Large-scale applications can balance risk and cost by spanning multiple different clouds, and blend in cloud-provider-specific tools such as data lakes and edge compute. Deepfence supports all major cloud providers, and can discover, visualize, and secure applications across one or many.
ThreatMapper uses a separate, sandboxed console that receives and processes application manifests and runtime telemetry from local, co-located, and remote production environments. As you scale and grow your deployment, Deepfence solutions grow seamlessly with you.
ThreatMapper automatically discovers, scans, and analyzes workloads, whether they are serverless, pod, container, virtual machine, or even bare metal. Automated compliance checks are tuned for each deployment platform type, using industry and community-developed benchmarks to verify compliance with good security practices.
Amazon ECS and AWS Fargate, Google Kubernetes Engine (GKE), Azure Kubernetes Service (AKS) – if it looks like Kubernetes or it runs containers, it’s supported by Deepfence. Whatever your deployment platform, Deepfence ThreatMapper and ThreatStryker are tuned to seek out vulnerabilities, assess threats, and secure your applications from exploit and lateral spread.
Deepfence’s lightweight, container-based architecture applies equally well to virtual machines and even bare metal workloads. All it takes is a local Docker runtime and the Deepfence agent can gather vulnerability data and install lightweight sensors for telemetry. Support legacy and modern workloads with one consistent solution.
When organizations make a multi-cloud strategy decision, they may do so on grounds of cost, business expansion, availability of advanced features, or to share the risk across platforms. A multi-cloud strategy creates a more distributed attack surface, and Deepfence solutions give a unified perspective on threats, attack surface, and security activity.