“Executives estimate that at least 30 percent of their cloud spending is wasted.”
-Forbes / State of the Cloud Report 2020
Djuno solutions are based on 3 key elements
- Machine learning to generate predictions of infrastructure utilization and detect infrastructure and code anomalies.
- Automation of the ongoing predictive cost analysis and recommendations.
- Price discovery with live price comparison to find the best alternative solutions, providers and prices.
Dashboards and APIs
- Past and predicted utilization
- Past and predicted costs
- Cost savings recommendation
- Technology and platform agnostic
- Works with all public clouds and
- Any on-prem and hybrid IT infrastructure
- Over-usage charges
- Redundant resources
- Underutilized infrastructure
- Reactive scaling and orchestration
- Optimized baseline
- Lower or no over-usage charges
- Optimized recourses, services, and pricing
- Pro-active scaling and orchestration
Our services include the following steps
We gather data about current infrastructure utilization and pricing
Our machine learning models predict future usage and costs
We present recommendations about IT architecture, services, providers, and billing options.
Our software continuously monitors utilization and prices to inform cost management decisions.
- Cost reduction, 30% on average.
- Performance, pro-active orchestration, efficient architecture.
- Peace of mind, continuous monitoring and cost comparison.
- Convenience, automation, integrated reporting, observability.
We’re a team of seasoned business and IT professionals with deep experience in machine learning and cloud computing.
- No risk. 100% satisfaction and no questions asked money back guarantee.
- Fast ROI. You’ll start seeing results from the next billing cycle.
- Transparency. You own all the data, research, and recommendations.
- We’re independent, technology, and vendor agnostic. We only work for our clients, not a big cloud provider.
- Proprietary technology including machine learning algorithms, pricing models, and ultra-efficient monitoring modules.