AI Resilience Assessment
Continuously assess your cloud and business continuity posture against best practice.
- Project range
- $8,000–18,000
- AWS running cost
- $80–380/mo
- Time to deploy
- 4–6 weeks
- Best-fit industries
- SaaS, Financial services
Executive summary
An assessment engine that inventories your cloud architecture and continuity controls, evaluates them against resilience best practices (single points of failure, backup coverage, recovery objectives, runbook readiness), and produces a prioritized, plain-language remediation plan. It replaces occasional, static resilience reviews with a living, continuously updated posture score.
Business problem
Most small and mid-size businesses discover resilience gaps during an outage. Backups are untested, recovery objectives are undefined, single points of failure hide in the architecture, and runbooks are stale. Traditional resilience audits are expensive, infrequent, and out of date the day they are delivered.
Architecture
AWS services
AWS Config
Observability- — Inventory resources and configuration state
- — Detect drift from resilient baselines
AWS Lambda
Compute- — Run resilience checks and scoring
- — Track findings and remediation
Best-practice checks
Compute- — Single-points-of-failure, backup coverage, RTO/RPO
- — Runbook and failover readiness
Amazon Bedrock
AI / ML- — Explain findings and prioritize remediation
- — Draft runbook and continuity improvements
Amazon S3
Storage- — Assessment reports and evidence, versioned
Amazon DynamoDB
Database- — Posture score, findings, and remediation state
Amazon EventBridge
Messaging- — Schedule sweeps and trigger on configuration change
Amazon SNS
Messaging- — Alert owners on new or worsening risks
Amazon CloudWatch
Observability- — Operational logs, metrics, and alarms
Data flow
- 1
AWS Config inventories cloud resources and configuration; runbooks and continuity docs are ingested.
- 2
On schedule or on change, Lambda runs best-practice checks for single points of failure, backup coverage, and recovery objectives.
- 3
Bedrock translates findings into a prioritized, plain-language remediation plan with effort and impact.
- 4
Posture score and findings are stored in DynamoDB; reports and evidence are versioned in S3.
- 5
SNS alerts owners on new or worsening risks, and a dashboard tracks the posture trend over time.
Security considerations
- Read-only assessment access by default; least-privilege IAM throughout.
- Evidence and reports encrypted and versioned for audit.
- Findings cite the specific resource and rule for verifiability.
- No changes made to production without explicit human action.
Cost considerations
- AWS Config and Bedrock assessment runs are the main variable costs.
- Scheduled and on-change evaluation avoids constant full scans.
- S3 and DynamoDB are inexpensive with lifecycle tiering.
Scalability
- Serverless and event-driven; scales across accounts and regions.
- New check packs (e.g., data, network, security resilience) extend coverage.
- Recovery objectives and baselines are configurable per workload tier.
Deployment roadmap
Phase 1 — Baselines & scope
Weeks 1–2- — Define RTO/RPO and resilient baselines per workload
- — Provision AWS foundation and Config inventory
Phase 2 — Build checks
Weeks 3–5- — Implement resilience check packs and scoring
- — Ingest runbooks and continuity documentation
Phase 3 — Report & operationalize
Week 6- — Stand up posture dashboard and alerts
- — Validate findings and prioritize the remediation backlog
Future enhancements
- Automated game-day and backup-restore testing.
- Cost-of-downtime modeling per workload.
- Chaos-experiment recommendations and tracking.
- Cross-account fleet resilience scoring in the executive dashboard.