Loft
VerifiedDate | Investors | Amount | Round |
---|---|---|---|
N/A | $0.0 | round | |
investor investor investor investor investor | $0.0 | round | |
* | $24.0m | Series A | |
Total Funding | 000k |
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EditLoft.sh is a tech startup that provides a platform for teams to build on Kubernetes, a popular open-source system for automating deployment, scaling, and management of containerized applications. The company's primary offering is a production-grade, multi-tenant Kubernetes platform with virtual clusters. These virtual clusters offer strong isolation for tenants, allowing multiple users to share a single Kubernetes cluster without interfering with each other's work.
Loft's platform is designed to be user-friendly and efficient. It can be adopted within days and offers a customizable user interface that can be branded according to the client's corporate design. The platform supports the same Kubernetes API and kubectl CLI that developers are already familiar with, and it can be used with any GitOps tooling.
Loft's business model is based on providing a service that reduces management overhead and costs for its clients. By allowing clients to spin up lightweight virtual clusters as needed, Loft helps them save on resources. The company's platform is also designed for high availability to prevent a single point of failure and supports air-gapped and VPC deployments for enterprise-grade security.
Loft operates in the cloud computing market, serving clients who need to develop against Kubernetes as a deployment target. Its clients range from small teams to large enterprises that require a reliable and efficient platform for building on Kubernetes.
In terms of revenue generation, while the specifics are not publicly available, it is likely that Loft operates on a subscription-based model, charging clients for access to its platform and services.
Keywords: Kubernetes, Virtual Clusters, Cloud Computing, Multi-Tenant Platform, User-Friendly Interface, Cost-Effective, High Availability, Enterprise-Grade Deployments, Subscription-Based Model, Efficient Resource Management.