Are cloud computing services meeting the challenges of data security, compliance and flexibility?
Cloud computing has become ubiquitous over the past decade. Often times, we barely notice that we are using it to instantly move data and applications back and forth across the web. Like many workplaces, labs are increasingly looking to leverage cloud computing as a way to save time and resources, and as a cost-effective option for implementing enterprise lab solutions.
By integrating cloud computing into all aspects of the scientific workflow, laboratories can harness the increased data security and improved performance provided by the cloud. Cloud services allow labs to access data remotely, allowing scientists to view and process datasets outside of the lab. One of the main advantages of cloud computing is that resources can be increased or reduced, easily and quickly, which means that it can be applied to small single-site labs with minimal or no IT support for multi-global businesses. -sites and multi-laboratories.
But how do labs 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 any lab.
A nebular network of the Internet of Things (IoT)
Cloud computing is the provision of computing resources on demand over the Internet. Applications and data are hosted on virtual servers centralized in a cloud data center and accessible through an Internet connection. Usually the required hardware and software is provided in small monthly payments and only pays for what is used. Different pricing models allow you to save money over on-demand services, and it is possible to commit to a compute amount over one or three years and pay some or all of the costs to the advance, maximizing savings.
Cloud computing has gone far beyond uploading photos and documents to storage systems and is more about connecting everyday objects to the IoT. Smart refrigerators, analysis machines, thermostats and HVAC (heating, ventilation and air conditioning) systems; all are examples of internet-connected instruments for remote control and monitoring from personal computers or mobile applications, as well as for data sharing and integration between devices. All of these IoT components generate large amounts of data, which requires methods to store, process, and access information more efficiently. Cloud computing has the advantage of quickly accessing this data from multiple access points, often including applications âon the goâ from mobile devices.
Rain clouds to come? Perceived challenges of cloud computing systems
Many companies face or perceive challenges in using cloud systems, especially when they need to be integrated into pre-existing systems that are already quite complex. On the one hand, there may be resistance to moving from physical storage systems to cloud solutions due to some perceived risks. Moving from private on-premises storage or a server room to a public cloud, for example, can raise concerns about data security. Many people perceive cloud data loss issues on servers that are not under the direct control of the company and where they are vulnerable to hackers. This is especially true in GxP regulated environments, where governance and data integrity are critical to compliance. There can also be confusion about who is responsible (customer, cloud provider, software vendor) for security.
On the other hand, there are technical or logistical barriers to adopting cloud-based systems. Often these problems are specific to the size of the business. For example, small businesses may think they lack the expertise when it comes to configuring, operating, and managing applications in the cloud. Large companies may already have some experience with cloud systems, but are concerned about complying with data storage regulations, especially when patient data and intellectual property are involved. Another perceived barrier to cloud computing is cost management. The cloud may be cheaper than running infrastructure and applications on-premises, but careful management and monitoring is required to ensure that operating costs are maximized.
The security and flexibility of cloud computing systems
Modern cloud service providers are well aware of the challenges and resistance that customers often face and have worked hard to meet customer needs. This includes tackling misconceptions, especially regarding data security. One of the concerns is that as soon as the term “public cloud” is mentioned, the association is that their data will be stored with all other users of the cloud service. However, this is not how the cloud works. Cloud architecture provides organizations with a virtual private cloud (VPC) that separates data and users. Additionally, customers have full control over who has access to their cloud. Using a virtual private network (VPN) provides encrypted links between the client and the cloud, securing data in transit. Authorized users can access the cloud offsite through VPN and app services, they can work anywhere through 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 ‘future-proof’ organizations.
To meet data security regulations, cloud computing services are accredited and audited by a host of third-party security auditors. Other industries, such as the financial sector, have been using cloud services for some time and strict audit standards and protocols have been established. They do, after all, protect sensitive financial and personal data. These standards can be used to ensure data security for cloud applications in the biotechnology and pharmaceutical industry. Cloud providers have dedicated experts to prioritize security and have vast resources to continuously improve cloud security e.g. cloud service providers have systems that can mitigate Distributed Denial of Service (DDoS) attacks as well as managed data backup services, which means cloud systems can potentially offer more data privacy and security than is possible with on-premise applications and data storage solutions.
Another major advantage is the way in which cloud computing systems can be scaled flexibly. Organizations pay only for the resources they need, when they need them. This eliminates the headache of having to plan ahead for data storage and application systems; something often impossible to predict in fast growing organizations. The flexibility and scalability of the cloud can provide more capacity, for example, if you expand your lab operations, additional storage and compute is available with a few clicks and can be available within minutes. This flexibility extends to global deployments and new labs around the world can be added quickly to your cloud. Cloud computing services help customers by providing multiple services and streamlined support channels to manage scalable connectivity.
Different service models for different cloud computing needs
With the global proliferation and rapid adoption of cloud computing, labs are increasingly looking to use the benefits 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 offers networked servers and cloud storage, while Software as a Service (SaaS) provides a subscription service where the infrastructure and software are managed for you through a cloud provider or application host. These different service models enable cloud computing to deliver flexible, fast, and cost-effective online storage applications and solutions that secure data in an increasingly controlled manner, enabling businesses of all sizes to implement cloud-based solutions. laboratory with more success.