Funding
Funding not disclosed

Founders
Product
Problem
Traditional cloud computing models often struggle to efficiently manage resources in geographically distributed environments, leading to increased latency, bandwidth limitations, and challenges in data privacy and security, especially with the rise of IoT devices generating data at the edge. Existing cloud technologies lack the ability to handle decentralized infrastructures effectively.
Solution
FogAtlas is a software framework designed to orchestrate cloud-native applications across multi-tier, distributed, and decentralized cloud computing environments, embracing the Fog Computing paradigm. Built on Kubernetes, Ansible, Prometheus, and Grafana, FogAtlas extends Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) capabilities by incorporating "locality" to optimize resource utilization and workload placement. The platform facilitates service-aware workload placement and zero-touch deployment, enabling efficient management of resources closer to data sources and users. By distributing computational resources to the edge, FogAtlas minimizes network delays, optimizes bandwidth usage, enhances fault tolerance, and improves data privacy and security.
Target Audience
The primary users are infrastructure owners, such as cloud providers and sensor network owners, seeking to efficiently manage Fog Computing infrastructures, as well as developers of cloud-native applications aiming to leverage distributed services close to data sources.
Features
- Manages geographically distributed and decentralized cloud computing infrastructures.
- Provides service-aware workload placement and zero-touch deployment.
- Built on Kubernetes, Ansible, Prometheus, and Grafana.
- Facilitates the setup, monitoring, operations, and fleet management of multi-tier, distributed cloud infrastructures.
- Enables zero-touch deployment and orchestration of containerized applications.
- Supports resource allocation and workload placement based on location, network characteristics, and computational profiles.
- Offers a placement algorithm that computes the placement of microservices according to objective functions and imposed constraints.
- Includes a scheduler plugin that influences Kubernetes placement by adding scores obtained from the placement algorithm.
- Provides a monitoring chain based on Prometheus for collecting and evaluating metrics against defined thresholds.