By Bridget Karlin, chief technology officer, IBM Global Technology Services and Kristof Kloeckner, Ph.D., chief technology officer and general manager, IBM Global Technology Services
With rapidly changing business needs and accelerating business cycles, organizations need consistent and reliable service delivery across a “supply chain” of services from multiple vendors. There is no compromising choice for reliability. Both play an equally important role in a business’s success and they need the services they are using to continuously evolve.
For the IT services industry, it means a shift from system integration to services integration, and from a people-led and technology-assisted approach to one that is technology-led and people-assisted. In other words, most standard tasks and processes will be executed by increasingly autonomic systems that are data-driven, cognitive, and automated.
This approach also means the evolution of automation and advanced analytics to cognitive delivery. Like many in the industry, we believe cognitive delivery is the next stage of the delivery lifecycle transformation.
Companies are already taking better advantage of the wealth of operational data and experience to gain insights that trigger automated actions for better business outcomes from IT or advise human experts to make better decisions.
Using a simple analogy from biology, cognitive technologies like IBM Watson provide the brain (insights) and automation serves as the muscle (action). Information about the systems we manage in this way is constantly fed back into the ‘brain’ to enable further learning and produce better outcomes. Thus, the systems begin to understand, reason, and learn to become self-healing and self-optimizing. In other words, to become autonomic systems.
Cognitive delivery is enabled by our IBM Services Platform with Watson, comprised of IBM’s Data Lake, Cognitive Delivery Insights services and knowledge bases and role-based dashboards.
We expect that increasingly autonomic behavior will emerge in the context of business services or applications. Augmenting application performance management and event management systems with pattern recognition and deep learning will be critical.
Underlying ontologies will be the “glue” between the different levels of cognitive insights and will enable micro and macro learning mechanisms to support each other. For instance, learning that does not yet lead to automatic actions can still feed into the corpus of knowledge to aid a human expert.
In the emerging hybrid cloud world, services are designed, built and run with a workload perspective as the driving force.
Service delivery and integration requires a platform to mediate between IT consumers and service providers and to bridge between the business perspective represented by workloads and their owners and consumers and the services supporting them.
This platform is evolving and has three layers:
- A broker layer for governance of IT consumption, supported by a (federated) self-service catalog. This allows client CIOs to have visibility and control over who uses which services, while giving the users convenient access to services provided by potentially multiple providers (a services supply chain).
- An orchestration layer that ensures automated fulfillment of the service requests and integration of services across multiple providers, using blueprints (patterns) of configurations that embody best practices.
- An operational lifecycle layer that provides service management driven by automation and analytics.
This platform is data-driven, cognitive, and automated, with a data lake, analytics, and cognitive services spanning all the layers and the entire lifecycle of solutions using the platform.
A growing number of companies are using the platform with Watson and taking advantage of the wealth of operational data and experience. With this cognitive service, they’re gaining insights from their IT systems that either direct automated actions that result in better business outcomes or that advise human experts to make better, data-driven decisions.
A version of this story appeared on IBM’s THINK blog.
This post is sponsor content from IBM and was created by IBM and BI Studios.