Empower Engineers with an
AI Driven Approach to
Resource Control
The #1 Kubernetes and Cloud Resource Control Engine
Full-Stack K8s Resource Optimization From Container to Node to Scale Group
Cut costs while improving performance, elasticity & uptime.
Ask us how SRE’s, DevOps & Platform Owners at these enterprises are succeeding with Densify
Ask us how SRE’s, DevOps & Platform Owners at these enterprises are succeeding with Densify
Deep Analysis of Containers, Pods, ReplicaSets & Deployments
- At-a-glance view of the cost and risk for clusters, namespaces, services and even your entire K8S estate
- Rapidly identify savings opportunities, OOM risks, memory limit issues and other critical situations
Histograms: visualization of container environment
Broad Platform Support
Manage resources across Kubernetes, Red Hat OpenShift, Rancher RKE, EKS, AKS and GKE for all your clusters, namespaces and individual containers.
Densify automatically analyzes thousands of containers to determine optimal settings
Precise, Automated Recommendations to Optimize Requests & Limits
- Precise recommendations and predictive analysis based on deep policy and AI learning models
- Container, pod, ReplicaSet and deployment analysis using advanced QoS modeling
- Visibility into learning models, policies and raw metrics to provide critical detail and evidence for app owners
See the Benefits of Optimized KUBERNETES Resources
Denisfy is AI-driven analytics that precisely determine optimal resource settings for Kubernetes
Integrated, Automated Node Group Optimization
- Automated Cloud Scale Group optimization based on cross-catalog workload simulations
- Automatically recommends optimal instance type and scaling parameters based on utilization and container requests
- Leverages Densify’s industry-leading Cloud Resource Optimization
AWS ASG optimization analysis
CUSTOMER STORY
Raffeisen shares OpenShift optimization with Jenkins CI/CD. Watch how Raiffeisen Bank saves 50% on the frequency of resource expansions, an overall reduction in resources required, and the alleviation of the risk of instability caused by container memory shortages.
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