From Disaster to Recovery: Guide to PostgreSQL Backup Strategies (Part-1)
The only guide you need for Backup & Recovery Strategies
Note: This blog post will be published in two parts.
In the digital domain, data serves as the cornerstone of all operations, making the prospect of loss a critical concern. "From Disaster to Recovery: A Comprehensive Guide to PostgreSQL Backup Strategies" offers a strategic roadmap and framework to safeguard your most crucial asset—your data.
Through this blog, we'll explore the simple and easy process of assessing the value and sensitivity of your data, aligning it with compliance requirements, and establishing clear recovery objectives. Dive into the intricacies of various backup approaches—full, incremental, and logical—and discover how to tailor the frequency and methods of backups to the unique rhythm of your PostgreSQL databases.
Each step in this blog is designed to build a resilient framework for your data's protection, ensuring that your team is well-equipped to handle the data recovery process with finesse and confidence.
Why do we need Database backups ?
What if there is Hardware Failure or the cloud instance is crashed?
Quick Recovery: What if I have to Restore a dropped table or schema? How Do i recovery a deleted row or column?
Compliance and Regulatory Requirements: Compliance like ISO 27001 requires
User Error: Modified the data accidentely - how do i reach to previous state?
Maintaining Customer Trust- can our process honor customer contract and confidence?
Database Corruption
1. Assess Your Data and Requirements
When developing a backup and recovery strategy for PostgreSQL(Or any Other Database), the first and most crucial step is to thoroughly assess your data and understand your specific requirements. This is where you want to focus to find critical data and categories based on the impact of losing it.
This assessment lays the groundwork for a tailored backup strategy that aligns with your organizational needs and goals.
Understand Data Value
Identifying Critical Data: Begin by categorizing your data based on its importance to your business operations. Not all data is created equal; some are critical for your business continuity, while others might be less significant. Is it entire database, Schema or table?
Sensitivity and Confidentiality: Recognize the sensitivity of your data. Are you handling personal identifiable information (PII), financial records, or proprietary business information? The higher the sensitivity, the more stringent your backup and recovery processes need to be.
Impact Analysis: Conduct an impact analysis to understand the repercussions of data loss or unavailability. How would data loss affect your business operations, reputation, and revenue?
Compliance Needs
Regulatory Requirements: Different industries are subject to various legal and regulatory frameworks. For instance, healthcare data might need to comply with HIPAA, while financial data might be governed by GDPR or SOX.
Data Retention Policies: Understand the required retention periods for different types of data. Some regulations may mandate keeping records for a specified number of years.
Audit Trails and Record-Keeping: Ensure that your backup strategy supports compliance-related record-keeping and audit requirements.
Recovery Objectives
(Source)
Recovery Time Objective (RTO): This is the maximum acceptable time to restore your database operations after a disaster. RTO is crucial for business continuity planning. A lower RTO indicates a need for more frequent backups ,Robust recovery solutions, and faster recovery solutions.
Recovery Point Objective (RPO): RPO defines the maximum acceptable amount of data loss measured in time. It determines how often you need to perform backups. A tighter RPO requires more frequent backups to minimize potential data loss.
Balancing Objectives with Cost and Complexity: There’s often a trade-off between achieving lower RTOs and RPOs and the associated costs and complexity. Assess the cost-benefit ratio to find a balance that suits your business needs and resources. For example: Lower RTOs and RPOs requires having delayed replicas and standby solutions in place. Having an additional server(replica) will host more $$$.
2. Choose Backup Types
After assessing your data and requirements, the next crucial step in developing a PostgreSQL backup and recovery strategy is selecting the appropriate types of backups. This choice depends on factors like the size of your database, the frequency of data changes, and your recovery objectives.
Full Backups
What They Are: Full backups involve making a complete copy of the entire database at a specific point in time. This includes all data files, tablespaces, and transaction logs.
Advantages: Full backups provide a comprehensive snapshot of your database, simplifying the recovery process since you have all the data in one set.
Considerations: They tend to be time-consuming and require more storage space, especially for large databases. Also, frequent full backups can lead to redundancy in stored data.
Usage: Best suited for smaller-mid size databases or situations where the database isn’t updated frequently.
Incremental Backups
What They Are: Incremental backups only save the data that has changed since the last backup (either the last full backup or the last incremental backup).
Advantages: They are faster and consume less storage space compared to full backups. Incremental backups reduce the load on the backup storage system and are efficient for databases with frequent changes.
Considerations: The recovery process can be more complex and time-consuming, as it requires the last full backup and all subsequent incremental backups(WAL logs)
Logical Backups
What They Are: Logical backups involve exporting database objects and data into a human-readable format, often using tools like pg_dump for PostgreSQL.
Advantages: These backups are portable and can be useful for migrating data across different systems or PostgreSQL versions. They allow for selective backup and restoration at the object level (like specific tables).
Considerations: The backup and recovery process can be slower, especially for large databases. Also, they may not capture some low-level database attributes like OID (Object Identifier).
Usage: Best for smaller databases, object-level recovery needs, or for cross-version database migrations.
Backup Consideration based on Importance and transactions
Imagine a busy online retail store with a PostgreSQL database that handles transactions such as customer orders, inventory updates, and payment processing. This database is a high-transaction environment, with data changing almost every second.
To safeguard against data loss, the store implements a backup strategy that includes:
Full backups every night during the least busy hours.
Incremental backups(wal logs) every 4 hours to capture the day’s transactions.
This approach ensures that, in the worst-case scenario of a database failure the store would only lose a maximum of 4 hours of transaction data, aligning with their RPO.
Conversely, consider a small community library’s database that catalogs books and tracks borrowings. This database experiences much fewer changes – maybe a few updates a day. A weekly full backup suffices for their needs, as the risk and impact of data loss are much lower compared to the retail store scenario.