Operations | Monitoring | ITSM | DevOps | Cloud

The Ingress NGINX project is winding down. For many organizations, this means planning a migration for critical infrastructure. While the HAProxy Kubernetes Ingress Controller is the natural successor for these workloads, a "rip and replace" strategy isn’t always viable. You might have complex configurations, customized annotations, or deployment freezes that make a sudden switch risky. There's a lower-risk path: Place HAProxy in front of your existing Ingress NGINX deployment.

Harness is strengthening the open Liquibase ecosystem by introducing a native MongoDB executor that removes long-standing limitations for Community Edition users. It enables teams to run MongoDB scripts, generate changelogs, and integrate database workflows into CI/CD without relying on paid extensions. The initiative reinforces open collaboration while making MongoDB-based database DevOps more accessible, consistent, and production-ready.

Modern enterprises rely on software-defined wide area networks (SD-WANs) to connect branch offices, data centers, and cloud environments. While this flexibility improves resiliency and performance, it also increases operational complexity.

Modern CI/CD pipelines have automated the hard work of building, testing, and deploying our code. But for many teams, that’s where the automation stops. The most critical part of a release, turning a new feature on for real users, is still a stressful, manual process. An engineer cautiously ramps up traffic to 5%, then 10%. The whole team stares at dashboards, trying to see if anything breaks. If something does, they scramble to manually roll back.

This glossary is a bookmarkable reference for cost-per-unit metrics in FinOps unit economics. It’s designed for engineering, finance, and FinOps teams that need a shared language for understanding how cloud costs behave as usage, customers, and products scale. The terms are organized by category and include real-world context.

The initial hype of AI agents is hitting a hard reality: a clever prompt is not a production strategy. As organizations move from experimentation to operationalizing AI in 2026, a systemic bottleneck has emerged: It is not the model's intelligence; it is the model’s context and its access to the right tools. When an AI agent lacks access to live, grounded platform data, it guesses.