Today CloudPhysics released its intelligent IT operations management service for VMware workloads, after a highly successful beta with more than 500 enterprises worldwide. Leveraging the power of Big Data, the transformative new cloud-based service uncovers hidden operational hazards before problems emerge and identifies radical efficiency improvements in storage, compute and networking, giving IT more power than ever before to understand, troubleshoot and optimize their virtualized systems.
Overview of Cloud Physics
CloudPhysics is uniquely positioned to solve operations management problems because of the collective intelligence it derives from analyzing the world’s IT operations data combined with its unique, patent-pending data center smart modeling and simulation techniques.
Available as a SaaS offering, CloudPhysics specific capabilities include:
- Health Checks – Continuous checks for operational hazards cover best practices from vendors and field knowledge from CloudPhysics’ community of sysadmins personalized to the individual environment.
- Reporting – Interactive queries to find VMware insights, without requiring scripting or knowledge of schemas. Users can pull pre-built reports shared by community members or build unique ones and share with community members and colleagues.
- Analysis – Big data driven analytics for storage, compute and other systems to identify radical efficiency improvements for VMware.
- Planning – Simulation of planned purchases or configuration changes before rolling out in production
Customers can use CloudPhysics to identify and troubleshoot hundreds of operational issues by accessing focused operational analytics — referred to as “Cards” — available on the CloudPhysics SaaS platform. Some common use cases and Cards include:
- SSD Caching Simulation: Predict the latency benefit of IO caching and determines optimal cache sizing to balance cost and performance. Customers run this analysis first before hardware purchases to avoid wasteful procurement while dramatically improving the performance of business critical applications.
- Knowledge Network: A proactive, early warning service for the IT operator to identify operational hazards before they emerge. Uses collective intelligence to check the enterprise data center configuration against a live database of field issues, including firmware bugs, hardware incompatibilities and more.
- Storage Thin Provisioning Advisor: Reclaim expensive SAN/NAS disk space from virtual machines and data stores to reallocate for new workloads.
- High Availability (HA) Simulation: Analyze HA configuration changes before committing them into production. Customers optimize resource settings while ensuring critical VMs are protected against server failures.
What’s Really Different about CloudPhysics?
There are a lot of vendors whose products collect data from your vSphere environment and that want to tell you when something is abnormal and what to do about it. CloudPhysics is unique with respect to all of these vendors in the following respects:
- CloudPhysics is founded and staffed by some very senior and very experienced ex-VMware and ex-Google people. The people that wrote Storage DRS for VMware now work for CloudPhysics. The Chief Performance Scientist for Google now works for CloudPhysics.
- CloudPhysics is a SaaS based Operations Management Service. That means that you do not have to install one or many databases in your environment to have Operations Management and monitoring.
- With CloudPhysics, your data goes over the Internet to their back end which means that you need to be comfortable with their security and their anonymization polices.
- If you can get over the idea that your data is analyzed in an anonymous manner you will benefit from insights gleaned from not just you but every CloudPhysics customer.
- The analogy is this. If you are willing to let Google know where your start your journey and where your journey ends, then Google (and Waze) can use analytics based upon everyone else in a similar situation to shorten your travel time. Did your home address get disclosed to anyone? No. Did your destination get disclosed to anyone? No. But your route (analogous to your IT environment) does get compared to everyone who had a similar situation to you.
- Both VMware and Netuitive have very sophisticated self-learning analytical models which learn “normal” and alert you automatically as to deviations from normal. The analytics at CloudPhysics are different. CloudPhysics analytics are focused not upon learning what is normal at any one customer, but instead focused upon learning what is normal across all customers (currently all VMware vSphere customers running their data collection appliance).
- Most importantly, the strategy of CloudPhysics is to use their analytics not just to tell you when a number is out of bounds (leaving you to figure out why), but rather to give you advice that you can immediately act on in order to improve the operational efficiency of your environment.
- CloudPhysic’s investor is Kleiner-Perkins the venture capital firm that was also an investor in Facebook, Google, Intuit, Juniper, Intel, Sun, Symantec, Tivoli, and Versign among hundreds of other successful investments.
Links to Cloud Physics Press Releases
Other Posts Where We Have Explained the Potential Role of CloudPhysics
The Big Data Back End for the SDDC Management Stack – Discusses the need for a multi-vendor big data back end to manage the SDDC.
SDDC Operations Management – Discusses the need for a new approach to Operations Management for the SDDC.
Software Defined Data Center Analytics – Discusses the importance of analytics in managing the SDDC.
Best of Breed SDDC Management Stack – Discusses which vendors comprise best of breed solutions for managing the SDDC.
The New Management Platforms for the SDDC Management Stack and the Cloud – Discusses the need for a multi-vendor platform to replace legacy management frameworks.
CloudPhysics has launched the first production release of its intelligent Operations Management solution – a SaaS based offerings that uses analytics to derive actionable insights from cross-customer data.
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