Cloud computing has become ubiquitous over the last ten years. Often, we barely even notice that we are using it to instantly move data and applications back and forth through the web. Like many workplaces, laboratories are increasingly looking to take advantage of cloud computing as a way to save time and resources, and as a cost-effective option to implement enterprise laboratory solutions.
By integrating cloud computing into all aspects of the scientific workflow, laboratories can harness the increased data security and improved performance delivered by the cloud. Cloud services enable laboratories to remotely access data, permitting scientists to view and process data sets outside the laboratory. A major benefit of cloud computing is that resources can be scaled-up or down, easily and quickly, meaning it can be applied to the small single-site laboratories with minimal or no IT support to multi-site, multi-lab global corporations.
But, how do laboratories integrate cloud systems into their pre-existing systems? Here, we discuss the challenges and benefits of operating in the cloud, focusing on how this model ensures data security and compliance, creating a flexible and scalable resource for all laboratories.
A nebular network of the Internet of Things (IoT)
Cloud computing is the delivery of on-demand computing resources over the Internet. Applications and data are hosted on centralized virtual servers in a cloud data center and accessed via an Internet connection. Usually, both the hardware and software required are delivered as small monthly payments, and only paying for what is used. Different pricing models allow you to make savings over on-demand services, and it is possible to commit to an amount of compute over one or three years and pay a portion of the costs or all the costs upfront maximizing savings.
Cloud computing has moved far beyond uploading photos and documents into storage systems and is more about connecting everyday objects into IoT. Smart fridges, analytical machines, thermostats and HVAC (heating, ventilation and air conditioning) systems; all are examples of instruments that are connected to the Internet for remote control and monitoring from personal computers or mobile applications, as well as data sharing and integration between equipment. All these components in the IoT generate vast amounts of data, which necessitates methods to store, process and access information more effectively. Cloud computing has the advantage of rapid access of this data from multiple access points, often including “on the go” apps from mobile devices.
Rainclouds ahead? Perceived challenges of cloud computing systems
Many companies experience or perceive challenges of using cloud systems, especially when they must be integrated into pre-existing systems that are already quite complex. On the one hand, there can be resistance to change from physical storage systems to cloud solutions due to certain perceived risks. The shift from moving from a private, on-site storage or server room to a public cloud, for example, can create concerns about data security. Many people perceive issues around data being lost in the cloud in servers that are not under direct control of the company and where it is vulnerable to hackers. This is especially true in GxP regulated environments, where data governance and integrity are critical to compliance. There can also be confusion about who is responsible (the customer, cloud provider, software provider) for security.
On the other hand, there are technical or logistical barriers of adopting cloud-based systems. Often, these issues are specific for the size of the companies. For example, small companies may feel they have a lack of expertise when it comes to setting up, operating and managing applications in the cloud. Larger companies might already have some experiences with cloud systems, but worry about compliance with data storage regulations, especially when patient data and intellectual property is involved. Another perceived barrier to cloud computing is cost management. The cloud can be cheaper than running on-premise infrastructure and applications, but it takes careful management and monitoring to ensure operational costs are optimized.
The security and flexibility of cloud computing systems
Modern cloud service providers are well aware of the challenges and resistances that customers often face and have been working hard to address customer needs. This includes addressing misconceptions, particularly around data security. One worry is that as soon as the term “public cloud” is mentioned, the association is that their data will be stored alongside all other users in the cloud service. However, that is not how the cloud works. Cloud architecture provides organizations with a virtual private cloud (VPC) which keeps data and users separate. Moreover, customers have full control over who has access to their cloud. The use of virtual private network (VPN) gives encrypted links between the customer and the cloud, securing the data in transit. Authorized users can access the cloud off-site via a VPN and app services, they are able to work anywhere via smartphones, tablets, and laptops, as long as they have an Internet connection. This has become even more important as we learned during the COVID-19 pandemic, and shows how cloud systems can help to “future-proof” organizations.
To address data security regulations, cloud computing services are accredited and audited by a multitude of third-party security auditors. Other industries, like the financial sector, have been using cloud services for some time and tight standards and audit protocols have established. They are after all protecting sensitive financial and personal data. These standards can be used to ensure data security for the biotechnology and pharma sector cloud applications. Cloud providers have dedicated experts to prioritize security and have vast resources to continually improve the security of the cloud, for example cloud service providers have systems that can mitigate against distributed denial of service (DDoS) attacks as well as managed data back-up services, meaning that cloud systems can potentially offer more data privacy and security than is possible with on-premise applications and data storage solutions.
Another major benefit is the way cloud computing systems can be scaled flexibly. Organizations only pay for the resources they need, when they need them. This removes the headache of having to plan ahead for data storage and application systems; something often impossible to predict in rapid-growth organizations. Cloud flexibility and scalability can provide more capacity for example, if you are expanding your laboratory operations extra storage and compute is available with a few clicks and can be available in minutes. This flexibility extends to global deployments and new labs around the world can be added to your cloud quickly. Cloud computing services help customers by providing multiple services and simplified support channels to deal with scaling connectivity.
Different service models for different cloud computing needs
With the global proliferation and rapid adoption of cloud computing, laboratories are increasingly looking to utilize the advantages of cloud computing as the backbone of their IoT. Service providers and application hosts offer a variety of different service models to meet customer needs. The infrastructure as a service (IaaS) model offer servers and network cloud storage, while software as a service (SaaS) provides a subscription service where both the infrastructure and software are managed for you by a cloud provider or application host. These different service models enable cloud computing to offer flexible, rapid, and cost-effective online applications and storage solutions that secure data in ever more controlled ways, enabling companies of all sizes to implement laboratory cloud solutions with greater success.