NWave nw-deployment-strategies

Rollback procedures, risk assessment, pre/post-deployment validation, and contingency planning. Load when orchestrating deployment or preparing rollback plans. For deployment strategy details (canary, blue-green, rolling), see `cicd-and-deployment` skill.

install

source · Clone the upstream repo

git clone https://github.com/nWave-ai/nWave

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/nWave-ai/nWave "$T" && mkdir -p ~/.claude/skills && cp -r "$T/nWave/skills/nw-deployment-strategies" ~/.claude/skills/nwave-ai-nwave-nw-deployment-strategies && rm -rf "$T"

manifest: nWave/skills/nw-deployment-strategies/SKILL.md

source content

Deployment Strategies — Rollback, Risk, and Validation

For deployment strategy patterns (canary, blue-green, rolling, progressive delivery), see

cicd-and-deployment

skill. This skill focuses on operational concerns: validation, rollback, risk, and post-deployment.

Pre-Deployment Validation

Before any deployment, validate:

Deployment scripts tested in staging | Database migrations tested with rollback scripts
Configuration management consistent across environments | Health checks and service discovery configured
Monitoring and alerting systems prepared | Backup and disaster recovery procedures validated

Rollback Procedures

Design Rollback First

Every deployment plan starts with the rollback section:

Database rollback: migration revert scripts tested and verified
Application rollback: previous version tagged and deployable
Configuration rollback: previous config snapshots available
Traffic rollback: load balancer / feature flag kill switch ready
Data rollback: data consistency plan for partial rollback scenarios

Automated Rollback Triggers

Configure automatic rollback when:

Error rate exceeds baseline by >2x | P95 latency exceeds SLA threshold
Health check failures exceed threshold (e.g., 3 consecutive) | Business metric anomaly detected (e.g., conversion drop >10%)

Manual Rollback Decision Criteria

Stakeholder-reported functional issues | Security vulnerability discovered post-deploy | Data integrity concerns | Performance degradation below acceptable levels.

Risk Assessment

Technical Risks

Integration failure with downstream services | Performance degradation under production load | Data migration integrity issues | Security vulnerabilities introduced.

Business Risks

User adoption challenges | Business process disruption | Stakeholder expectation misalignment.

Operational Risks

Infrastructure capacity limitations | Third-party dependency failures | Team availability for incident response.

Risk Mitigation Checklist

Rollback procedure designed and tested
Monitoring dashboards configured for deployment
On-call team notified of deployment window
Feature flags configured for gradual rollout
Communication plan for stakeholders prepared
Incident response runbook updated

Post-Deployment Validation

Production Smoke Tests

Critical user paths validated | Integration points tested with real external systems | Performance validated under production load | Security controls verified | Data integrity confirmed.

Monitoring Validation

Application performance metrics collecting | Error tracking and alerting active | Business metric dashboards updated | Infrastructure monitoring nominal.