Applied engineering, without conference-room abstraction.
We publish field notes, architecture decisions and operational lessons on SaaS, cloud, data, observability and AI engineering. The focus is what helps technical teams and founders scale product with less noise and more evidence.
FinOps for cloud without sacrificing performance
FinOps for the cloud reduces waste without cutting capacity. See how to unite costs, architecture, and operations for better decisions in your production SaaS.
Guide to incidents in production without the hype
Production incident guide for SaaS teams: how to respond quickly, reduce impact, organize roles and learn without creating bureaucracy.
Reliability of SaaS systems in practice
Reliability of SaaS systems requires mature architecture, observability and operation. Understand what really reduces risk and downtime.
Kubernetes vs. serverless: real scalability
Kubernetes vs. serverless scalability: compare latency, cost, operation and real limits to decide with technical criteria in production.
A resilient architecture guide for SaaS
SaaS resilient architecture guide to scale safely, reduce failures, control p99, cloud costs and operational risk.
Multi Region Architecture Guide for SaaS
Multi region architecture guide for SaaS: when it makes sense, practical standards, risks, costs and operating decisions to climb safely.
How to structure an internal SaaS platform
How to structure an internal SaaS platform with a focus on autonomy, reliability, cost and real operation, without creating another layer of complexity.
Modern analytics architecture in practice
Modern analytics architecture organizes data, reduces delay and improves governance for SaaS to operate BI, product and AI with predictability.
8 leading causes of downtime in SaaS
Understand the main causes of downtime in SaaS, how to identify them early and what to do to reduce scale and production impact.
Corporate data governance in practice
Corporate data governance with a focus on execution: quality, access, security and operation for SaaS, analytics and AI in production.
How to define SLI and SLO without fictional targets
Learn how to define SLI and SLO with technical criteria, user focus and viable goals for SaaS operations without falling into empty metrics.
End-to-end observability in practice
End-to-end observability connects metrics, logs, traces and business impact to reduce MTTR, cost and risk in SaaS on scale.
Staff Engineer vs Fractional CTO
Staff engineer vs Fractional CTO: understand when each paper accelerates architecture, execution and scale without inflating structure or management.
An operational maturity guide for SaaS
Operational maturity guide SaaS for CTOs and founders: how to reduce risk, gain scale and evolve architecture without expensive rewrites.
How to reduce API latency in practice
See how to reduce API latency with a focus on p95 and p99, database, cache, network and observability. Less delay, more real predictability.
SaaS platform engineering in practice
SaaS platform engineering reduces operational friction, improves cost, and reliability without rewriting already critical systems in production.
How to prepare data for AI without creating debt
Understand how to prepare data for AI with quality, governance and traceability, without creating technical debt or slowing down the operation.
AWS or Azure SaaS: which makes more sense?
AWS or Azure SaaS: Compare cost, operations, data, AI, and governance to decide the right cloud without creating technical debt in the product.
When to rewrite a legacy system
Understand when rewriting legacy system makes sense, what signs to observe and how to avoid an expensive, slow and risky decision.
Data pipeline for noise-free analytics
Data pipeline for analytics requires modeling, observability and governance. See how to structure a reliable basis for decisions.
How to reduce cloud costs without slowing down scale
How to reduce cloud costs without compromising performance, reliability and scale. See where to cut waste and where to invest better now.
What a platform engineer does in practice
Understand what platform engineer does, where this role acts and how it reduces friction, cost and risk in SaaS teams that already operate in production.
9 signs of poorly planned cloud architecture
See 9 ill-planned cloud architecture signals and understand how they affect team cost, latency, reliability and speed.
How to improve observability in production
Learn how to improve observability in production with useful metrics, logs and traces, less noise and more context to operate safely.
When to hire a Fractional CTO
Learn when to hire a Fractional CTO and identify signs of architecture, scale, and operation that require senior technical leadership.
How to scale SaaS safely
See how to safely scale SaaS without rewriting everything: architecture, observability, data, costs, and reliable operation in production.
A no-hype Power BI executive dashboard
How to structure an executive Power BI dashboard that shows risk, revenue and operations without noise, with reliable data and real use of leadership.
Is Azure Data Factory Consulting worth it?
Azure Data Factory consultancy to structure pipelines, reduce failures and scale data with governance, controlled cost and real execution.
Is Databricks consulting in Brazil worth it?
Databricks Brasil consultancy for companies that need to structure data, reduce costs and put analytics and AI into production with less friction.
AI engineering for enterprises without the hype
AI engineering for enterprise requires ready data, observability, governance and secure rollout. Less pretty pilot, more stable production.
Data analytics for SaaS without the hype
Data analytics for SaaS with a focus on product, revenue and operations. Learn what to measure, how to model data, and where to avoid technical debt.
Modern data architecture in practice
Modern data architecture requires less theory and more operation: scale, governance, cost, analytics and real foundation for AI in production.
Data engineering consultancy in practice
Data engineering consultancy for SaaS that needs to scale with governance, reliable pipelines, cost under control and AI-ready data.
Is Fractional CTO for startups worth it?
Fractional CTO for startups helps to scale product, cloud and team with practical seniority, without inflating structure or slowing down execution.
Observability consultancy in practice
Observability consultancy for SaaS in production: less guesswork, more visibility into latency, errors, cost and real reliability.
AWS and Azure cloud architecture without guesswork
AWS Azure cloud architecture requires clear technical choices to scale with true cost, resilience, observability, and governance.
Is Kubernetes Consulting for SaaS worth it?
Understand when Kubernetes consultancy for SaaS makes sense, what to review in the cluster and how to gain scale, cost and reliability.