From manual to modern cloud

When “cloud” still means tickets

Many enterprises believe they’ve modernized simply by moving to the cloud. But once LAB³ steps in, a different picture emerges. Provisioning usually still runs through long ticket queues. Secrets are stored and rotated manually. Networking changes also require manual intervention. What should be a minutes-long workflow stretches into weeks, a bottleneck Lachlan White, LAB³’s Chief Technology Officer, describes as “fake speed to market.”

“We see a trend where there’s a lot of manual, risk-averse processes driving decisions. Specifically, people holding onto control rather than letting go. That really lets people fall into a bit of a fake speed to market with cloud,” explains White.

The root problem isn’t the cloud itself, but the lack of shared patterns. Without consistent foundations for infrastructure as code (IaC), teams reinvent architectures on every project, creating drift and uneven security.

As AI, microservices, and event-driven systems appear, the cracks become even more apparent. Organizations want to operate at cloud speed, but their processes can’t keep pace.

The crawl, walk, run model of transformation

Once LAB³ uncovers the operational drag holding teams back, the next step is rebuilding the path forward. Many organizations believe they’ve modernized because provisioning time has dropped, but the underlying manual processes often remain unchanged.

“If it took six weeks to build a server originally, and in the cloud, it takes three weeks, that’s good. But we know it can take three minutes,” says White.

LAB³’s crawl, walk, run model is designed to close this gap by providing enterprises with a structured way to overcome manual bottlenecks and move toward true cloud velocity. In the crawl stage, LAB³ stabilizes the basics: introducing shared patterns, defining architectural standards, and teaching teams how to use Terraform and Vault effectively.

Once standardized IaC is introduced, the results are pretty staggering: Clients typically reduce VM prework from approximately two weeks to just hours.

Reaching the walk stage marks a turning point in a client’s modernization journey. LAB³ helps shift the organization from ad hoc practices to a unified, scalable operating model where standardization becomes the catalyst for real velocity.

“The walk phase is really about making it efficient rather than just doing it because we’ve been told it’s a good practice to do,” adds White. With Terraform’s reusable templates and well-architected modules, the team can establish a consistent infrastructure foundation, eliminating one-off builds and reducing drift. Vault brings structure to secrets management, embedding rotation and access controls into the development workflow. And Consul begins to streamline connectivity by aligning networking practices with the broader platform strategy.

Together, these capabilities significantly reduce the client’s timeto-market and speed provisioning by 70%. By the run stage, LAB³ layers in platform engineering practices, FinOps feedback loops, and more advanced Vault and Consul capabilities to strengthen connectivity, governance, and automation. Or, as White put it, the team starts looking at “what’s the art of the possible?”

Building what’s next

As emerging technologies accelerate, from AI and agentic systems to microservices, event-driven workloads, and even quantum computing, the challenge is no longer about whether organizations can adopt new tools, but whether their platforms can support them safely and at scale.

White sees this shift clearly: “AI dramatically increases the speed of change and the surface area of access across modern platforms. As agents, pipelines, and services are introduced at pace, non-human identity becomes the dominant security challenge. Vault enables workload-based authentication and short-lived credentials, giving teams the freedom to adopt new tools quickly without relying on long-lived shared secrets.”

Looking ahead, LAB³ plans to bring more intelligence into the platform itself, using AI to automate Terraform workflows, predict configuration drift, strengthen security signals, and guide developers directly in their environments. And HashiCorp remains central to that vision.