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Concepts Overview

This article describes the key concepts and architecture of PinkCloudSync.

Core Concepts

Sync Session

A sync session is the process of transferring data between a source and target system1. Each session has:

  • A unique identifier (UUID)
  • Execution status
  • Source and target configuration
  • Processing statistics
stateDiagram-v2
    [*] --> pending: Create session
    pending --> in_progress: Start sync
    in_progress --> completed: Success
    in_progress --> failed: Error
    failed --> [*]
    completed --> [*]

Data Sources

PinkCloudSync supports various types of data sources:

Type Description Examples
database Relational and NoSQL databases PostgreSQL, MySQL, MongoDB
api REST API endpoints External services
file File sources CSV, JSON, XML

Conflict Resolution Strategies

During data synchronization, conflicts may occur — situations where the same record has been modified in both systems. PinkCloudSync offers several strategies:

Manual

Conflicts are saved for subsequent manual resolution via API.

Best for: Critical business data, financial records, customer information requiring review.

Source Wins

Always use data from the source, discard changes in the target system.

Best for: One-way synchronization, master data management, authoritative source scenarios.

Target Wins

Always use data from the target system, discard changes in the source.

Best for: Preserving local modifications, backup scenarios, read-only source systems.

Newest Wins

Use the version with the most recent modification timestamp.

Best for: Bidirectional synchronization, collaborative environments, general-purpose syncing.

Recommendation

For critical data, use the manual strategy to avoid losing important information.

System Architecture

PinkCloudSync consists of several key components that work together to provide reliable data synchronization:

  • API Gateway — handles incoming requests and authentication
  • Sync Engine — manages the synchronization process
  • Conflict Resolver — applies conflict resolution strategies
  • Metadata Database — stores session information and statistics

Synchronization Process

  1. Initialization

    • Client creates a sync session via API
    • System validates connection parameters
    • Record is created in metadata database

  2. Data Reading

    • Sync Engine connects to the source
    • Data is read in batches
    • Filters are applied if specified

  3. Processing

    • Each record is compared with the target system
    • Changes are determined (create, update, delete)
    • Conflicts are detected

  4. Conflict Resolution

    • Selected strategy is applied
    • Conflicts are logged
    • Tasks for manual resolution are created if needed

  5. Data Writing

    • Changes are applied to the target system
    • Session statistics are updated
    • Notifications are sent

  6. Completion

    • Session transitions to completed or failed status
    • Synchronization report is generated

Security

Authentication

PinkCloudSync uses two-step authentication:

  1. API keys — to obtain an access token
  2. JWT tokens — to authenticate API requests

Encryption

  • All data is transmitted over HTTPS
  • Credentials for connecting to sources are encrypted in the database
  • API secrets are hashed using bcrypt

Access Control

Each API key has a set of permissions:

  • sync:read — read session information
  • sync:write — create and manage sessions
  • conflicts:read — view conflicts
  • conflicts:write — resolve conflicts

Performance

Optimization

  • Batch processing — data is processed in batches to reduce load
  • Parallel synchronization — multiple sessions can run simultaneously
  • Incremental synchronization — only changed data is synchronized

Performance

PinkCloudSync can process up to 10,000 records per second with optimal configuration.

Limitations

Technical Limitations

Parameter Value
Maximum batch size 1000 records
Maximum session duration 24 hours
Maximum record size 10 MB
Concurrent sessions per account 100

Best Practices

Data Volume Management:

  • Use filters to limit the volume of synchronized data
  • Split large volumes into multiple sessions
  • Schedule large syncs during off-peak hours

Monitoring:

  • Configure notifications to track the status of long operations
  • Monitor conflict rates to identify data quality issues
  • Set up alerts for failed sessions

Error Handling:

  • Implement retry logic with exponential backoff
  • Log all errors for troubleshooting
  • Have a rollback strategy for critical data

Next Steps

  1. Sessions are stateful and can be monitored, paused, or cancelled through the API. ↩