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Automated Data Recovery Workflow for Backup Verification and Restoration of a Serverless Enterprise Document Management Application

Description

The proposed system implements a Serverless Enterprise Document Management Application with an automated workflow for data backup, backup verification, failure detection, and data restoration. The application allows employees and administrators to upload, organize, search, retrieve, update, and manage enterprise documents. Cloud Lambda provides serverless computing, while Cloud S3 stores the actual document files and PostgreSQL stores document metadata and application information. The backup and recovery workflow automatically creates backups, verifies whether the backups are usable, and restores the latest valid backup when data loss or application failure occurs.

Aim

To design and implement an automated data recovery workflow for a serverless Enterprise Document Management Application that provides reliable backup verification and automated restoration of application data after failures or data loss.

Objectives

01 Implement a serverless Enterprise Document Management Application using Cloud Lambda.
02 Store enterprise documents securely using Cloud S3.
03 Maintain document metadata and application information using PostgreSQL.
04 Automate regular backup operations.
05 Verify that backups are valid and can be restored.
06 Automatically restore application data after failure or data loss.
07 Monitor application, backup, and recovery operations.

Application Workflow

01

Stage 1 – User Registration

Process

The employee or administrator registers in the Enterprise Document Management Application.

Tools
Keycloak PostgreSQL
Implementation

The user enters personal and organizational details. The application validates the information, creates the user account, and stores the required user information in the database.

02

Stage 2 – User Authentication and Access

Process

The user logs into the application and accesses documents according to their role.

Tools
Keycloak PostgreSQL
Implementation

The user provides their login credentials. The application authenticates the user and determines their permissions, such as viewing, uploading, editing, sharing, or approving documents.

03

Stage 3 – Document Upload

Process

The user uploads an enterprise document to the application.

Tools
Cloud S3 PostgreSQL
Implementation

The user selects a document and enters information such as document name, category, department, and description. The application stores the document and records its metadata.

04

Stage 4 – Document Organization

Process

The user organizes documents according to business requirements.

Tools
Cloud S3 PostgreSQL
Implementation

The user creates folders and categories such as HR, Finance, Legal, Projects, and Administration. The application associates each document with the appropriate folder and category.

05

Stage 5 – Document Search and Retrieval

Process

The user searches for and retrieves required documents.

Tools
PostgreSQL Cloud S3
Implementation

The user searches using document name, category, department, keyword, or date. The application retrieves the matching metadata and provides access to the corresponding document.

06

Stage 6 – Document Update and Version Management

Process

The user updates an existing document while maintaining its previous versions.

Tools
Cloud S3 PostgreSQL
Implementation

The user uploads a revised document. The application stores the new version and updates the document metadata while retaining information about previous versions.

07

Stage 7 – Document Sharing

Process

The user shares documents with authorized employees or departments.

Tools
Keycloak PostgreSQL Cloud S3
Implementation

The document owner selects the required users or roles and assigns permissions such as view, download, or edit. The application stores and enforces these permissions.

08

Stage 8 – Document Approval

Process

Documents requiring authorization are submitted to managers or designated reviewers.

Tools
Keycloak PostgreSQL Cloud S3
Implementation

The reviewer accesses the submitted document and approves or rejects it. The application records the approval status, reviewer, and approval date.

09

Stage 9 – Document History and Audit

Process

The user or administrator views the document's activity and version history.

Tools
PostgreSQL Cloud S3
Implementation

The application maintains information about document versions, modifications, users, and timestamps. Authorized users can review the document's history.

10

Stage 10 – Document Archiving

Process

Completed, outdated, or inactive documents are archived.

Tools
Cloud S3 PostgreSQL
Implementation

The authorized user marks the document as archived. The application updates the document status while retaining the document and its historical information for future reference.

Cloud Infrastructure and Tools

Cloud Network Cloud VPC

Provides the network environment and controls connectivity between the application components and protected resources.

Serverless Compute Cloud Lambda

Runs application functions such as document upload, retrieval, update, search, and recovery-related processing without managing servers.

API Gateway Cloud API Gateway

Receives user requests and invokes the appropriate Lambda functions.

Document Storage Cloud S3

Stores the actual enterprise documents and backup copies.

Database PostgreSQL

Stores document metadata, user information, folders, permissions, document versions, and other application information.

Identity and Access Management Keycloak

Authenticates users and manages roles and permissions for accessing documents.

Backup Tool Restic

Creates and manages backups and supports restoration of application data during recovery.

Workflow Automation Apache Airflow

Automates and schedules the backup, backup verification, and restoration workflow.

Infrastructure as Code OpenTofu

Creates and manages the required Cloud infrastructure using configuration code.

Monitoring Prometheus

Collects metrics from the application, database, backup processes, and infrastructure.

Monitoring Dashboard Grafana

Displays application health, backup status, recovery status, and resource metrics through dashboards.

Cloud Security Cloud IAM

Controls permissions for Lambda and other Cloud services so that only authorized services and users can access application data.

Implementation Process

01
Step 1 – Analyze the Application and Recovery Requirements
  • Identify the documents and application data that need protection.
  • Identify the metadata stored in PostgreSQL.
  • Identify the documents stored in Cloud S3.
  • Define backup frequency and retention requirements.
  • Define recovery requirements and acceptable data loss.
02
Step 2 – Create the Cloud Infrastructure
  • Use OpenTofu to create the required Cloud resources.
  • Configure the Cloud VPC and required networking.
  • Configure security and IAM permissions.
  • Create the required S3 storage.
  • Configure PostgreSQL database infrastructure.
03
Step 3 – Deploy the Serverless Application
  • Create the required Cloud Lambda functions.
  • Configure API Gateway to invoke the Lambda functions.
  • Connect Lambda functions to PostgreSQL.
  • Connect Lambda functions to Cloud S3.
  • Configure Keycloak for authentication and role-based access.
04
Step 4 – Configure the Backup Workflow
  • Configure Restic for application data backup.
  • Configure PostgreSQL backup.
  • Configure document backup from S3.
  • Configure Apache Airflow to schedule the backup process.
  • Store backups in the designated backup location.
05
Step 5 – Configure Backup Verification and Recovery
  • Trigger backup verification after every backup.
  • Check whether the backup was successfully created.
  • Perform a test restoration of the backup.
  • Mark successful backups as Verified.
  • Configure Airflow to select the latest verified backup during recovery.
  • Restore PostgreSQL data and documents.
  • Verify the restored application data.
06
Step 6 – Configure Monitoring and Testing
  • Deploy Prometheus to collect application and recovery metrics.
  • Connect Prometheus to Grafana.
  • Monitor Lambda functions, database operations, storage, and backup jobs.
  • Simulate data loss or application failure.
  • Trigger the automated recovery workflow.
  • Verify that the latest valid backup is restored successfully.

Proposed Solution

The proposed solution uses a serverless architecture on cloud for an Enterprise Document Management Application. Cloud Lambda executes application functions, API Gateway handles user requests, Cloud S3 stores documents, and PostgreSQL stores document metadata. Restic and Apache Airflow automate backup, backup verification, and restoration. When data loss occurs, the recovery workflow identifies the latest verified backup and restores the required application data. Prometheus and Grafana provide monitoring of application and recovery operations.

Benefits

Automated Data Recovery: Reduces manual intervention during data loss.
Backup Verification: Ensures backups are tested before being used for recovery.
Serverless Architecture: Eliminates the need to manage application servers.
Data Protection: Protects both document files and application metadata.
Faster Recovery: Uses verified backups for restoration.
Scalability: Lambda can automatically handle varying application workloads.
Monitoring: Prometheus and Grafana provide visibility into application and recovery status.
Reduced Infrastructure Management: Cloud manages the underlying server infrastructure for Lambda.

Challenges

Backup Consistency: PostgreSQL metadata and S3 documents must correspond to a suitable recovery point.
Large Documents: Backing up and restoring large numbers of documents can take significant time.
Recovery Testing: Backup verification requires additional resources and testing environments.
Storage Cost: Maintaining multiple backup versions requires additional storage.
Workflow Complexity: Automated recovery requires proper handling of failures, retries, and verification.
Security: Backup copies must be protected because they contain enterprise documents.
Serverless Limitations: Lambda has execution and resource limits that must be considered when designing functions.
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