InfoQ Homepage DevOps Content on InfoQ
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/articles/event-driven-banking-architecture/en/smallimage/event-driven-banking-architecture-thumbnail-1774430827143.jpg)
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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/articles/configuration-control-plane/en/smallimage/configuration-as-a-control-plane-designing-for-safety-and-reliability-at-scale-thumb-1773657574566.jpg)
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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/articles/proactive-autoscaling-edge-kubernetes/en/smallimage/proactive-autoscaling-edge-kubernetes-thumbnail-1770721062673.jpg)
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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/articles/architecting-agentic-mlops-a2a-mcp/en/smallimage/architecting-agentic-mlops-a2a-mcp-1770303550343.jpg)
Architecting Agentic MLOps: a Layered Protocol Strategy with A2A and MCP
In this article, the authors outline protocols for building extensible multi-agent MLOps systems. The core architecture deliberately decouples orchestration from execution, allowing teams to incrementally add capabilities via discovery and evolve operations from static pipelines toward intelligent, adaptive coordination.
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/articles/agent-assisted-intelligent-observability/en/smallimage/agent-assisted-intelligent-thumbnail-1769595476571.jpg)
From Alert Fatigue to Agent-Assisted Intelligent Observability
As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.
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/articles/durable-objects-handle-inflight-requests/en/smallimage/durable-objects-handle-inflight-requests-thumbnail-1769161248259.jpg)
One Cache to Rule Them All: Handling Responses and In-Flight Requests with Durable Objects
Traditional caching fails to stop "thundering herds" where multiple clients trigger the same work during a miss. This article proposes using Cloudflare Durable Objects to treat in-flight work and finished results as two states of one cache entry. By routing to a single owner, systems eliminate redundant tasks. This pattern replaces complex locks with simple promises, simplifying the system design.
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/articles/preventing-data-exfiltration-google-cloud/en/smallimage/preventing-data-exfiltration-google-cloud-thumbnail-1768221099670.jpg)
Preventing Data Exfiltration: a Practical Implementation of VPC Service Controls at Enterprise Scale in Google Cloud Platform
Implementing VPC Service Controls is more about people and process than technology. Organizations must conduct extensive upfront discovery, use phased rollouts to avoid breaking production systems, and design VPC Service Controls that enable rather than block work. Success requires automation, clear exception processes, tracking both security and business metrics, and continuous improvement.
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/articles/platform-golden-path-approach/en/smallimage/thumbnail-platform-golden-path-approach-1768216983360.jpg)
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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/articles/DORA-metrics-PBCs/en/smallimage/thumbnail-dora-metrics-1766410050172.jpg)
Stop Guessing, Start Improving: Using DORA Metrics and Process Behavior Charts
Delivery performance rarely changes in a straight line. Small degradations caused by tooling, environment instability, or team changes can accumulate quietly, while real improvements take time to emerge. This article shows how combining DORA metrics with Process Behavior Charts helps teams zoom out, detect meaningful shifts early, and validate improvement hypotheses.
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/articles/overload-protection-platform-engineering/en/smallimage/overload-protection-platform-engineering-1764921362184.jpg)
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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/articles/holistic-engineering-organic-problem-solving-complex-systems/en/smallimage/holistic-engineering-organic-problem-solving-complex-systems-thumbnail-1762857128649.jpg)
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.