Guidance for throttled requests in Azure Resource Graph
When creating programmatic and frequent use of Azure Resource Graph data, consideration should be made for how throttling affects the results of the queries. Changing the way data is requested can help you and your organization avoid being throttled and maintain the flow of timely data about your Azure resources.
This article covers four areas and patterns related to the creation of queries in Azure Resource Graph:
- Understand throttling headers.
- Grouping queries.
- Staggering queries.
- The effect of pagination.
Understand throttling headers
Azure Resource Graph allocates a quota number for each user based on a time window. For example, a user can send at most 15 queries within every 5-second window without being throttled. The quota value is determined by many factors and is subject to change.
In every query response, Azure Resource Graph adds two throttling headers:
x-ms-user-quota-remaining
(int): The remaining resource quota for the user. This value maps to query count.x-ms-user-quota-resets-after
(hh:mm:ss): The time duration until a user's quota consumption is reset.
When a security principal has access to more than 10,000 subscriptions within the tenant or
management group query scope, the response is limited to the
first 10,000 subscriptions and the x-ms-tenant-subscription-limit-hit
header is returned as true
.
To illustrate how the headers work, let's look at a query response that has the header and values of
x-ms-user-quota-remaining: 10
and x-ms-user-quota-resets-after: 00:00:03
.
- Within the next 3 seconds, at most 10 queries can be submitted without being throttled.
- In 3 seconds, the values of
x-ms-user-quota-remaining
andx-ms-user-quota-resets-after
are reset to15
and00:00:05
respectively.
To see an example of using the headers to backoff on query requests, see the sample in Query in parallel.
Grouping queries
Grouping queries by the subscription, resource group, or individual resource is more efficient than parallelizing queries. The quota cost of a larger query is often less than the quota cost of many small and targeted queries. The group size is recommended to be less than 300.
Example of a poorly optimized approach.
// NOT RECOMMENDED var header = /* your request header */ var subscriptionIds = /* A big list of subscriptionIds */ foreach (var subscriptionId in subscriptionIds) { var userQueryRequest = new QueryRequest( subscriptions: new[] { subscriptionId }, query: "Resources | project name, type"); var azureOperationResponse = await this.resourceGraphClient .ResourcesWithHttpMessagesAsync(userQueryRequest, header) .ConfigureAwait(false); // ... }
Example of an optimized grouping approach.
// RECOMMENDED var header = /* your request header */ var subscriptionIds = /* A big list of subscriptionIds */ const int groupSize = 100; for (var i = 0; i <= subscriptionIds.Count / groupSize; ++i) { var currSubscriptionGroup = subscriptionIds.Skip(i * groupSize).Take(groupSize).ToList(); var userQueryRequest = new QueryRequest( subscriptions: currSubscriptionGroup, query: "Resources | project name, type"); var azureOperationResponse = await this.resourceGraphClient .ResourcesWithHttpMessagesAsync(userQueryRequest, header) .ConfigureAwait(false); // ... }
Example of an optimized grouping approach for getting multiple resources in one query.
Resources | where id in~ ({resourceIdGroup}) | project name, type
// RECOMMENDED var header = /* your request header */ var resourceIds = /* A big list of resourceIds */ const int groupSize = 100; for (var i = 0; i <= resourceIds.Count / groupSize; ++i) { var resourceIdGroup = string.Join(",", resourceIds.Skip(i * groupSize).Take(groupSize).Select(id => string.Format("'{0}'", id))); var userQueryRequest = new QueryRequest( subscriptions: subscriptionList, query: $"Resources | where id in~ ({resourceIdGroup}) | project name, type"); var azureOperationResponse = await this.resourceGraphClient .ResourcesWithHttpMessagesAsync(userQueryRequest, header) .ConfigureAwait(false); // ... }
Staggering queries
Because of the way throttling is enforced, we recommend queries to be staggered. For example, instead of sending 60 queries at the same time, stagger the queries into four 5-second windows.
Nonstaggered query schedule.
Query Count 60 0 0 0 Time Interval (sec) 0-5 5-10 10-15 15-20 Staggered query schedule.
Query Count 15 15 15 15 Time Interval (sec) 0-5 5-10 10-15 15-20
The following code is an example of respecting throttling headers when querying Azure Resource Graph.
while (/* Need to query more? */)
{
var userQueryRequest = /* ... */
// Send post request to Azure Resource Graph
var azureOperationResponse = await this.resourceGraphClient
.ResourcesWithHttpMessagesAsync(userQueryRequest, header)
.ConfigureAwait(false);
var responseHeaders = azureOperationResponse.response.Headers;
int remainingQuota = /* read and parse x-ms-user-quota-remaining from responseHeaders */
TimeSpan resetAfter = /* read and parse x-ms-user-quota-resets-after from responseHeaders */
if (remainingQuota == 0)
{
// Need to wait until new quota is allocated
await Task.Delay(resetAfter).ConfigureAwait(false);
}
}
Query in parallel
Even though grouping is recommended over parallelization, there are times where queries can't be easily grouped. In these cases, you might want to query Azure Resource Graph by sending multiple queries in a parallel fashion. The following example shows how to backoff based on throttling headers.
IEnumerable<IEnumerable<string>> queryGroup = /* Groups of queries */
// Run groups in parallel.
await Task.WhenAll(queryGroup.Select(ExecuteQueries)).ConfigureAwait(false);
async Task ExecuteQueries(IEnumerable<string> queries)
{
foreach (var query in queries)
{
var userQueryRequest = new QueryRequest(
subscriptions: subscriptionList,
query: query);
// Send post request to Azure Resource Graph.
var azureOperationResponse = await this.resourceGraphClient
.ResourcesWithHttpMessagesAsync(userQueryRequest, header)
.ConfigureAwait(false);
var responseHeaders = azureOperationResponse.response.Headers;
int remainingQuota = /* read and parse x-ms-user-quota-remaining from responseHeaders */
TimeSpan resetAfter = /* read and parse x-ms-user-quota-resets-after from responseHeaders */
if (remainingQuota == 0)
{
// Delay by a random period to avoid bursting when the quota is reset.
var delay = (new Random()).Next(1, 5) * resetAfter;
await Task.Delay(delay).ConfigureAwait(false);
}
}
}
Pagination
Because Azure Resource Graph returns a maximum of 1,000 entries in a single query response, you might need to paginate your queries to get the complete dataset you want. But some Azure Resource Graph clients handle pagination differently than others.
When using ResourceGraph SDK, you need to handle pagination by passing the skip token being returned from the previous query response to the next paginated query. This design means you need to collect results from all paginated calls and combine them together at the end. In this case, each paginated query you send takes one query quota.
var results = new List<object>();
var queryRequest = new QueryRequest(
subscriptions: new[] { mySubscriptionId },
query: "Resources | project id, name, type");
var azureOperationResponse = await this.resourceGraphClient
.ResourcesWithHttpMessagesAsync(queryRequest, header)
.ConfigureAwait(false);
while (!string.IsNullOrEmpty(azureOperationResponse.Body.SkipToken))
{
queryRequest.Options ??= new QueryRequestOptions();
queryRequest.Options.SkipToken = azureOperationResponse.Body.SkipToken;
var azureOperationResponse = await this.resourceGraphClient
.ResourcesWithHttpMessagesAsync(queryRequest, header)
.ConfigureAwait(false);
results.Add(azureOperationResponse.Body.Data.Rows);
// Inspect throttling headers in query response and delay the next call if needed.
}
Still being throttled?
If you used this article's recommendations and your Azure Resource Graph queries are still being throttled, contact the Azure Resource Graph team. The team supports Azure Resource Graph but doesn't support Microsoft Graph throttling.
Provide these details when you contact the Azure Resource Graph team:
- Your specific use-case and business driver needs for a higher throttling limit.
- How many resources do you have access to? How many of them are returned from a single query?
- What types of resources are you interested in?
- What's your query pattern? X queries per Y seconds, and so on.
Next steps
- See the language in use in Starter queries.
- See advanced uses in Advanced queries.
- Learn more about how to explore resources.