Most IT professionals lack visibility into their hybrid and multi-cloud environments. And they have problems identifying all the cloud services in use in their organizations.
The cloud promised three important things – simplicity, security, and flexibility. As the variety and the sheer number of cloud platforms increases with unprecedented velocity, the corresponding challenges of effectively managing, securing, and paying for these cloud services inevitably rise, too. An Omdia report suggested that by 2023 most companies will spend 40% of their IT budget managing their infrastructure across multiple cloud service providers.
There are many factors influencing these challenges – chief among them are cost and security. In addition, the growing use of hybrid or multi-cloud architectures increases complexity and creates additional obfuscation. In the Omdia study, most of the IT professionals surveyed reported that they had problems simply identifying all the cloud services in use in their organizations.
Cloud providers have done a good job of delivering tools that address issues within their own particular platforms, but there are limitations. For example, the visualization of the cloud infrastructure varies between each provider tool. Nomenclature often differs between platforms, and the tools themselves don’t integrate with each other.
Indeed, IT resources are often stretched thin or constrained. Managers face a paucity of trained engineers, a situation further complicated by a budgetary climate that doesn’t allow for the hiring of additional staff. Ultimately, enterprises need to empower their people to use their training more effectively. Additionally, diagnosing a problem using siloed providers and people whose skills and training fail to cross tech and platform boundaries usually requires the services of multiple experts, whether that be in cloud engineering, security engineering/operations, or network engineering/operations.
Enterprises need to find a better way.
Specifically, they need to ensure their toolbelt includes a few important capabilities. For one, they need to maintain a normalized view across all facets of the “computing estate” they occupy, preferably on a single screen. There need to be mechanisms that can verify that security policies are consistently enforced across all clouds in the enterprise’s IT infrastructure.
Additionally, there needs to be a way for staff to instantly visualize the topography of the entire hybrid multi-cloud environment and to be able to drill down into individual devices or cloud resources from there. In order to reduce Mean Time To Recovery (MTTR) after an incident, engineers need easy access to configuration, state, and behavioral data across on-premises as well as the multi-cloud environment.
One way to achieve this is through the use of a network digital twin. Using a read-only collection of running configuration and dynamic state from on-premises devices and cloud provider APIs, a digital twin computes all possible traffic paths and effectively turns the billions of lines of configuration into a searchable behavioral database. This way, insights that previously took hours, days, or even weeks to obtain, become instantly available.
This level of detail makes it possible to solve problems faster, prove network innocence, and verify security compliance. Using a myriad of siloed tools in an attempt to gather this information is slow and error-prone. A network digital twin is necessary to make networks more agile, predictable, and secure.
