The Solano Spotmark platform brings data-driven modeling to the planning and consumption of cloud services. Spotmark makes placement recommendations, finding the best provider, location, time of day, and hardware for your job.
With Solano Spotmark, take advantage of powerful data-driven modeling to optimize your spending on cloud infrastructure — including infrastructure in your own datacenters. Specify critical constraints such as budget, deadlines and regulatory location constraints with Spotmark’s API. Patented Solano Labs technology optimizes your workload to make optimal placement decisions for you so that your job runs on time and on budget. It can even help you identify the best hardware configurations at runtime — this flexibility offers you even faster turnaround times or lower cost.
Why “Spotmark?” Traders have long referred to “spot” markets for real-time trading of commodities. As cloud computing increasingly resembles a commodity utility, providers like Amazon and Google have begun to offer real-time pricing of spare cloud computing resources. In exchange for deep discounts, a cloud provider reserves the right to reclaim (or “kill”) an instance at any time. Solano Spotmark takes care of the additional work required to take advantage of these “spare cycles” — staying up to date with providers’ changes in infrastructure and pricing, optimizing bidding and pricing for the lowest cost for work performed, and providing infrastructure to automate restarting computations when instances are reclaimed.
Solano Spotmark can help you reduce you get the most out of your cloud spend:
- Compatible with Amazon Web Services, Google Cloud Platform, Microsoft Azure, and multiple on-premise cloud platforms
- Manage the cost of your batch and parallel cloud workloads — identify the best purchasing strategies and save 70-80%.
- Improve turnaround time for your existing test infrastructure, including Solano Private CI, Jenkins, or any other self-hosted platform.
- Leverage Solano Labs IP and expertise to integrate cloud cost and performance management into your existing and custom compute-intensive applications. Common applications include MapReduce (e.g. Hadoop and AWS EMR), large ETL jobs, and compute intensive workloads such as audio and video transcoding and EDA.
- Track and improve utilization of your existing cloud assets.
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