Integration Architecture and Data Flow
Plivo-Odoo Communication Model
The Plivo-Odoo integration operates on a bidirectional webhook architecture that maintains real-time synchronization between communication events and business data. Odoo acts as the central command center, initiating outbound communications through Plivo’s REST API and receiving inbound interactions via webhook endpoints exposed by your Odoo instance. This model creates a continuous feedback loop where communication data enriches Odoo records, and Odoo customer data personalizes Plivo interactions.
Plivo handles the telephony infrastructure and SMS delivery, while Odoo manages business logic and data persistence. When a customer calls your Plivo number, Plivo immediately sends an HTTP POST request to your configured Odoo webhook URL. This request contains the caller’s number, call unique identifier, and timestamp data. Your Odoo system processes this webhook, identifies the customer based on phone number matching, and creates a call log record linked to the appropriate contact or lead.
Data Flow Patterns for Different Communication Types
Outbound calls from Odoo follow a different data flow pattern. When a user clicks a phone number in Odoo, your custom module captures this event and makes an API call to Plivo’s /v1/Account/MAUTH_ID/Call/ endpoint. Plivo then initiates the call to both parties and bridges the connection. Throughout the call lifecycle, Plivo sends multiple webhooks to Odoo - call initiated, answered, completed - each updating the call record with current status and duration.
SMS messaging operates with similar webhook patterns but different data structures. Outbound SMS messages originate from Odoo through Plivo’s Message API, while inbound messages trigger webhooks that Odoo processes to create or update message threads in the chatter. The system attaches these threads to specific records like sales orders, support tickets, or partner forms, maintaining full context for all customer communications.
Webhook Endpoint Design
Your Odoo webhook endpoints require careful design to handle Plivo’s expected payload formats and respond with appropriate HTTP status codes. The /plivo/inbound/call endpoint processes incoming call notifications, while /plivo/inbound/message handles SMS delivery reports and inbound messages. Each endpoint must validate requests using Plivo’s signature verification to prevent spoofing, then process the data asynchronously to maintain system responsiveness under high communication volumes.
Step-by-Step Configuration
Plivo Account Configuration
Begin with your Plivo account setup. Log into the Plivo console and navigate to the Phone Numbers section. Purchase a virtual number that will serve as your business line for both voice and SMS capabilities. Different countries impose various regulatory requirements for number verification, so select a number that aligns with your primary customer regions.
Navigate to the Applications section and create a new Plivo application. This application defines how Plivo handles incoming communications. Specify your Odoo server’s webhook URLs in the Message URL and Answer URL fields. Use HTTPS endpoints with valid SSL certificates, as Plivo requires secure connections for production webhooks. Generate and note your Auth ID and Auth Token from the account dashboard, as these credentials authenticate all API requests from Odoo.
Odoo Module Creation and Dependencies
Create a new Odoo module for the Plivo integration. Define your module manifest file with dependencies on ‘base’, ‘crm’, and ‘phone_validation’. The phone_validation module provides essential number formatting utilities that ensure consistent phone number handling between Odoo’s internal storage and Plivo’s API requirements.
Create the core model for storing Plivo configuration parameters. Implement a settings model that extends res.company, adding fields for plivo_auth_id, plivo_auth_token, plivo_phone_number, and webhook_base_url. Store authentication tokens using Odoo’s config parameters with proper encryption, never in plain text in the database. This approach maintains security while allowing different configuration per company in multi-company environments.
Authentication Handler Implementation
Build the authentication handler that manages Plivo API interactions. Create a PlivoAPI class that encapsulates all API operations. Implement methods for sending SMS, making calls, and fetching account details. This class should handle authentication using your stored credentials and manage API rate limiting to respect Plivo’s thresholds.
class PlivoAPI:
def __init__(self, auth_id, auth_token):
self.auth_id = auth_id
self.auth_token = auth_token
self.base_url = "https://api.plivo.com/v1/Account/"
def make_call(self, from_number, to_number, answer_url):
endpoint = f"{self.base_url}{self.auth_id}/Call/"
auth = (self.auth_id, self.auth_token)
payload = {
'from': from_number,
'to': to_number,
'answer_url': answer_url,
'answer_method': 'GET'
}
response = requests.post(endpoint, auth=auth, json=payload)
return response.json()
Webhook Controller Development
Develop webhook controllers that process inbound communications from Plivo. Create controllers.py in your module with endpoints for call and message webhooks. These controllers must verify request authenticity using Plivo’s signature validation, which prevents malicious actors from spoofing communication events.
from odoo import http
import hmac
import hashlib
import base64
class PlivoWebhook(http.Controller):
@http.route('/plivo/inbound/call', type='json', auth='public', methods=['POST'])
def inbound_call(self):
# Verify Plivo signature
signature = http.request.httprequest.headers.get('X-Plivo-Signature')
self._verify_signature(signature, http.request.jsonrequest)
# Process call data
call_data = http.request.jsonrequest
return self._create_call_log(call_data)
def _verify_signature(self, signature, data):
# Implementation of Plivo signature verification
pass
User Interface Integration
Integrate communication features into Odoo’s user interface. Extend the partner form view to display a new “Communications” tab that shows call history and SMS threads. Add smart buttons that display call statistics and message counts for each contact. Implement click-to-call functionality by adding phone number widgets that trigger calls when clicked.
Create scheduled actions for maintenance tasks like purging old call logs and synchronizing message statuses. These automated processes ensure your communication data remains current without manual intervention. Configure log rotation policies that balance historical data retention with database performance considerations.
Data Mapping and Transformation
Phone Number Normalization
Phone number formatting presents the first data mapping challenge. Odoo stores phone numbers in various formats based on user input, while Plivo requires E.164 format for all API interactions. Implement a normalization function that converts Odoo phone numbers to the standard +[country code][number] format that Plivo expects.
Create a phone utility module that handles international number parsing. Use the python-phonenumbers library to validate and format numbers, accounting for different country conventions. Store the normalized version in a computed field on partner records to optimize performance, as real-time normalization would impact system responsiveness during high-volume communication periods.
Call Log Data Structure
Map Plivo’s webhook payloads to Odoo’s call log model. When Plivo sends call event data, extract essential fields like call_uuid, from_number, to_number, call_direction, start_time, end_time, and call_status. Create a call.log model in Odoo with these fields plus relational fields to link to res.partner, crm.lead, and other relevant business objects.
Design the call log model with appropriate indexing strategies to maintain performance as call volume grows. Add database indexes on from_number, to_number, and create_date fields to optimize the common query patterns for finding calls by number and time period. Consider partitioning strategies for enterprises with extremely high call volumes exceeding thousands of calls per day.
SMS Message Threading
SMS message data requires different mapping approaches than call logs. Map inbound SMS messages to Odoo’s mail.thread model to maintain conversation continuity within existing chatter widgets. Extract the from_number, to_number, message_content, and timestamp from Plivo’s message webhook, then create or append to message threads associated with the corresponding partner.
Implement message threading logic that groups related messages into coherent conversations. Use the message UUID from Plivo to prevent duplicate processing when webhooks might retry delivery. For outbound messages, store the Plivo message UUID in Odoo to enable status tracking when delivery reports arrive through separate webhooks.
Custom Field Mapping Strategies
Define custom field mapping strategies for business-specific data requirements. If your organization tracks communication outcomes like “call result” or “customer sentiment”, create additional fields in your call log model and populate them through post-call processing. Implement automation that suggests field values based on call duration, time of day, or previous interaction patterns.
For advanced use cases, implement mapping rules that vary by partner tags or geographic regions. Create configuration models that allow administrators to define custom field transformations without code modifications. This approach maintains flexibility while preserving data consistency across different communication scenarios and business units.
Error Handling and Resilience
Common Plivo API Errors
The Plivo API returns specific HTTP status codes that indicate different error conditions. 400 errors signify bad requests, often from invalid phone numbers or incorrect parameter formats. 401 errors indicate authentication failures, typically from expired or invalid auth tokens. 429 errors represent rate limiting, which occurs when you exceed Plivo’s API call thresholds.
Implement comprehensive error handling for each API response type. Create a decorator that wraps all Plivo API calls and transforms HTTP errors into meaningful Odoo exceptions. Log detailed error context including timestamps, user context, and request parameters to facilitate debugging without exposing sensitive authentication data in log files.
Webhook Delivery Failures
Webhook delivery failures represent another common error scenario. Plivo attempts webhook delivery multiple times with exponential backoff, but persistent failures cause lost communication data. Implement idempotent webhook handlers that can process duplicate deliveries without creating redundant records. Use Plivo’s unique identifiers for calls and messages to detect and skip already processed events.
Create a dead letter queue mechanism for webhooks that fail processing after multiple attempts. Instead of discarding failed webhooks, store them in a separate model for manual review and reprocessing. This approach preserves communication data even when temporary system issues prevent normal processing, maintaining data completeness.
Network Resilience Strategies
Network instability between your Odoo instance and Plivo’s API requires resilience strategies. Implement retry mechanisms with jitter for all outgoing API calls. Use exponential backoff algorithms that increase wait times between retries, preventing cascade failures during Plivo service interruptions. Set reasonable timeout values that balance user experience with system resource consumption.
For critical communications, implement a fallback queue system that stores outgoing messages and calls when Plivo’s API becomes unavailable. Create a cron job that periodically attempts to send queued items, ensuring eventual delivery even during extended service disruptions. Monitor queue depth and age to alert administrators when backlogs indicate serious integration issues.
Debugging and Monitoring
Build comprehensive monitoring that tracks integration health. Create dashboards that display key metrics like API success rates, webhook processing times, and communication volumes. Implement alert rules that trigger when error rates exceed thresholds or when no communications flow for unexpected periods.
Develop debugging utilities that reconstruct communication flows from scattered log data. Create a diagnostic view in Odoo that shows the complete lifecycle of specific calls or messages, including all API interactions and webhook processing steps. This visibility accelerates troubleshooting when users report communication issues or missing records.
Testing and Validation
Test Environment Configuration
Establish a dedicated testing environment that mirrors your production setup. Create a separate Plivo account for testing purposes, using Plivo’s sandbox numbers that simulate call and SMS behavior without incurring charges. Configure test webhook endpoints that point to your staging Odoo instance, ensuring production data remains isolated during testing.
Prepare test data that covers various scenarios including international numbers, different time zones, and special characters in SMS content. Create partner records with phone numbers from different countries to validate international dialing capabilities. Develop test cases that simulate edge conditions like network timeouts, invalid numbers, and concurrent communication attempts.
Unit Test Implementation
Develop comprehensive unit tests that validate individual integration components. Test phone number normalization with inputs from various countries and formats. Verify webhook signature validation with both valid and tampered signatures. Create mock Plivo API responses that simulate success and error conditions, ensuring your error handling functions as expected.
Implement integration tests that validate the complete data flow from Odoo to Plivo and back. Use tools like Odoo’s HttpCase to simulate webhook requests and verify the resulting database records. Test concurrent webhook processing to identify race conditions or database locking issues that might emerge under production load.
End-to-End Validation Scenarios
Execute end-to-end validation scenarios that replicate real-world usage patterns. Perform complete test cycles for inbound calls, outbound calls, inbound SMS, and outbound SMS. Verify that call logs appear in the correct partner records with accurate duration and timing information. Confirm that SMS messages thread properly within Odoo’s chatter and maintain conversation history.
Validate integration behavior under load by simulating peak usage patterns. Use performance testing tools to send multiple simultaneous webhooks to your Odoo instance, measuring processing throughput and identifying resource bottlenecks. Monitor system resources during these tests to ensure the integration maintains stability without impacting other Odoo functions.
User Acceptance Testing
Conduct user acceptance testing with actual business teams before deployment. Train test users on the new communication features and observe how they incorporate them into daily workflows. Gather feedback on interface design, data presentation, and overall usability. Identify any gaps between technical implementation and business process requirements.
Create validation checklists that ensure all functional requirements meet acceptance criteria. Verify that security requirements like authentication and data encryption function correctly. Confirm that performance benchmarks for call log display and search operations meet user expectations. Document any issues discovered during testing and track them through resolution before production deployment.
Security Considerations
Authentication Security
Plivo integration introduces new authentication vectors that require careful security management. Store Plivo auth tokens using Odoo’s encrypted configuration parameters rather than database fields. Implement token rotation procedures that periodically update credentials, limiting exposure if tokens become compromised. Never log authentication tokens or include them in error messages that users might view.
Implement multi-layered authentication for administrative functions within your integration module. Require both Odoo administrator privileges and separate integration-specific credentials for accessing sensitive configuration screens. This defense-in-depth approach prevents privilege escalation attacks from compromising your Plivo account.
Webhook Security
Webhook endpoints represent potential attack surfaces since they accept external requests. Implement Plivo signature verification on all webhook handlers to ensure only legitimate Plivo requests process. Reject requests with invalid signatures immediately without further processing. Configure webhook endpoints with CSRF protection disabled since they require public accessibility for Plivo delivery.
Limit the data exposure in webhook responses. Plivo expects specific XML responses for call control instructions, but these responses should contain minimal sensitive information. Avoid including database identifiers, internal system details, or customer personal data in webhook responses that traverse external networks.
Data Protection and Privacy
Communication data often contains sensitive customer information requiring protection. Implement data encryption for call recordings and message content stored within Odoo. Use Odoo’s built-in encryption capabilities or database-level encryption features to protect data at rest. Establish data retention policies that automatically purge old communication records after specified periods, complying with privacy regulations.
Apply access controls that restrict communication data based on user roles. Sales team members should access communication history for their accounts but not entire organizational datasets. Implement record rules that enforce data segmentation between business units, departments, or teams based on your organizational security model.
API Security Hardening
Harden your API integration against common security threats. Implement request validation that sanitizes all inputs from both Odoo interfaces and Plivo webhooks. Use parameterized queries when storing communication data to prevent SQL injection attacks. Employ Odoo’s built-in cross-site scripting protections when rendering communication data in user interfaces.
Monitor API usage patterns for anomalous behavior that might indicate security breaches. Create alerts for unusual patterns like sudden spikes in international calls or SMS messages to premium numbers. Implement spending limits in your Plivo account to prevent financial loss from compromised credentials or system abuse.
Performance Optimization
Database Optimization Strategies
Communication data accumulates rapidly, demanding careful database management. Implement database indexing strategies that optimize common query patterns without degrading write performance. Create partial indexes on call log status fields where you frequently query for specific states like “completed” or “failed”. Use Odoo’s computed fields and store parameters judiciously to balance performance with storage costs.
Consider table partitioning for the call log model in high-volume environments. Partitioning by date ranges improves query performance for time-based reports and simplifies archival of old data. Implement this at the PostgreSQL level since Odoo’s ORM doesn’t natively support partitioning, but ensure your integration code remains compatible with the partitioned structure.
Caching Implementation
Implement strategic caching to reduce API calls and database queries. Cache Plivo’s account details like remaining balance and number information instead of fetching them repeatedly. Use Odoo’s cache tools with appropriate expiration times that balance data freshness with performance gains. Cache frequently accessed communication statistics on partner records to avoid expensive aggregations during interface rendering.
Develop application-level caching for phone number normalization results. Normalization involves computationally expensive parsing and validation, so caching transformed numbers provides significant performance benefits. Implement cache invalidation triggers that clear normalized values when source phone numbers update, maintaining data consistency.
Asynchronous Processing
Implement asynchronous processing for non-critical operations to maintain system responsiveness. Use Odoo’s queue system to defer tasks like communication analytics, sentiment analysis, or bulk message operations. Process webhook payloads asynchronously to prevent Plivo retries when your system experiences temporary load spikes.
Design long-running operations like bulk SMS campaigns as background jobs with progress tracking. This approach prevents browser timeouts and provides users with feedback on operation status. Implement job prioritization that processes time-sensitive operations like call initiation before batch operations like report generation.
API Call Optimization
Optimize API usage to minimize latency and reduce Plivo costs. Batch outgoing SMS messages where possible instead of sending individual API requests. Plivo’s bulk messaging endpoints support sending multiple messages in a single API call, reducing network overhead and improving throughput.
Implement connection pooling for HTTP requests to Plivo’s API. Reusing connections avoids the overhead of establishing new TLS sessions for each request. Configure appropriate timeout values that balance user experience with resource utilization, preventing hung requests from consuming application workers indefinitely.