Rendering in the cloud – A matter of scale and agility

Data science and storytelling CSC Blogs

By Paul Attridge, CSC Life Sciences Product Technology Strategist

Over the past few months we’ve had a very informative back-and-forth discussion with our partner Adlib about PDF rendering. During the discussion, we’ve addressed the problems associated with low-cost rendering, and Adlib added to the discussion with a blog on the power of high-fidelity rendering. We then offered our point of view on the importance of scale, configuration and system monitoring, and Adlib further responded with a blog on the importance of efficiency.

The one issue we haven’t delved into as yet is how cloud provisioning fits into the rendering equation. With rendering, what matters to customers is agility. Customers need a service that is scalable, but without involving large amounts of infrastructure, effort and cost. Such a service isn’t multi-tenant since it doesn’t involve multiple customers, but it does need to be a shared provision across the customer’s own internal requirements. However, the customer will always need the service to be gold standard. That’s because rendering is such a critical part of the puzzle, which means you can’t get by with something that provides only 95% availability.

Preparing for Bottlenecks

The reality is that with rendering there is very little planning that can go into preparing for the critical bottlenecks that occur when there is unpredictable and sometimes high-level demand for a solution. That means the demand for service is unpredictable so customers need a service they can scale up quickly as and when they need it. At the same time, you don’t want to have to bring in a lot of new people to add in these new capabilities, so you want a service that can scale up quickly without adding to internal time and cost burdens.

On the other side of the spectrum, there are things that a cloud service for rendering won’t require. Generally, because it is a back-end service, it doesn’t require connectivity into the customer’s environment. That simplifies cloud deployment because the provider doesn’t have to connect that cloud deployment to the user’s work station. What tends to happen is users will say, for example, that in three weeks they’ll be working on a submission and will need rendition support. The cloud provider then goes away, builds the provision and makes it available. That’s different from, say, a software upgrade, which has a significant impact on the customer’s working environment.

Keeping it Simple

From our point of view, as life sciences solutions providers, and particularly in providing a productive and user-friendly environment for a content management system, these are important and well-considered aspects of what we do. With FirstDoc, for example, new rendition engines or new scalability requirements can be added to enable an improved level of service quickly through configuration. That makes plugging in new rendition engines or new scalability requirements simple, cost-effective capabilities to maintain.

At the same time, we’re able to scale customers for cloud infrastructure in a dynamic way by managing applications in hybrid cloud environments. So we can scale the environment at whatever tier of the infrastructure or architecture is needed through configuration rather than requiring the commissioning of new hardware.

Adlib then scales the solution to meet the provision, so our question for our partner is how do they go about doing that?

Secondly, as we’re providing a solution as a service, what does Adlib have in its arsenal to enable us or any cloud provider to monitor the state of meeting the service level set by the customer?

These are all crucial considerations in deploying a rendition solution, especially as more customers look to adopt cloud capabilities to manage at least some aspects of the submission process. And I believe once you’ve heard from Adlib, how all those pieces of the puzzle fit together will become even clearer.



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