DFS Namespace API Queue Test
To manage DFS, administrators often rely on management tools and functions that Windows offers - for eg., DFS Management UI, DFS BPA, DFS Namespaces Windows PowerShell cmdlets, File Server Resource Manager, and many more. All these management tools use NetDfs API functions to perform a wide variety of management tasks such as:
- Adding a DFS link to a DFS root;
- Creating or removing stand-alone and domain-based DFS namespaces;
- Adding targets to an existing DFS link;
- Removing a DFS link from a DFS root;
- Removing a target from a DFS link;
- Viewing and configuring information about DFS roots and links
In the process, these tools can generate a significant amount of management traffic on the namespace server. The true test of strength of the namespace server lies in how well it processes this traffic. To determine whether/not the namespace server is able to handle this traffic, administrators can use the DFS Namespace API Queues test. This test continuously tracks the length of the API queues on the server to figure out how quickly the server processes the API requests in the queue. This sheds light on the load imposed by API requests on the server and the ability of the server to respond to these requests.
Target of the test : A server that hosts the DFS namespace (this can even be a server that contains the DFS root or a replica of it)
Agent deploying the test : An internal agent
Outputs of the test : One set of results for the DFS namespace server being monitored.
This indicates how often should the test be executed.
The host for which the test is to be configured.
The port at which the specified host listens to.
API queue length
Indicates the number of requests (made using the NetDfs API) currently in the queue for the DFS Namespace service to process.
If the value of this measure keeps increasing while at the peak level of activity, it could indicate a bottleneck in processing API requests. One of the common reasons why a namespace server may be unable to process API requests quickly is improper server sizing.
A server that is sized right should be able to crank through its work queues and be responsive. A server with insufficient resources on the other hand will not be able to handle this load, and may hence end-up processing requests slowly; this in turn will increase the length of the API request processing queues.
In such cases, add more processing power to the server and see if it helps reduce queue length.