Loading...

Honor Retry-After and RateLimit Headers in SharePoint Online Throttling

Honor Retry-After and RateLimit Headers in SharePoint Online Throttling

Throttling in SharePoint Online is a mechanism implemented to prevent overuse of resources and maintain optimal performance and reliability. When throttling occurs, SharePoint Online returns HTTP status codes, such as 429 (“Too many requests”) or 503 (“Server Too Busy”). This article focuses on the best practices for handling throttling by honoring the Retry-After and RateLimit headers provided in the response.

Understanding Throttling in SharePoint Online

Throttling in SharePoint Online can occur at both the user and application levels. User throttling restricts the number of calls and operations made by applications on behalf of a user, while application throttling imposes limits on applications within a tenant based on the number of licenses purchased per organization.

Handling 429 and 503 Errors with Retry

To handle throttling effectively, it is crucial to honor the Retry-After and RateLimit headers provided in the response. The following Python code snippet demonstrates how to handle 429 and 503 errors with a maximum retry of three times:

Sample Python Code

import requests
import time

class GraphAPIHandler:
    def __init__(self, tenant_id, client_id, client_secret, user_agent):
        self.tenant_id = tenant_id
        self.client_id = client_id
        self.client_secret = client_secret
        self.user_agent = user_agent
        self.access_token = None

    def get_access_token(self):
        token_url = f'https://login.microsoftonline.com/{self.tenant_id}/oauth2/v2.0/token'
        payload = {
            'client_id': self.client_id,
            'client_secret': self.client_secret,
            'scope': 'https://graph.microsoft.com/.default',
            'grant_type': 'client_credentials'
        }
        headers = {
            'User-Agent': self.user_agent
        }
        response = requests.post(token_url, data=payload, headers=headers)
        response_data = response.json()
        if 'access_token' in response_data:
            self.access_token = response_data['access_token']
        else:
            raise Exception('Failed to obtain access token')

    def make_graph_api_request(self, url):
        headers = {
            'Authorization': f'Bearer {self.access_token}',
            'User-Agent': self.user_agent
        }
        max_retries = 3
        retry_wait_time = 1  # Wait time in seconds between retries

        for retry in range(max_retries):
            response = requests.get(url, headers=headers)

            if response.status_code == 200:
                return response.json()
            elif response.status_code == 429 or response.status_code == 503:
                if 'Retry-After' in response.headers:
                    # Retry-After header provides the recommended wait time
                    wait_time = int(response.headers.get('Retry-After', 0))
                    if wait_time > 0:
                        print(f'Received {response.status_code} status code. Waiting for {wait_time} seconds before retrying...')
                        time.sleep(wait_time)
                    else:
                        print(f'Received {response.status_code} status code, but Retry-After header was not provided. Waiting for {retry_wait_time} seconds before retrying...')
                        time.sleep(retry_wait_time)
                else:
                    # If Retry-After header is not available, use a default wait time
                    print(f'Received {response.status_code} status code, but Retry-After header was not provided. Waiting for {retry_wait_time} seconds before retrying...')
                    time.sleep(retry_wait_time)
            else:
                # Other error occurred, handle it accordingly
                raise Exception(f"Request failed with status code: {response.status_code}")

        # Reached maximum retries without a successful response
        raise Exception("Maximum retry attempts reached. Unable to complete the request.")

# Usage example
tenant_id = '<your_tenant_id>'
client_id = '<your_client_id>'
client_secret = '<your_client_secret>'
user_agent = 'NONISV|CompanyName|AppName/Versio' # If ISV Application type, use ISV|CompanyName|AppName/Version 

graph_handler = GraphAPIHandler(tenant_id, client_id, client_secret, user_agent)

try:
    graph_handler.get_access_token()

    graph_api_url = 'https://graph.microsoft.com/v1.0/me'
    user_data = graph_handler.make_graph_api_request(graph_api_url)
    print('User data:', user_data)

except Exception as e:
    print('An error occurred:', str(e))

By incorporating the above code into your SharePoint Online application, you can handle 429 and 503 errors effectively. The code retries the request with appropriate wait times based on the Retry-After header provided in the response. It allows a maximum of three retries before raising an exception if a successful response is not received. Adjust the retry_wait_time and max_retries variables as per your application’s requirements.

Conclusion

By following the best practices mentioned in this article and honoring the Retry-After and RateLimit headers in SharePoint Online, you can handle throttling more effectively. Remember to reduce concurrent requests, avoid request spikes, utilize Microsoft Graph APIs, and implement proper retry mechanisms for 429 and 503 errors. With these practices in place, you can optimize your application’s performance and ensure a reliable and responsive experience for SharePoint Online users.

Although the best practice for avoiding SharePoint Online throttling is to optimize your code to minimize the impact of service-related limits, SharePoint Online provides a number of tools to manage and troubleshoot throttling in your tenant. For example, you can use the SharePoint Online Component-based Scalable Logical Architecture(CSLA) tool, monitor the health of your environment, and identify potential throttling issues. The tool, accessed through an elevated command prompt, enables you to configure throttling policies, restrict access to specific endpoints and resources, and monitor the health of your SharePoint Online deployments. Additionally, the SharePoint Online Knowledge Base contains information regarding the most common throttling scenarios and possible solutions.

Even with all the available tools, it can be difficult to detect and address throttling issues in your SharePoint Online environment. To manage and troubleshoot potential throttling issues, perform continuous monitoring of your environment. Monitor the health of your SharePoint Online deployments and identify potential misuse. Also, keep in mind that throttling can occur for any number of reasons—from network bottlenecks to limited server resources and performance degradation.

Published on:

Learn more
Home | Joseph Velliah
Home | Joseph Velliah

Fulfilling God’s purpose for my life

Share post:

Related posts

Power Automate: Teams - When I'm @mentioned

The Power Automate "When I'm @mentioned" Teams trigger fires for chat and channel mentions in near real time. Webhook based, fires on replies,...

16 hours ago

Microsoft Teams: Join Google Meet meetings in Teams Rooms on Windows

Organizations now have expanded meeting interoperability with two-way Direct Guest Join (DGJ) between Google Meet and Teams meetings. Teams Ro...

22 hours ago

Microsoft Teams: Preloaded video for Teams Events and Meetings

Users can now upload videos directly into a Teams event or meeting from OneDrive from the “Manage view” options when an organizer ...

22 hours ago

Microsoft Viva: Agent metrics for custom reporting in Insights analyst workbench

Unlock deeper insights into Copilot agent adoption with flexible, self-serve analytics. Insights global and partition analysts can access and ...

22 hours ago

Planner Synchronization of Microsoft 365 Message Center Notifications Improves

Microsoft published the very good news that the Planner synchronization with the Microsoft 365 message center will support HTML formatted text...

23 hours ago

Authoritative Sites for SharePoint in Microsoft Copilot

Authoritative Sites lets admins mark specific SharePoint sites as trusted, prioritizing their content in Microsoft Copilot Chat and Search to ...

1 day ago

SharePoint Online: Storage quota enforcement updated to align with license limits

SharePoint Online will update storage quota enforcement by late May to June 2026, aligning user quotas with license limits. Users exceeding li...

1 day ago

Microsoft Teams: Standardized preview experience for PowerPoint, Excel, and Word files

Microsoft Teams will standardize the preview experience for Word, Excel, and PowerPoint files across desktop and mobile, improving speed and r...

1 day ago

Microsoft 365 Backup management through SharePoint Admin Center

Microsoft 365 Backup management for SharePoint and OneDrive will be integrated into the SharePoint Admin Center by mid-May 2026. This centrali...

1 day ago

Microsoft Dataverse – Chat and reason over Dataverse business data in Microsoft 365 Copilot (preview)

We are announcing the ability to chat and reason over Dataverse business data with Microsoft 365 Copilot in Microsoft Dataverse. This feature ...

1 day ago
Stay up to date with latest Microsoft Dynamics 365 and Power Platform news!
* Yes, I agree to the privacy policy