Cloud-native architecture and cost: how design impacts TCO
Why cloud bills rise after migration and how to embed financial efficiency (FinOps) into infrastructure design during the application planning stage.
INSIGHTS & PRACTICE
AI and digital implementation
Practical guides to business-process automation: from the first assessment to measurable results.
57 publications
Cloud overspending: how to curb over-provisioning and zombie resources
Analyzing cloud architectural errors: from over-provisioning to uncontrolled scaling, and exploring practical mitigation methods through FinOps and proper governance.
Cloud governance: policies, tags, guardrails, and cost prevention
Effective cloud governance requires shifting from reactive cost-cutting to automated design-phase control and shared financial responsibility between teams.
FinOps practices for enterprise: from chaos to unit economics
A practical guide to cost allocation, rightsizing, and reserved capacity for CTOs and CFOs. Learn how to turn the cloud into a predictable and efficient business asset.
Anatomy of cloud billing: why budgets leak
Cloud budget control is a continuous architectural process. We analyze budget leaks, FinOps implementation, and practical infrastructure optimization tools.
Multi-cloud and hybrid infrastructure: when it makes sense
Analyzing a pragmatic approach to multi-cloud and hybrid architectures: how to avoid operational complexity traps, implement FinOps, and secure the organizational perimeter.
Cloud migration: lift-and-shift, re-platform, or re-architect
Choosing a cloud migration strategy is a financial and architectural decision. We analyze how to prevent budget growth using cost modeling and FinOps methodology.
FinOps in enterprise: from chaotic cloud spending to unit economics
An overview of implementing a FinOps culture, the Inform-Optimize-Operate cycle, and unit economics principles to effectively manage cloud spending in the enterprise sector.
Scaling AI-assisted development in enterprise: from code generation to engineering discipline
By 2027, successful AI adoption in development will depend not on code generation speed, but on integrating AI tools into controlled testing, security, and architectural oversight processes.
Integrating AI/ML into products: From prototype to production
Transitioning from experimental ML models to robust enterprise systems using AWS Well-Architected Framework, Google SRE, and 12-Factor App principles.
Managing technical debt and code quality in enterprise systems
How SRE practices, DORA metrics, and engineering discipline help prevent technical debt, while low-code platforms standardize core architecture.
From MVP to production-ready: architectural discipline
Transforming a successful prototype into a stable enterprise solution using the 12-Factor App, SRE practices, and the Well-Architected Framework.