Although businesses are increasingly using cloud computing for engineering simulation, many misconceptions still surround cloud-based simulation.
This post debunks the leading misconceptions about cloud computing, and, in doing so, will assist engineering and IT managers, as well as directors, as they make decisions regarding computing resources. While dispelling these misconceptions, I will share resources and provide insight to help organizations steer around possible failure points as they consider cloud computing.
1 – On-the-Cloud Simulation is Less Secure Than On-Premise
Cloud computing still suffers from a perception problem when it comes to security. There is, perhaps, a natural inclination to believe that things outside of our own control are inherently less secure. The reality is that the cloud in and of itself is no more or less secure than other models. It depends on the measures organizations and providers take to secure the data. It is clear that if policies and procedures aren’t robust, then data will be vulnerable wherever it is hosted, on-premise or in the cloud.
I would contend that many cloud providers likely have better security than most organizations because of the economies of scale of their business. Moreover, it is common practice that cloud service providers hire the world’s best talent as they focus on security as a core part of their business. In addition to other security methods, Amazon Web Services (AWS), for example, provides a complete set of network security, encryption, identity and compliance tools, as well as over 50 global assurance programs to ensure sensitive workloads can operate on AWS in compliance with relevant laws and regulations.
To learn more, download this white paper describing the well-known triad of confidentiality, integrity and availability (CIA). Or watch this webinar and hear how ANSYS leverages AWS to provide secure engineering workflows in the cloud.
2 – Managing Simulation Jobs and Data in the Cloud is Difficult
This myth relates to a key concern that you may have when thinking about cloud computing: will we lose productivity when we have to manage our simulation jobs and data remotely (in the cloud)? You want simple, intuitive job submission procedures, tuned to the requirements of the specific applications that you are using. You want to monitor jobs in progress, and you need ways to find, retrieve and reuse simulation data. Our best cloud-hosting partners have created web/user interfaces that enable these capabilities.
Our own web-based interface, ANSYS Cloud GatewayTM , manages the end-to-end simulation process, including high performance interactive processes and graphics, combined with auto-scaling high performance computing and cloud-based data management. Because all ANSYS software applications and data are hosted on the (AWS) cloud, data is searchable, reusable, and shareable, which will improve collaboration among geographically distributed teams. Using just a web browser, you can access your applications and data in the cloud, from any location, on any device. In addition to increasing your mobility, you can reduce your spending on high-end desktop workstations.
3 – The Cloud Should Be Used for Every Simulation Project
Nobody expects simulation to move entirely to the cloud all at once. To get started I would recommend that you consider a significant project that is not well-served by in-house infrastructure and tackle that project in the cloud. This is particularly true when companies have already significantly invested in on-premise computing resources (while technology startups have a unique opportunity to be “born in the cloud” for simulation).
In general, the more successful cloud projects will benefit from a step-by-step approach to their adoption. Most companies are likely to reach a hybrid cloud model in the long run with a mix across private, managed and public cloud sourcing that will evolve over time. That is why starting with a holistic view covering all of the different options makes sense.
ANSYS helps customers gain clarity on cloud solutions, identify the various cloud options that can work for their engineering simulation activities and subsequently draw actionable steps.
4 – Public Cloud Cannot Meet My Enterprise Requirements
When you are deploying ANSYS at an enterprise level, you (or your IT colleagues) may be looking to make simulation assets – hardware and software – available consistently across the globe. To maintain separate deployments in each office that require access to the same tools can be increasingly inefficient as the scale of use and scale of HPC increases.
So consolidation, or moving simulation from the department to the data center, can be considered as a paradigm shift with much appeal. Add to that the desire for business agility, with simulation assets that scale up and down as needed, our ANSYS Enterprise Cloud makes a lot of sense to these global enterprises.
5 – Cloud Computing Will Make Our IT Colleagues Redundant
Most experts believe that the hype surrounding the impact of cloud computing on IT resources can be easily dispelled. I personally think that that the job description and the value of your IT colleagues will evolve from “service provisioning” to “service monitoring.” I am confident that cloud computing won’t replace your IT team. It will, instead, allow them to bring their unique IT skillsets to help, for example, with monitoring the security and usage of the cloud-based infrastructure, and optimizing cloud-based resource usage.
With ANSYS Enterprise Cloud, our customers usually stay responsible for IT management of the cloud environment just as if it were an on-premise deployment. They also take care of the day-to-day monitoring and maintenance of the systems, resolving issues that might arise. They also manage user access and overall account spending.
6 – If We Don’t Save Money, Cloud Computing Isn’t a Viable Option
Cost savings can definitely be achieved by using cloud computing, but they are not always easily quantifiable. I often hear customers saying that the decision to migrate to the cloud will be dependent on the total cost of ownership (TCO). However, doing an accurate TCO calculation for both cloud and on-premise HPC resources isn’t an easy task to begin with. For example, how do you accurately assess the (almost hidden) costs of longer queue times and delayed projects due to insufficient computing capacity within your fixed infrastructure?
More importantly, I think that you should refrain from a one-by-one comparison between an on-premise server and a cloud-based server. After all, you can re-configure cloud resources whenever you want, and scale whenever you need to, paying only for what you need. With cloud computing, you will no longer be constrained by computing power, so you can perform more and higher-fidelity simulations, resulting in better products getting to market faster. With cloud you can increase your simulation throughput because it is regularly upgraded to the latest generation of fast and efficient computing.
Although there are many ways to explain the value of cloud, basically it improves agility, flexibility and speed to innovation. Unfortunately, all of this, as well as the ability to do things that were not possible before, are often difficult to quantify.
My advice therefore, would be to look beyond potential cost saving benefits and rephrase your question from, “will cloud computing will save us money?” to, “what value does it create for our organization?” To help you answer that question, I’d recommend you read our recent blog post Cloud Offers Much More Than Unlimited Computing Power.
7 -ISV Licensing is Inappropriate for Cloud Computing
I sometimes hear that independent software vendors (ISVs) are reluctant to evolve their business or licensing models for cloud computing. For ISVs in general, IDC Research, Inc. predicts that they will offer some kind of usage-based pricing models for the majority of their apps in the coming years.
We offer ANSYS Elastic Licensing, a pay-per-use licensing model that unlocks virtually every ANSYS product that is supported on cloud-hosting partner hardware and on AWS infrastructure (through our Enterprise Cloud solution). Customers can also use their existing lease or paid-up licenses on the cloud. You can read more about this here.
8 – Cloud Computing is One-Size-Fits-All
On one hand, there are customers working on, or interested in, different HPC and cloud infrastructure, from desktop or workstation-based computing, to private or enterprise HPC-based, to hosted cloud and public cloud. 
On the other hand, customers clearly have different requirements and practices for their engineering simulation, from HPC scale-up and software utilization optimization, to job scheduling, to a need for more collaboration across geographically distributed teams, or to satisfy mobility requirements.
Therefore, ANSYS has adopted an Open Cloud StrategyTM that is:
- Open to multiple cloud platform and vendors, from an ecosystem of ANSYS partners. To learn more, watch our on-demand webinar series showcasing cloud-hosting partner solutions.
- Open to multiple cloud solution types, from cloud hosting services, internal private clouds to virtual private cloud on the public cloud. To learn more, watch our webcast HPC from Desktop to Cloud.
- Open to multiple business models on the cloud, from traditional lease/paid-up to pay-per-use licensing. To learn more, watch our webcast Pay-per-Use Licensing for Cloud Computing.
I hope that this post has given you some solid reasons to consider the use of cloud computing for engineering simulation. Please feel free to comment or tell me about other concerns you might have, and I’ll be happy to address them.
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