Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Piotr Zaniewski, vCluster Labs Head of Engineering Enablement
The increasing rate of adoption of generative AI this past year has introduced a number of challenges and learnings for cloud-native development. This is good news as this type of stress fuels faster innovation and more options for solutions. Next year we will certainly see adoption of genAI continue to increase, but there will be exciting shifts in how platform teams and developers extract its value.
Below are three distinct trends I believe will pick up momentum in 2026.
Multitenancy will be non-negotiable as GPU renting becomes commonplace
We predict a surge in companies renting out GPUs, serving as intermediaries between hardware leaders like NVIDIA and the businesses seeking intense compute power. Success in this market will no longer hinge solely on access to the best hardware, but will also depend on the surrounding software experience including ease of onboarding, developer ergonomics, strong workload isolation, and integrated security. Capabilities once considered “advanced” or “exotic,” like robust multitenancy, will quickly become the industry baseline, just as virtualization is today. Those who are able to implement reliable multitenancy seamlessly, rather than building from scratch, will be the ones who scale quickly and win in this evolving market.
AI-powered development will trigger a ‘quality hangover’
AI is democratizing software development and allowing teams to ship much faster, but this speed has come at a cost, as code quality is slipping. Many more developers, and even non-developers, are now generating and deploying code without always following best practices, proper performance checks, or security standards. This has resulted in a wave of buggy, fragile, and exploitable code making it into production. We predict that, as a result, we will see more vulnerabilities, production glitches, and models learning badly from poor-quality code. To counter this, the industry will need smarter tools that spot and fix problematic AI-generated code, as well as disciplined human oversight, especially for critical systems.
APIs will evolve into ‘API + MCP’ as AI becomes core to software development
While APIs drove the last era of software, the next will be defined by their evolution alongside the Model Context Protocol (MCP). Because AI models rarely produce strictly deterministic outputs, the MCP essentially arms them with “tools,” like a calculator, that ensure both accuracy and safety. As AI agents and assistants are woven deeper into business processes, endpoints that combine APIs and MCP will become the new standard, enhancing and eventually reshaping the traditional API layer. Although it’s still early to expose MCP broadly in infrastructure or Kubernetes environments, we do expect rapid uptake. In the long term, software will run on APIs that natively support predictable, safe collaboration with AI.
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ABOUT THE AUTHOR
Piotr Zaniewski is the Head of Engineering Enablement at vCluster Labs. He is a veteran software architect, engineering manager, and platform engineer with over 15 years of experience mastering software engineering, cloud solutions, and leadership roles. Piotr excels at architecting and implementing cloud-native technologies; leveraging tools like Kubernetes, Docker, Terraform and Crossplane to empower business operations and drive successful digital transformation initiatives. He is also a regular speaker and thought leader, and the founder of cloudrumble.net. Piotr holds a degree in IT and Economics from the University of Finance and Management in Bialystok, and a Master’s in Management Psychology and Finance and Management from Kardynal Stefan Wyszynski University.
