DailyAzureUpdatesGenerator

Azure Updates Automatic Summary

Japanese version

Japanese Version is here

Overview

Automatic summaries of Azure Updates are stored in the updates_en directory. The automatic summary feature is triggered by GitHub Actions repository_dispatch (daily-update), collecting recent Azure Updates information and generating English summaries.

Disclaimer

The automatic summary reports are generated based on information obtained from RSS feeds and do not guarantee accuracy or completeness. Users should use the provided information at their own risk. If you find content of interest, we recommend checking the original information by referring to the links included in the reports.

Azure Updates RSS Feed Processing Application

This application reads Azure Updates RSS feeds, summarizes Azure Update information updated within a specified time period in English using Azure OpenAI (Chat Completions), and outputs reports in Markdown format.

Features

Robust RSS feed retrieval: Tries multiple URLs to ensure reliable feed acquisition
Details mode: Retrieve detailed information from Azure Updates API (--details option)
Backfill mode: Regenerate day-based reports for a date range (--backfill-* options)
Filtering of new updates within specified time periods
English summary generation using Azure OpenAI
Detailed report output in Markdown format
Comprehensive error handling and retry functionality
Detailed logging and monitoring
Test mode: Feed retrieval testing functionality

Required Environment Variables (DefaultAzureCredential Authentication)

Before running the application, set the following environment variables:

AOAI_ENDPOINT: Azure OpenAI endpoint URL
DEPLOYMENT: Azure OpenAI deployment name
API_VER: Azure OpenAI API version (default: 2025-01-01-preview)
CHECK_HOURS: Target check time (in hours, default: 24)
AZURE_TENANT_ID: Azure AD tenant ID (optional)
AZURE_CLIENT_ID: Client ID (optional)
AZURE_CLIENT_SECRET: Client secret (used for service principal authentication)
ENABLE_AZURE_SDK_LOG: Enable Azure SDK logs (optional, enable with true/1/on/yes; suppressed by default)

Authentication is auto-detected by DefaultAzureCredential.

AZURE_TENANT_ID + AZURE_CLIENT_ID + AZURE_CLIENT_SECRET: service principal authentication
AZURE_TENANT_ID + AZURE_CLIENT_ID (+ OIDC context available): OIDC / Workload Identity authentication
AZURE_TENANT_ID + AZURE_CLIENT_ID (+ managed identity-enabled environment): managed identity authentication
Local development: Azure CLI authentication after az login

Installation

Install required packages:

pip install -r requirements.txt

Test RSS feed:

test_feed.bat

python getlatestupdate_en_mid.py --test-feed --verbose

Usage

Test Execution (Recommended: Run First)

# Test RSS feed retrieval
python getlatestupdate_en_mid.py --test-feed --verbose

# Test execution with batch file
test_feed.bat

Basic Usage

python getlatestupdate_en_mid.py

Execution with Options

# Check updates from the past 12 hours
python getlatestupdate_en_mid.py --hours 12

# Details mode (retrieve detailed information from Azure Updates API)
python getlatestupdate_en_mid.py --details

# Specify output directory
python getlatestupdate_en_mid.py --output-dir reports

# Output detailed logs
python getlatestupdate_en_mid.py --verbose

# Run RSS feed test only
python getlatestupdate_en_mid.py --test-feed

# Combine multiple options (details mode + detailed logs + 72 hours)
python getlatestupdate_en_mid.py --details --verbose --hours 72

# Regenerate the past 7 days (skip existing files)
python getlatestupdate_en_mid.py --details --backfill-days 7

# Regenerate with explicit date range
python getlatestupdate_en_mid.py --details --backfill-startdate 2026-02-01 --backfill-enddate 2026-02-07

# Force overwrite existing daily files
python getlatestupdate_en_mid.py --details --backfill-days 3 --force

Using Details Mode

Details mode (--details) retrieves detailed information from the Azure Updates API in addition to RSS feed information:

# Run in details mode
python getlatestupdate_en_mid.py --details

# Batch file example with details mode
run_details_example.bat

Details mode features:

Retrieve detailed information for each article from Azure Updates API
Use more accurate and complete article titles and content
Display information retrieved from API in reports
Detailed information source tracking and log output

Environment Variable Setup Example (Windows)

set AOAI_ENDPOINT=https://your-openai-resource.openai.azure.com
set DEPLOYMENT=gpt-4-mini
set API_VER=2025-01-01-preview
set CHECK_HOURS=24
set AZURE_TENANT_ID=your-tenant-id
set AZURE_CLIENT_ID=your-client-id
set AZURE_CLIENT_SECRET=your-client-secret

Troubleshooting

RSS Feed Retrieval Errors

Check with test mode:

python getlatestupdate_en_mid.py --test-feed --verbose

Check log file: azure_updates.log
Verify network connection: Internet connection and proxy settings
Multiple URL attempts: The application automatically tries multiple RSS URLs

Test details mode:
```
python test_details.py
```
API access errors: If Azure Updates API is temporarily unavailable, processing continues in standard mode
Update ID extraction failure: When ID cannot be extracted for some articles, RSS information is used

Common Errors and Solutions

“No entries in feed”: RSS URL may have been changed
“not well-formed (invalid token)”: XML parse error. Trying alternative URLs
HTTP connection errors: Check network settings and firewall

Output

The application generates:

Markdown report: updates/azure-updates-YYYY-MM-DD.md
Log file: azure_updates.log

Report Contents

Standard Mode

Generation date/time and target period
Summary of update count
Details of each update:
- Title (from RSS feed)
- Publication date/time
- Link
- Category
- AI-generated English summary
- Original detailed description (from RSS feed)

Details Mode (`--details`)

In addition to the above:

Update ID: Individual article identifier
Data source: Clear indication of Azure Updates API usage
Enhanced title: More accurate title retrieved from API
Detailed content: Complete article content retrieved from API
Improved summary: Summary based on more detailed and accurate information

Error Handling

Multiple RSS URLs: Automatic fallback when primary URL fails
Network errors: Automatic retry and timeout settings
XML parse errors: Minor errors are ignored to continue processing
API rate limiting: Appropriate wait time settings
Detailed logs: Comprehensive logging for troubleshooting

Security Considerations

API keys retrieved from environment variables
Use of HTTPS communication
Appropriate timeout settings
Session management and resource cleanup
Proper User-Agent configuration

Limitations

Dependent on Azure OpenAI rate limits
Dependent on RSS feed availability
Date parsing accuracy depends on feed format

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