"Omnistrate gave us an enterprise-grade control plane without the need to hire or build one in-house. With their decade of expertise baked in, we launched faster, cut costs, and focused on growing our business from day one. Highly recommended for any team building a managed SaaS." - Peter Farkas - Co-Founder & CEO Ferret DB

Bringing software to the cloud is only half the challenge—proving it’s secure, compliant, and enterprise-ready is what unlocks adoption in regulated industries and large-scale procurement pipelines. That’s why we’re excited to announce our partnership with Brownstone Consulting, combining Omnistrate’s modern cloud automation platform with Brownstone’s compliance and security expertise.

Together, we offer software vendors and platform teams a faster, integrated path to launch and scale managed cloud services across AWS, Azure, GCP, or on-prem environments—with GDPR, NIST 800-53, SOC 2, ISO 27001, HIPAA, and FedRAMP compliance built in.

Over the past few weeks, I've been leading an initiative to integrate the Serverless Framework with our Omnistrate platform. Today, I'm excited to share the technical details of this integration and how it can help developers maintain their serverless applications while gaining enterprise SaaS capabilities.

Many B2B startups start their cloud journey with AWS ECS or GCP Cloud Run. It's understandable—they're familiar, quick to set up, and tightly integrated with the hyperscalers' ecosystems. Throw in some Terraform, and you have a hello-world deployment workflow that seems "good enough" to get your SaaS up and running.

But "good enough" quickly breaks down as you scale.

In previous posts, we explored BYOA deployments, AI job scheduling, and cost control and insights. In this blog, we focus on the performance accelerators and scalability layers Omnistrate offers out of the box—purpose-built for AI workloads that demand fast startup, efficient resource usage, and intelligent scaling.

Let’s dive into four features that can supercharge your AI deployment strategy.

In our previous blogs, we discussed two foundational pillars of AI infrastructure: BYOA (Bring Your Own Account) for secure, scalable deployments and Jobs Support for managing bursty and scheduled workloads.

Now, in Part 3, we’re diving into something that’s just as critical for AI workloads: cost controls and infrastructure insights. Because while scaling AI is powerful, scaling it without cost awareness is risky.

Omnistrate, the industry's first SaaS Control Plane as a Service, has launched a powerful new Jobs controller paradigm that enables businesses to efficiently manage and execute workloads across multiple environments. This feature extends Omnistrate's ability to transform cloud applications into enterprise-ready B2B SaaS services by providing robust job scheduling, resource optimization, and workload management capabilities.

“Security startups don’t have time or resources to reinvent cloud infrastructure. Omnistrate allowed us to run a scalable SaaS in weeks—not years—without experienced DevOps personnel on staff, so we could focus on what matters: securing our customers.” — Vinay Mamidi, CEO and Founder at Whiteswan Security"

One of the most common questions for any developer-focused product is whether to build or buy. At first glance, building in-house seems to offer full control and customization, at the cost of significant time, resources, and ongoing maintenance—often diverting engineers from core product innovation.

A while ago I wrote, why Terraform tool is not enough for SaaS here. Today, I am extending the same series for Helm -- covering the purpose they serve and why they are NOT enough to build your cloud offering or control plane.

Helm charts are widely used for Kubernetes application deployment, offering a templated approach to package and manage applications. However, when it comes to building a full-fledged SaaS control plane, relying solely on Helm is not enough.