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harness

Architecting Trust: The Blueprint for a "Golden Standard" Software Supply Chain | Harness Blog

Feb 5, 2026 By Aditya Kashyap In Harness
We’ve all seen it happen. A DevOps initiative starts with high energy, but two years later, you’re left with a sprawl of "fragile agile" pipelines. Every team has built their own bespoke scripts, security checks are inconsistent (or non-existent), and maintaining the system feels like playing whack-a-mole. This is where the industry is shifting from simple DevOps execution to Platform Engineering.
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Komodor

From Blueprint to Production: Building a Kubernetes MCP Server

Feb 5, 2026 By Nir Adler In Komodor
As Large Language Models (LLMs) evolve from simple chatbots into agentic workflows, the need for a standardized way to connect them to external data and infrastructure has become critical. In a recent workshop hosted by Nir Adler, Innovation Engineer at Komodor, we explored how to bridge this gap using the Model Context Protocol (MCP).
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harness

Backstage Alternatives: IDP Options for Engineering Leaders | Harness Blog

Feb 5, 2026 By Bri Strozewski In Harness
Backstage alternatives fall into three real choices: build and own a framework, buy a fully managed IDP product, or choose a hybrid path that reduces maintenance but keeps Backstage at the core. The trade-off is not "free vs paid" but engineering headcount, governance maturity, time to value, and how actionable your portal is across CI/CD, IaC, and environments. The best commercial IDPs go beyond catalog and documentation.
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Your Boss Doesn't Understand Your Work (Here's Why)

Feb 5, 2026 By GitKraken In GitKraken
Developer productivity metrics create unique anxiety. If your company rolled out tracking systems like DORA metrics or velocity dashboards, you're probably wondering what these numbers mean and how they'll evaluate your work. At GitKon 2025, we assembled senior engineers from GitHub, Cloudflare, Kong, and GitKraken to discuss "Your Boss is Measuring You, Now What?" The panel included both individual contributors and engineering leaders, creating an honest conversation about measurement from both perspectives.
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upsun

Why MCP is becoming part of your product surface

Feb 5, 2026 By Upsun In Upsun
AI assistants are quickly becoming a primary interface for how people interact with software. Developers ask them how to integrate APIs. Users ask them how products work. Buyers ask them how tools compare. Increasingly, the first explanation someone receives about your product does not come from your website, your documentation, or your sales team. It comes from an AI assistant. That shift has an important consequence that many organizations are only starting to notice.
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upsun

Why preview environments only work when the platform owns them

Feb 5, 2026 By Upsun In Upsun
Deployments are one of the few moments where software development still feels risky. Teams may have tests, a staging environment, and careful review processes, yet the final step still carries uncertainty. Will this change behave the same way in production? Will it interact cleanly with existing data, traffic, and infrastructure? Will it introduce regressions no one anticipated? Preview environments exist to reduce that uncertainty.
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upsun

Upsun's AI story: the 5% path from pilots to production value at scale

Feb 5, 2026 By Upsun In Upsun
Here’s the uncomfortable truth: most companies do not have an AI problem. They have a delivery problem wearing an AI costume. MIT’s Project NANDA research has been widely cited for a brutal headline statistic: roughly 95% of corporate generative AI pilots fail to produce measurable business impact or returns, while only about 5% break through to meaningful outcomes. (Yahoo Finance) The models are impressive. The demos are dazzling. The budgets are real.
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Top 9 Observability Tools for AI-Assisted Development & Deployment

Top 9 Observability Tools for AI-Assisted Development & Deployment

Feb 5, 2026 By OpsMatters In OpsMatters
AI-assisted development is rapidly becoming the default way software is built. Code generation, AI copilots, agentic pull requests, and automated refactoring are now embedded directly into engineering workflows. While this shift dramatically increases delivery speed, it also introduces a new operational reality: production systems are changing faster than humans can fully reason about them. This is where observability becomes mission-critical.
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speedscale

What AI Has Never Seen: The Context Gap in Code Generation

Feb 4, 2026 By Ken Ahrens In Speedscale
Your AI coding assistant has read the entire internet. It knows every programming language, every framework, every best practice documented in Stack Overflow answers and GitHub repositories. It can generate a REST API handler in seconds that looks perfect with clean code, proper error handling, following all the patterns. But here’s what it’s never seen: your production traffic. Data from a real API request. Someone filling out a form with messed up or incomplete data.
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upsun

What mid-market IT teams wish they knew before deploying AI agents

Feb 4, 2026 By Upsun In Upsun
AI agents are quickly shifting from experimentation into day-to-day operations. That shift is showing up in the data. McKinsey’s latest State of AI research highlights both broader AI use and the growing focus on “agentic AI,” even as many organizations still struggle to scale safely. For mid-market IT teams, agents can feel like the unlock: automate repetitive workflows, reduce backlog pressure, and deliver more output without expanding headcount.
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