We are excited to announce CloudWisdom, a SaaS platform that reduces the cost and risk of operating public cloud infrastructure for enterprise businesses. CloudWisdom optimizes public cloud computing and capacity by recommending configurations unique to your application workloads using machine learning algorithms. This enables our customers to avoid performance bottlenecks and financial waste commonly associated with environments hosted in the public cloud.
I’ve provided a few examples below of our product features along with screenshots to help explain some of CloudWisdom’s functionalities.
To reduce the risk of workload management, Cloud Wisdom applies analytics to measure historical workload patterns and calculate the exact resource requirements in the various dimensions of CPU, memory, I/O, network and disk usage. It then automatically formulates specific recommendations for each instance. The diagram below shows the top 10 recommendations for reducing cost while increasing resource utilization within safe levels. This tool also allows users to apply additional customized constraints to control the outcome of the recommendations.
Cloud Wisdom leverages self-learning anomaly detection and pre-configured alerting policies to identify capacity bottlenecks, notifying administrators in real-time to avoid the risk of end-user impact. Unexpected capacity bottlenecks may happen because of a sudden change in application work, a fail-over, or an intended or unintended change in infrastructure configuration.
A successful plan for cost reduction must include a capability to detect sudden increases in daily spend to avoid an end-of-month surprise. CloudWisdom automates the process of comparing cloud spending over time by correlating real-time data collected via APIs with detailed billing logs. The cost data can be grouped by meta-data such as attributes and tags, including related charges like data transfer and storage usage—all at an instance-level. Finally, it can account for the amortization of upfront spending commitments made to cloud providers that must be allocated to an individual instance based on usage. The result is a comprehensive yet simple report that can be set up once and regularly emailed to all stakeholders.
This past August, we announced the merger of Metricly and Virtual Instruments. This merger was especially exciting because both companies aspired to transform performance, capacity, and cost management using advanced analytics. Metricly had created a cloud-native tool, designed from the ground-up, that tackled managing public cloud computing resources; Virtual Instruments led the market in managing enterprise private cloud platforms, touting industry-leading technologies such as recording every data read-write on storage systems that last only microseconds.
Our combined company is now known as Virtana, which ushers in an exciting new era in hybrid cloud management. Virtana has become the most comprehensive and in-depth workload management solution, spanning both private and public clouds, offered by a single vendor.
Why is hybrid cloud management so important?
Goldman Sachs’ Cloud Quarterly report estimates that the public cloud represented 7% of the $612B spent on enterprise IT infrastructure in 2018, growing to 9% of the $633B market in 2019. This makes for a giant market in need of hybrid cloud management. For many years to come, enterprises will continue to migrate more and more to the public cloud. But some workloads will always remain candidates for running in local data centers—due to usage patterns, data storage, or security requirements.
Stay tuned for our upcoming product feature announcements! We love closely collaborating with our customers to develop innovative and frictionless approaches for automating the analysis and management of hybrid workloads.
Metricly coaches users throughout their cloud journey to organize, plan, analyze, and optimize their public cloud resources.Try Metricly Free