InfoQ Homepage Platform Engineering Content on InfoQ
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Rightsizing Platform Engineering: Building the Platform Your Organization Actually Needs
Shift-left and DevOps have impacted how we flow changes from inception to production, but at the cost of increased cognitive load and duplication of effort across testing, security, and maintenance. This article explores the real-world challenges of rightsizing developer platforms and finding a cultural match for engineering teams who use them to reduce cognitive load and deliver change faster.
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InfoQ Culture and Methods Trends Report - 2026
This report summarizes how the InfoQ Culture and Methods editorial team sees the ongoing and emergent trends in the culture and methods space in 2026.
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The Hard-Stop Rule: from 3 HCM Monoliths to 120 Domain Microservices
A payroll and HR software team rebuilt three monoliths into over 120 smaller services over five years, with no dedicated migration budget. Every new feature was built as its own service instead of changing the old ones. The article covers the pull-based migration, the tools that made this possible, how costs were kept down, and the problems the team ran into along the way.
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An Evolutionary Architecture Pattern for Managing AI’s Pace of Change
Traditional API gateways assume deterministic services and simple schemas - assumptions agentic AI breaks. Discover why enterprise engineering leaders are adopting AI Gateways as an evolutionary architecture seam. Centralize guardrails, model routing, agent identity, action policy, and semantic audit within a single control plane to prevent costly incidents while keeping core platforms stable.
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Three Pillars of Platform Engineering: a Virtuous Cycle
Platform engineering succeeds when reliability and ergonomics reinforce each other rather than compete. This article explores three foundational pillars: automated reliability, developer ergonomics, and operator ergonomics. Together, they establish a virtuous cycle that strengthens system stability, reduces operational burden, and empowers teams to scale infrastructure with confidence.
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Event-Driven Patterns for Cloud-Native Banking: Lessons from What Works and What Hurts
Event-driven architecture helps banks decouple systems, scale services, and create clear activity trails. But it also introduces complexity, new failure modes, and operational challenges. Chris Tacey-Green explains where it adds value in banking systems and the practical patterns, such as inbox/outbox and stable event contracts, needed to make it reliable.
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Configuration as a Control Plane: Designing for Safety and Reliability at Scale
Configuration has evolved from static deployment files into a live control plane that directly shapes system behavior. The evolution of configuration management highlights why misconfigurations can trigger large outages and how hyperscalers deploy changes safely using staged rollouts, validation, blast radius limits, and automated rollback at scale.
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/articles/change-metrics-system-reliability/en/smallimage/change-metrics-systems-reliability-thumbnail-1772787617464.jpg)
Change as Metrics: Measuring System Reliability through Change Delivery Signals
System changes are the primary driver of production incidents, making change-related metrics essential reliability signals. A minimal metric set of Change Lead Time, Change Success Rate, and Incident Leakage Rate assesses delivery efficiency and reliability, supported by actionable technical metrics and an event-centric data warehouse for unified change observability.
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Proactive Autoscaling for Edge Applications in Kubernetes
Kubernetes often reacts too late when traffic suddenly increases at the edge. A proactive scaling approach that considers response time, spare CPU capacity, and container startup delays can add or remove instances more smoothly, prevent sudden spikes, and keep performance stable on systems with limited resources.
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Platform-as-a-Product: Declarative Infrastructure for Developer Velocity
Declarative infrastructure config hides complexity, enabling developers to focus on application code. Unified YAML per service allows early cost validation, while independent CI with centralized CD balances team autonomy and deployment consistency. This standardized approach scales across organizations, making infrastructure invisible and operations automatic.
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Overload Protection: the Missing Pillar of Platform Engineering
Overload protection is often overlooked in platform engineering, leaving teams to create inconsistent, fragile fixes. Centralized rate limits, quotas, adaptive controls, and clear visibility give services predictable ways to handle traffic spikes, reduce reliability debt, and prevent cascading failures across systems.
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Holistic Engineering: Organic Problem Solving for Complex Evolving Systems
Late projects. Architectures that drift from their original design. Code that mysteriously evolves into something nobody planned. These persistent problems in software development often stem not from technical failures, but from forces we pretend don't exist—reward systems that incentivize the wrong behaviors, organizational structures that ignore domain boundaries, and human dynamics.