TriggerMesh raised $3 million in seed funding to back its plans of building a cloud native integration platform. The company has been working toward that goal since it burst onto the scene in late 2018 focused on a serverless management platform that runs on top of the Kubernetes-based Knative platform.

Mark Hinkle, co-founder of TriggerMesh, told SDxCentral that the company plans to use the investment to accelerate development by building an international team, including adding developers in Germany, India, and Spain. The company has mostly been running with a lean team bolstered by developers under contract. 

TriggerMesh's platform allows developers to automate the deployment and management of serverless and functions-as-a-service (FaaS) across different cloud platforms. This allows users to incorporate virtually any source into the platform to trigger functions across serverless platforms like Amazon Web Services' (AWS) Lambda, Microsoft Azure Function, Google Cloud Functions, or Knative.

“The future isn’t necessarily limited to serverless or microservices or even a single cloud," Hinkle noted in a blog post tied to the funding news. "The real need is for integration between cloud services. This has informed our decision to focus on building a cloud native integration platform."

Hinkle added that he expects TriggerMesh’s product to continue serving in this capacity as a direct-to-end-user developer integration, which he said, begins with making the initial experience more intuitive and easier to use. 

Last fall, TriggerMesh launched its EveryBridge platform that targets the still challenging task of triggering serverless-based events that can run across multiple clouds and on-premises infrastructure. The TriggerMesh bridge is in the form of its Knative Lamdba Runtime (KLR, which is pronounced “clear”) project to provide portability of AWS Lambda functions to Knative-enabled clusters and serverless cloud infrastructure without needing to rewrite the serverless functions.

That launch followed up on AWS' unveiling of its EventBridge platform that is a serverless event bus that allows users to connect applications together using data from their own applications, software-as-a-service (SaaS) applications, and AWS services.

"I think Amazon EventBridge shows us there's a real need for these kinds of solutions. The problem is it's specific only to Amazon,” Hinkle said, adding that it ties developers that use Lambda-based serverless functions to AWS. This model is also used by other large cloud providers and their respective hosted serverless platforms.

TriggerMesh does not currently offer a product that is officially termed enterprise ready, though Hinkle said the company itself is very confident in the robustness of its platform. He made a distinction between the point where new technology is good enough to be deployed in the enterprise versus when it makes sense for users to update applications or add on new projects in order to adopt that technology.

“We feel like the technology is ready but there’s more features to make it more broadly attractive, and that's what we're doing with the money,” Hinkle said. “I think we often get caught up in the hype, whether it's Kubernetes or Docker, it's just a matter of not everyone's future comes at the same time. We want to be the event fabric for cloud native infrastructure wherever it lives in whatever technology is out there.”

TriggerMesh does have a long-standing relationship with GitLab. The DevOps platform provider tapped TriggerMesh to power its GitLab Serverless platform that allows users to run serverless workloads on Kubernetes as part of GitLab’s single application for the entire DevOps lifecycle. Hinkle said that the partnership has provided TriggerMesh with insight into what’s missing in the community and exposes the company to different kinds of users. 

The company will be rolling out a preview release of its EveryBridge platform in March that will include more features, namely user-friendly interfaces, with plans to release additional features over the course of year based on user feedback.