Scale Readiness Assessment Tool

Platform Foundations

Infrastructure, containerization, and platform architecture

1. Infrastructure as Code

Manual infrastructure management (no IaC) Some scripts, but not declarative or version-controlled Terraform/Pulumi for some infrastructure, not fully automated Full IaC with Terraform/Pulumi, version-controlled, automated

2. Containerization Strategy

No containers, running directly on VMs/servers Using Docker locally, but not in production Containers in production (Docker/Kubernetes), some services Fully containerized with orchestration (K8s/EKS/ECS)

3. Platform Reliability

Frequent outages, no monitoring/alerting Basic monitoring, reactive to incidents Proactive monitoring, defined SLOs, some automation High reliability (99.9%+), automated recovery, SLO tracking

CI/CD Maturity

Pipeline automation and deployment frequency

1. Deployment Automation

Manual deployments (SSH, FTP, copy/paste) Basic CI (tests run), but deployments still manual CI/CD for some environments (staging auto-deploys) Full CI/CD to production, automated rollbacks

2. Deployment Frequency

Monthly or less frequent deployments Weekly deployments Daily deployments Multiple deployments per day (on-demand)

3. Testing in Pipeline

No automated tests Unit tests only, manually run Unit + integration tests in CI pipeline Comprehensive testing (unit/integration/e2e) blocking deploys

Automation & Toil

Manual work elimination and GitOps practices

1. Operational Toil

Most tasks are manual (>75% of time on repetitive work) Some automation, but 50%+ time still on manual tasks Most common tasks automated (<25% toil) Minimal toil (<10%), proactive automation culture

2. GitOps Adoption

No GitOps, manual kubectl/console changes Some config in Git, but not enforced GitOps for some environments (ArgoCD/FluxCD) Full GitOps, all changes via Git, automated sync

3. Self-Service Capabilities

Developers always need ops/platform team intervention Developers can deploy, but need ops for infrastructure Self-service for common tasks (deploy, scale, logs) Full self-service platform with internal developer portal

Dev/Sec/Ops Alignment

Team collaboration and toolchain integration

1. Team Collaboration

Dev/Ops/Sec operate in silos, frequent handoff issues Some collaboration, but still separate teams/tools Shared tooling and responsibilities, regular sync Fully integrated DevSecOps culture, shared ownership

2. Security Integration

Security is an afterthought, manual reviews Basic security scanning, but not in CI/CD Automated security scans in pipeline (SAST/DAST) Shift-left security, automated scans block bad code

3. Observability

No centralized logging/monitoring Basic logging (Cloudwatch/Splunk), manual correlation Centralized logging + metrics (ELK/Datadog/Prometheus) Full observability (logs/metrics/traces), distributed tracing

Migration Readiness

Cloud modernization and platform portability

1. Cloud Portability

Tightly coupled to specific cloud/vendor services Some vendor lock-in, migration would be difficult Mostly portable (containers, standard APIs) Fully portable, multi-cloud or cloud-agnostic design

2. Migration Planning

No migration plan or documentation Informal plans, but no tested migration strategy Documented migration plan, some components tested Tested migration runbooks, disaster recovery validated

3. Data Portability

Vendor-specific data formats, manual migration required Standard formats, but complex migration process Automated backups, tested restore procedures Fully automated data migration and validation

BPA Maturity

Business process automation and workflow integration

1. Workflow Automation

No workflow automation, all processes manual Basic automation with scripts/cron jobs Workflow tools (n8n/Zapier/Airflow) for some processes Comprehensive BPA platform automating most workflows

2. Tool Integration

Disconnected tools, manual data transfer Some integrations, but lots of manual work Most tools integrated via APIs or middleware Fully integrated toolchain, event-driven automation

3. Business-IT Alignment

Business processes not reflected in automation Some business processes automated, but inconsistent Business processes mapped and automated strategically Full digital transformation, business-driven automation

AI Agent Opportunities

Agentic automation and LLM integration readiness

1. AI/LLM Adoption

No AI/LLM usage in operations or development Ad-hoc ChatGPT usage by individuals AI tools integrated into some workflows (GitHub Copilot) Strategic AI integration with custom agents/automations

2. Data Readiness for AI

Data is siloed, unstructured, hard to access Some structured data, but not easily consumable Centralized data platform with APIs AI-ready data lake/warehouse with vector embeddings

3. Agentic Automation Potential

No clear use cases for AI agents Some repetitive tasks that could use AI automation Clear use cases identified, early experiments AI agents deployed handling complex workflows

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Platform Foundations

CI/CD Maturity

Automation & Toil

Dev/Sec/Ops Alignment

Migration Readiness

BPA Maturity

AI Agent Opportunities

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Your Scale Readiness Score

Score Breakdown

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