Storage

Choose and architect storage systems for applications with the right tradeoffs.

Security Scan

This is an instruction-only advisory skill about storage architecture; it contains guidance only, requests no credentials, and has no installable code.

Purpose & Capability

The SKILL.md content matches the name/description: it's a high-level guide on object/block/file storage, SQL/NoSQL tradeoffs, CDN and backup patterns. There are no unrelated environment variables, binaries, or config requirements.

Instruction Scope

The instructions are purely prescriptive guidance. They do not instruct the agent to read files, access environment variables, call external endpoints, or perform system operations beyond giving recommendations.

Install Mechanism

No install spec and no code files are present (instruction-only). Nothing will be downloaded or written to disk by an installer defined in the skill.

Credentials

The skill declares no required environment variables, credentials, or config paths—proportional to its stated purpose as a documentation/advice skill.

Persistence & Privilege

always is false and the skill does not request persistent presence or modify agent/system settings. disable-model-invocation is default (false), which is normal and not concerning here because the skill has no privileged actions.

Assessment

This skill is a read-only design guide and does not access your system or secrets—installing it is low risk. Consider that the content is general guidance (not provider- or context-specific): verify cloud pricing, compliance, and performance claims before acting on recommendations. If you plan to let an autonomous agent follow these recommendations, review any concrete changes it proposes (infrastructure changes, backups, replication) before execution.

Object vs Block vs File

• Object storage (S3, R2, GCS) for immutable blobs: images, videos, backups, logs — cheap, scales infinitely, but no partial updates
• Block storage (EBS, Persistent Disks) for databases and apps needing filesystem semantics — faster, but tied to single instance
• Network file systems (NFS, EFS) when multiple instances need shared filesystem access — convenient but latency and cost add up
• Default to object storage for user uploads — block storage for database files only

When SQL vs NoSQL

• SQL when you need joins, transactions, or complex queries — fighting against NoSQL for relational data wastes months
• Document stores (MongoDB, Firestore) for nested/variable schemas where you always fetch the whole document
• Key-value (Redis, DynamoDB) for simple lookups by ID at massive scale — not for complex queries
• Time-series databases (InfluxDB, TimescaleDB) for metrics with timestamp-based queries — regular SQL struggles with retention policies
• Start with PostgreSQL unless you have a specific reason not to — it handles JSON, full-text search, and scales further than most assume

Local vs Cloud Storage

• Local disk for ephemeral data: temp files, build artifacts, caches — assume it disappears on restart
• Cloud storage for anything that must survive instance termination — never store user data only on local disk
• Local SSD for databases in production — network-attached storage adds latency to every query
• Hybrid: local cache in front of cloud storage for frequently accessed files

CDN Patterns

• Put CDN in front of static assets always — origin requests are slower and more expensive
• Set long cache TTLs with versioned URLs (style.abc123.css) — cache invalidation is slow and unreliable
• CDN for dynamic content only if latency matters more than freshness — adds complexity for marginal gains
• Edge caching for API responses works but cache keys get tricky — start simple, add only when needed

Upload Handling

• Never accept uploads directly to app server disk in production — use presigned URLs to cloud storage
• Set file size limits at load balancer level, not just application — prevents memory exhaustion attacks
• Generate unique keys for uploads (UUIDs) — user-provided filenames cause collisions and path traversal risks
• Validate file types by content (magic bytes), not extension — extensions are trivially spoofed

Data Locality

• Keep compute and storage in same region — cross-region data transfer adds latency and cost
• Replicate data to regions where users are, not where developers are
• Multi-region storage adds complexity — single region with backups elsewhere usually sufficient
• Database read replicas in user regions for read-heavy workloads

Retention and Lifecycle

• Define retention policy before storing data — "keep everything" becomes expensive and legally risky
• Automate deletion of temporary data — manual cleanup never happens consistently
• Tiered storage for aging data: hot → warm → cold → archive — but check retrieval costs before archiving
• Separate storage for logs vs business data — different retention, different compliance requirements

Cost Traps

• Egress fees dominate cloud storage costs — calculate before choosing provider
• Many small files cost more than few large files — batch small writes when possible
• Minimum storage duration on cold tiers — early deletion still charges full period
• API request costs matter at scale — millions of LIST operations add up

Backup Strategy

• 3-2-1 rule: 3 copies, 2 different media types, 1 offsite — cloud counts as one location
• Test restores regularly — untested backups are not backups
• Point-in-time recovery for databases — daily snapshots lose a day of data
• Version important files — deletion or corruption often discovered late