Backups & Data Recovery: Engineering for Vibe Coders
Vibe coders often assume that data loss is something to worry about later. But prototypes fail, databases get reset, cloud resources are deleted, and bugs happen. Without a basic plan for backups and data recovery, a single mistake can wipe out weeks of work or critical user data.
Backups are not about paranoia. They are about accepting that failure will happen and designing for recovery. Thinking about backups early keeps your prototype safe, testable, and resilient.
1. What backups and data recovery really mean
A backup is a copy of data stored separately from the system that uses it. Data recovery is the ability to restore that data after loss, corruption, or failure.
Key ideas:
- Data loss is inevitable at some point
- Recovery matters more than the backup itself
- A backup you cannot restore is not a backup
- Prototypes still handle real data and effort
Even simple prototypes can benefit from minimal recovery planning.
🟢 Pre-prototype habit:
List what data would hurt to lose. User inputs, configurations, training data, logs, or generated outputs. Decide which ones deserve backups before coding.
2. What data actually needs to be backed up
Not all data is equal. Some can be recreated. Some cannot.
Common categories:
- Critical data: user accounts, user-generated content, business data
- Derived data: AI outputs, cached results, computed values
- Configuration data: environment settings, prompts, feature flags
- Ephemeral data: temporary state, in-memory queues
Backing up everything blindly increases complexity and cost.
🟢 Pre-prototype habit:
Classify your data as critical, derived, configuration, or ephemeral. Only plan backups for what truly matters.
3. Backup frequency and retention basics
How often you back up and how long you keep backups defines how much data you can afford to lose.
Key concepts:
- Backup frequency: hourly, daily, weekly
- Retention: how long backups are stored
- Recovery point objective (RPO): how much data loss is acceptable
- Recovery time objective (RTO): how fast recovery needs to happen
For prototypes, simple and conservative is often best.
🟢 Pre-prototype habit:
Decide how much data loss is acceptable and how fast you would need to recover. Write this down before building anything.
4. Common failure scenarios vibe coders overlook
Most data loss does not come from hackers. It comes from normal mistakes.
Typical scenarios:
- Accidental database deletion
- Re-deployments that wipe state
- Schema changes that corrupt data
- Buggy code that overwrites records
- Cloud resources destroyed during cleanup
Backups are your safety net for all of these.
🟢 Pre-prototype habit:
Walk through “what if I deleted this by accident?” scenarios for each data store. Decide how you would recover before coding.
5. Lightweight backup strategies for prototypes
You do not need enterprise tooling to be safe early on.
Simple approaches:
- Automated database snapshots
- Periodic exports to object storage
- Versioned backups with timestamps
- Manual restore testing on a schedule
- Keeping backups in a separate account or location
The goal is recoverability, not perfection.
🟢 Pre-prototype habit:
Choose the simplest backup mechanism that allows you to restore data confidently. Avoid anything you will not actually maintain.
6. Testing recovery, not just creating backups
A backup is only valuable if you know it works.
Recovery testing includes:
- Verifying backups exist and are readable
- Practicing restoring to a test environment
- Confirming data integrity after restore
- Measuring how long recovery takes
Most teams discover broken backups during an incident, which is too late.
🟢 Pre-prototype habit:
Plan at least one recovery test before your prototype handles important data. Write down the steps needed to restore.
7. Quick pre-prototype checklist
| Checklist Item | Why It Matters |
|---|---|
| Identify critical data | Determines what must be protected |
| Classify data types | Avoids unnecessary backups |
| Define acceptable data loss | Sets realistic expectations |
| Choose simple backup methods | Increases reliability |
| Plan recovery steps | Ensures backups are usable |
Backups and data recovery are not advanced topics reserved for production systems. They are foundational practices that protect your time, your users, and your credibility.
🟢 Pre-prototype habit:
Before writing code, list critical data, decide what loss is acceptable, choose a simple backup strategy, and write down recovery steps. A prototype that can recover is a prototype you can safely evolve.
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