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Engineering Spotlight: Turbonomic

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Launched in 2009, Turbonomic is one of the fastest-growing technology companies in the virtualization and cloud management industry. They work with companies to maintain their IT systems and keep them running smoothly. 

We connected with Danilo Florissi, (Co-Founder & SVP Engineering),  Giampiero DeCiantis (Senior Director, Product Management), Ariel Cohen-Tal, (Director, Ecosystem Engineering), and Sylvia Isler (SVP, Engineering) at Turbonomic to learn more about the company's engineering team, culture, the different technologies they get to use, and more. 

Also, Turbonomic is hiring! Visit their BIZZpage for the latest job opportunities and to learn more about what they do!

Quick Hit Details

  • Year Founded:  2009
  • Number of employees: 500
  • Number of engineers: 130
  • Industry: Software / Technology

Can you share a summary on what Turbonomic does?

Turbonomic helps customers automate their workloads (VMs and Applications, containers) on-premises and/or in a public cloud. It makes the right workload placement and scaling decisions at the right time, unleashing the full potential of hybrid cloud elasticity. That’s the what - but the how is even more interesting:

Common Data Model: Turbonomic abstracts workloads, compute, storage, network, fabric, etc. into a common vendor-agnostic data model, a market of buyers and sellers of resources.

Analytics—the Economic Scheduling Engine: This decision engine applies the principles of supply, demand, and price to the market. Entities price their resources based on utilization levels. As utilization of a resource increases so does the price. The analytics ensure the right resource decisions are made at the right time.

Mediation—Any Workload, Any Infrastructure: Turbonomic works for any workload on any infrastructure or cloud. The data center and cloud stack fundamentally operate as a supply chain of buyers and sellers. Applications get resources from VMs, which in turn get resources from hosts, storage, network, fabric, etc. Any new technology can be added to the stack through Turbonomic’s mediation component - and because of the common data model, the engineering cost to make such additions is relatively low.

Describe the Turbonomic 6.1 platform and what the key components are that are used to help customers manage workload?

Prior to the release of 6.1, our customers told us that they needed to bridge the gap between the static, manual operations and infrastructure of today and the automated, dynamic operations and infrastructure of tomorrow is a responsive, application-aware infrastructure that delivers application performance– on-prem, in the cloud, and on container platforms – while also optimizing costs and maintaining compliance with policy.  To that end 6.1 makes major contributions in three areas:

1st – Cloud. Can you imagine if there was a platform that could automatically maximize your AWS Reserved Instance utilization – with a holistic understanding of the best resizing actions to take for both cost and performance? We do that in 6.1 by providing  the ability Maximize AWS RI utilization – in concert with workload resizing Result: 33% Savings on AWS Bills by 6.1 adopters

2nd Application-Aware Infrastructure. And, what if your infrastructure actually KNEW about your applications – and knew exactly what resources it needed, and when? What if your infrastructure was intelligent enough to automatically resize itself, on demand, so that every application got just what it needed – no more, no less. The 6.1 release provides an Integration with Cisco AppDynamics Application Performance Management (APM) enables deep application understanding and trustworthy, application-aware sizing automation.

3rd Container Platforms. What if your container platform projects never had to run up significant cloud bills, or spiral into overwhelming management complexity on-premises? With the 6.1 release, our customers can automate and scale workloads in Kubernetes, Red Hat OpenShift, Pivotal Cloud Foundry.

What are some of the different technologies that the engineering team gets to work with and at what scale?

Our team gets to work with some of the latest technologies on the infrastructure side - both private and public cloud. These include AWS, MS Azure, ESX and HyperV, the latest data storage platforms (like Pure, ScaleIO, etc). In terms of the software stack, our engineers are exposed to and need to understand Kubernetes, Kafka, Lambdas, and other related microservices technologies. I should also mention that algorithms are big for us. So the technology between their ears is the most important technology of all.

What are some of the interesting projects that the engineering team is tackling?

Our team is working on evolving our platform from a monolithic architecture to a platform based on microservices. This effort has been compared to re-engineering a jet engine in flight. Nonetheless, the early version of the new platform has been released and the team continues to introduce some very cool new features to increase the platform's scalability and resilience. In addition to that, we are incubating several projects around managing Serverless and edge-computing.  

Does your engineering team have a chance to work on projects outside of their day-to-day responsibilities?  For example - skunk work projects, open source projects?

Yes, our team is actively contributing to several open-source projects including OpenStack and Kubernetes. In addition, we have a lively ecosystem of our own projects on GitHub. Click here to check us out on GitHub.

What is the culture like at Turbonomic for the engineering team?

Our engineering culture is one that is very collaborative and forward-thinking. Starting with our founders, who are still involved in the day-to-day activities, everyone gets open access and support from our founders and executives which leads to an environment of continuous learning. The engineering team has a rotational program where you can cycle through the various R&D teams to gain different perspective, skills and really drive your career in the direction you want. If you’re looking to be part of a culture of innovation, then Turbonomic is exactly what you’d want to check out.

What can a potential employee expect during the interview process?

Employees can expect a challenging but fun interview with Turbonomic. We typically ask them to solve some non-trivial coding and architecture problems. But we also ask them about their own aspirations, what sorts of team structures and projects they have worked on in the past and what types of problems they are interested in solving. We also provide lunch and snacks throughout the process. In addition, if they are interviewing on the right day, they’ll get treated to one of our company-wide lunch meetings - which are informative, fun and a great way to get a true feel of our company culture.

Are you involved in any local tech organizations or Meetups?

We’re involved in local Kubernetes (New York Kubernetes) and DevOps (Continuous Delivery NYC) Meetups. You can regularly find our engineers at those meet-ups among some others.

Rapid Fire Q&A 

What’s on tap?


Star Wars or Star Trek?

Star Wars

iPhone or Android?


Coffee - hot or iced?

Dare we say both? We keep both in our kitchen and both supplies burn down equally!

Favorite employee perk?

Thursday Yoga is becoming the favorite.

What TV show describes the engineering team’s culture?

The Big Bang Theory

What music is playing in your office?

Depends on the day and location. Ranges from 80s metal, to classical to R&B

View from your office:

Rooftop view at Turbonomic NYC
Rooftop view at Turbonomic's NYC office

A view of the office:

A view of the office at Turbonomic NYC
A view of the office floor at Turbonomic in NYC.

Team Profiles

Diampiero De Ciantis Turbonomic 
Diampiero De Ciantis
Director, Product Management at Turbonomic

Aditya Bhat, Engineering Manager at Turbonomic
Aditya Bhat
Engineering Manager at Turbonomic

Alyssa Oxner is a Customer Success Specialist at VentureFizz.  Follow her on Twitter: @Aoxner23.

About the

Turbonomic Application Resource Management matches application demand to infrastructure supply to continuously ensure application performance. 

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