amazon instance, the eG agent has to be configured with the access key and secret key of a user with a valid AWS account. For this purpose, we recommend that you create a special user on the AWS cloud, obtain the access and secret keys of this user, and configure this test with these keys. The procedure for this has been detailed in the Obtaining an Access key and Secret key topic. Make sure you reconfirm the access and secret keys you provide here by retyping it in the corresponding Confirm text boxes. |
Proxy Host and Proxy Port |
In some environments, all communication with the AWS cloud and its regions could be routed through a proxy server. In such environments, you should make sure that the eG agent connects to the cloud via the proxy server and collects metrics. To enable metrics collection via a proxy, specify the IP address of the proxy server and the port at which the server listens against the Proxy Host and Proxy Port parameters. By default, these parameters are set to none , indicating that the eG agent is not configured to communicate via a proxy, by default. |
Proxy User Name, Proxy Password, and Confirm Password |
If the proxy server requires authentication, then, specify a valid proxy user name and password in the proxy user name and proxy password parameters, respectively. Then, confirm the password by retyping it in the CONFIRM PASSWORD text box. By default, these parameters are set to none, indicating that the proxy sever does not require authentication by default. |
Proxy Domain and Proxy Workstation |
If a Windows NTLM proxy is to be configured for use, then additionally, you will have to configure the Windows domain name and the Windows workstation name required for the same against the proxy domain and proxy workstation parameters. If the environment does not support a Windows NTLM proxy, set these parameters to none. |
Exclude Region |
Here, you can provide a comma-separated list of region names or patterns of region names that you do not want to monitor. For instance, to exclude regions with names that contain 'east' and 'west' from |
Log Groups |
A log stream is a sequence of log events that share the same source. Each separate source of logs in CloudWatch Logs makes up a separate log stream. A log group is a group of log streams that share the same retention, monitoring, and access control settings. In some environments, a log group may have been created to include log streams that capture the details of WorkSpace sessions. If you want this test to report detailed diagnostics using such a log group, then specify the name of that log group against this parameter. By default however, this test does not use log groups for reporting detailed metrics. Instead, it uses the AWS API. Accordingly, this parameter is set to none by default. |
DD For Healthy Workspace |
In large AWS cloud environments, the count of healthy WorkSpaces may be abnormally high; collecting and storing detailed metrics for all these WorkSpaces may hence significantly increase the strain on the eG database. To conserve database space and reduce stress on the eG database, this test does not collect detailed diagnostics for the Healthy workspaces measure, by default. Accordingly, this flag is set to No by default. If you want to view detailed diagnostics for healthy WorkSpaces as well, set this flag to Yes. It is recommended that you turn on this flag only after ensuring that your eG database is well-sized and well-tuned. |
DD For Users Disconnected |
In large AWS cloud environments, thre may be numerous WorkSpaces to which no users are connected; collecting and storing detailed metrics for all these WorkSpaces may hence significantly increase the strain on the eG database. To conserve database space and reduce stress on the eG database, this test does not collect detailed diagnostics for the User disconnected workspaces measure, by default. Accordingly, this flag is set to No by default. If you want to view detailed diagnostics for the User disconnected workspaces measure, set this flag to Yes. It is recommended that you turn on this flag only after ensuring that your eG database is well-sized and well-tuned. |
DD For Users Connected |
In large AWS cloud environments, thre may be numerous WorkSpaces to which users may be connected; collecting and storing detailed metrics for all these WorkSpaces may hence significantly increase the strain on the eG database. To conserve database space and reduce stress on the eG database, this test does not collect detailed diagnostics for the User connected workspaces measure, by default. Accordingly, this flag is set to No by default. If you want to view detailed diagnostics for the User connected workspaces measure, set this flag to Yes. It is recommended that you turn on this flag only after ensuring that your eG database is well-sized and well-tuned. |
Session Latency |
By default, if the round-trip-time (RTT) between a WorkSpaces client and a WorkSpace is 500 seconds or more, then this test will count this WorkSpace session as a Session with high latency. If required, you can override the default value of this parameter. For instance, if you change the value of this parameter to 1000 seconds, then this test will consider only those sessions with an RTT that is equal to or more than 1000 seconds as latent sessions. The count of such sessions alone will be included in the value of the Session with high latency measure. |
Session Launch Time |
By default, if it takes more than 30 seconds for a WorkSpace session to be initiated, then this test will count such a session as a Session with high launch time. If required, you can override the default value of this parameter. For instance, if you change the value of this parameter to 100 seconds, then this test will consider only those sessions with a launch time that is equal to or more than 100 seconds as sessions that are slow to launch. The count of such sessions alone will be included in the value of the Session with high launch time measure. |
DD Frequency |
Refers to the frequency with which detailed diagnosis measures are to be generated for this test. The default is 1:1. This indicates that, by default, detailed measures will be generated every time this test runs, and also every time the test detects a problem. You can modify this frequency, if you so desire. Also, if you intend to disable the detailed diagnosis capability for this test, you can do so by specifying none against DD frequency. |
Detailed Diagnosis |
To make diagnosis more efficient and accurate, the eG Enterprise embeds an optional detailed diagnostic capability. With this capability, the eG agents can be configured to run detailed, more elaborate tests as and when specific problems are detected. To enable the detailed diagnosis capability of this test for a particular server, choose the On option. To disable the capability, click on the Off option. The option to selectively enable/disable the detailed diagnosis capability will be available only if the following conditions are fulfilled:
|
Measurement |
Description |
Measurement Unit |
Interpretation |
---|---|---|---|
Available workspaces |
Indicates the total number of WorkSpaces available in this region. |
Number |
Use the detailed diagnosis of this measure to know which are the available WorkSpaces. |
Recently user connected workspaces |
Indicates the number of WorkSpaces in this region to which users were connected during the last measurement period. |
Number |
Use the detailed diagnosis of this measure to know which users are connected to which workspaces. |
Healthy workspaces |
Indicates the number of WorkSpaces in this region that are healthy. |
Number |
Amazon WorkSpaces periodically sends status requests to a WorkSpace. The WorkSpace is marked as Unhealthy if a response isn’t received from the WorkSpace in a timely manner. If a response is received in good time, then the WorkSpace is marked as Healthy. Compare the value of this measure across regions to know which region has least number of healthy workspaces. However, note that these detailed metrics will be available only if the DD For Healthy Spaces flag is set to Yes. |
Unhealthy workspaces |
Indicates the number of WorkSpaces in this region that are unhealthy. |
Number |
Amazon WorkSpaces periodically sends status requests to a WorkSpace. The WorkSpace is marked as Unhealthy if a response isn’t received from the WorkSpace in a timely manner. A high value for this measure for any region is a cause for concern, as it means that numerous WorkSpaces in that region are currently unhealthy. In such a situation, you can use the detailed diagnosis of this measure to know which WorkSpaces in that region are unhealthy, quickly figure out why those WorkSpaces are unresponsive, and rapidly resolve that bottleneck so that all WorkSpaces become healthy. Common causes for the Unhealthy status of a WorkSpace are as follows:
The following troubleshooting steps can return the WorkSpace to a healthy state:
|
Workspaces connection attempts |
Indicates the total number of connection attempts made to WorkSpaces in this region. |
Number |
|
Workspaces connection successes |
Indicates the number of connection attempts to WorkSpaces in this region that resulted in a successful connection. |
Number |
|
Workspaces connection failures |
Indicates the number of connection attempts to WorkSpaces in this region that failed. |
Number |
Ideally, the value of this measure should be 0 for any region. If this value is unusually high for any region, then you can use the detailed diagnosis of this measure to identify the WorkSpaces to which connections failed and why the failure occurred. This will greatly help troubleshooting the failure. |
Session disconnects |
Indicates the number of WorkSpaces to which user-initiated sessions are disconnected. |
Number |
Ideally, the value of this measure should be low. If this value is abnormally high for any region, it is a matter of distress for an administrator, as it implies that many users/clients are disconnected from the WorkSpaces in that region. In such a situation, administrators should rapidly investigate the disconnects, identify why they occurred, and resolve it quickly. Some of the reasons for frequent disconnects are as follows:
To resolve issues with your WorkSpace frequently disconnecting and reconnecting, follow these broad steps:
|
Users connected workspaces |
Indicates the number of WorkSpaces in this region to which users are currently connected. |
Number |
Use the detailed diagnosis of this measure to know which users are connected to which WorkSpaces. However, note that these detailed metrics will be available only if the DD For Users Connected flag of this test is set to Yes. |
Stopped workspaces |
Indicates the number of WorkSpaces in this region that have stopped running. |
Number |
|
WorkSpaces in maintenance |
Indicates the number of Workspaces in this region that is under maintenance. |
Number |
This metric applies to WorkSpaces that are configured with an AutoStop running mode. With this mode, your WorkSpaces stop after a specified period of inactivity and the state of apps and data is saved. Amazon WorkSpaces schedules maintenance for your WorkSpaces. During the maintenance window, important updates are downloaded and installed. If you enable maintenance mode for your AutoStop WorkSpaces, they are started automatically once a month in order to download and install important service, security, and Windows updates. |
User disconnected workspaces |
Indicates the number of WorkSpaces in this region to which users are not connected. |
Number |
Use the detailed diagnosis of this measure to know which which WorkSpaces do not have any users connected. However, note that these detailed metrics will be available only if the DD For Users Disconnected flag of this test is set to Yes. |
Sessions with high latency |
Indicates the number of WorkSpaces in this region that are experiencing latency equal to or more than the value configured against the Session Latency parameter of this test. |
Number |
Latency is the round trip time (RTT) between the WorkSpaces client and this WorkSpace. If this RTT is very high for a WorkSpace, user experience with that WorkSpace will deteriorate. This is why, the value 0 is desired for this measure. If this measure reports a high value, it implies that many WorkSpaces in a region are highly latent. In such a situation, you can use the detailed diagnosis of this measure to know which WorkSpaces are latent, and which users are impacted by that slowness. A slow round-trip time can be caused by many factors, but the following are the most common causes:
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Sessions with high launch time |
Indicates the number of WorkSpaces in this region for which the session launch time is equal to or more than the value configured against the Session Launch Time parameter of this test. |
Number |
Session launch time is the time it takes for a session to be initiated on a WorkSpace. If this value is consistently high, then the user experience with the corresponding WorkSpace is bound to suffer. This is why, the value of this measure should be 0, ideally. If this measure reports an abnormally high value, it means that numerous WorkSpaces in a region are slow in launching sessions. In such a situation, you can use the detailed diagnosis of this measure to know which users are experiencing launching slowness with which WorkSpaces in the region. Some common reasons for a slow session launch are as follows:
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