Cloud drives laboratory research


With demand for remote working and easy access to data at an all time high, it is not surprising that

cloud technology is rising to meet the demands of laboratory scientists. Cloud and software as a service (SaaS) deployments reduce overheads and infrastructure while supporting scientists’ access to data anywhere in the world. LIMS and ELN systems are increasingly

deployed in the cloud to provide flexibility, added security and reduced costs. The advent of cloud-based systems and SaaS platforms are changing the way that laboratory management software is implemented. For many users, cloud and SaaS

deployment models provide a platform that can support today’s workflows, while also offering the scalability needed for customers who are looking to use their data for machine learning (ML) and artificial intelligence (AI) workflows. These models deliver a software stack that can help reduce costs and increase productivity in the laboratory by facilitating access to data and making it easier for users to collaborate. Sharon Williams, product director at

Interactive Software, comments: ‘I think the biggest difference is, from a cloud perspective, whether that’s private cloud or public cloud, is the infrastructure is already in place. Williams gave an example of a recent

customer installation where they wanted a Covid-19 testing system up running. ‘For them and for us, having that cloud infrastructure that you could just spin up at a moment’s notice, meant that we didn’t have all of the headaches that sometimes arise with the IT team. Paul Ward technical director at

Interactive Software added: ‘Traditionally applications, whether they are old legacy

32 Scientific Computing World Summer 2021

client server apps, or web-based apps, have been on-premises applications. But with that there’s a lot of ownership that goes along with not only running and maintaining the application, but it’s actually the infrastructure to support that application. This includes networking, server resources, storage, backups, access, security, and so on.

Infrastructure costs With a managed cloud-based model, ownership of the underlying server network backups and so on is passed on to someone so that the users of the application can concentrate on using the application, and doing what they need to do on a day to day basis as part of their role. ‘Scientists do not have to worry about the application. Is the service backed up? Are there enough resources? Is the service available, who’s accessing it, who’s not accessing it, and the security side of things,’ added Ward. ‘You no longer have to maintain the

infrastructure and those applications and services on premise. Again, it’s going back to passing some of the responsibility and the ownership back to the cloud provider and the application provider as well,’ Ward concluded. While there is a cost associated with

cloud software, in many cases, the cost of the platform can actually be cheaper than an in-house alternative due to the additional costs of supporting the underlying infrastructure that supports in-house deployments. Particularly for new

or smaller businesses, cloud can help save costs and allow the organisation to scale up faster than would traditionally have been possible without considerable costs. ‘If you’re thinking just from a licensing

perspective then it may seem quite expensive if you want to run it in the cloud,’ said Ward. ‘It depends on the licensing model, but it may be named users, for example, rather than current users if it was on premise. But you have to consider what you’re saving from an infrastructure perspective, and the management of that infrastructure to support that underlying application.’ ‘That’s the time required to provision

the infrastructure in the first place and to maintain that on an ongoing basis. And then the other software and services that need to run on that infrastructure as well to make sure it’s secure and available and accessible by all the users,’ Ward added. Cloud can also accelerate the time

to results for scientific organisations by giving scientists and researchers access and the freedom to conduct their experiments within the confines of a configurable platform. This means if a scientist needs to make small changes they can do so without having to consult IT and wait for this change to be completed. ‘Purely from the scientist’s perspective, I was going to talk about the speed in which they can do things without having to go back to the IT team all the time,’ noted Williams. ‘There’s an element of that which is dependent on the configuration available, how configurable the application

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