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

What’s new and coming next to Microsoft 365 Copilot and Teams

Hat on, roadmap rolling. ✨ I follow the Microsoft Admin Center (MAC) Message Center all the time — or to be precise, my AI teammate follows it...

5 hours ago

How SharePoint Integration Improves Dynamics 365 Document Management

Managing business documents inside Dynamics 365 can become increasingly difficult as CRM data grows. Sales teams upload proposals, support tea...

6 hours ago

Microsoft Purview | Data Lifecycle Management – Archive OneDrive and SharePoint files under retention

Microsoft Purview Data Lifecycle Management will enable archiving OneDrive and SharePoint files under retention policies to reduce storage cos...

8 hours ago

Microsoft 365 Copilot app: Simplified, chat-centered experience

Microsoft 365 Copilot app updates introduce a streamlined, chat-centered experience with simplified navigation, a new Tasks tab, and consolida...

8 hours ago

Microsoft 365 Copilot: Support for real-time screen sharing in Copilot voice sessions

Microsoft 365 Copilot will support real-time screen and camera sharing in voice sessions, enabling Copilot to analyze visual content and provi...

8 hours ago

Microsoft Teams: Guest invitation emails will be sent from the inviter’s email address

Microsoft Teams guest invitation emails will soon be sent from the inviter’s email address instead of a no-reply address, improving clarity an...

8 hours ago

Microsoft Cans Power BI App for Microsoft 365 Usage

Microsoft has announced that the Microsoft 365 Usage Analytics Power BI app will retire on August 1, 2026. The alternative is the usage report...

10 hours ago

D365 CE 2026 Release Wave 1: For Sales & Service Teams

Microsoft continues to evolve Dynamics 365 Customer Engagement with updates that affect how organizations manage sales pipelines, customer ser...

20 hours ago

SharePoint Framework (SPFx) roadmap update – May 2026

SPFx is powering the future of Microsoft 365 with AI driven portals and deep integrations across SharePoint and Microsoft 365. The May 2026 up...

1 day ago

File-level backup and restore in Microsoft 365

Microsoft 365 Copilot become more and more crucial component. AFI.AI offers the backup of this technology as a first vendor on the market. The...

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