By Tobias Kunze, Co-founder & CEO, Glasnostic

Enterprises today face rapidly changing business needs, and the pressure to modernize digitally demands fast-paced innovation. As a result, the number of services and applications that support the business is growing continually, created by parallel development teams that are working autonomously in rapid decision and learning cycles.

Innovative applications are not islands, however. It takes little time for new applications and services to depend on them. As more and more new services build on top of existing ones, stacked like LEGO blocks atop one another, enterprises quickly find themselves running an ecosystem of services that are inextricably connected. They find themselves running a service landscape.

How Does a Service Landscape Support Enterprise Agility?

Unlike a stand-alone, self-contained application that has been architected and designed based on a coherent blueprint, a service landscape evolves organically. Independent teams deploy code rapidly and contemporaneously. This enables the enterprise to become agile, ready to support new services as needed. It is able to innovate and quickly take advantage of new market opportunities.

The ability to support rapid change makes a service landscape the architectural style of choice to support an agile enterprise. However, the complex and dynamic nature of service landscapes can lead to unpredictable and disruptive application behaviors. If these behaviors are not adequately observed and controlled, they can threaten the stability of the service landscape and bring the enterprise down.  

Typical journey of enterprises transitioning from a static operating model to an agile one.

How Do Enterprises Transition From a Static Operating Model to an Agile One?

Enterprises typically transition to an agile operating model on multiple levels simultaneously:

• At the organization level, top-down hierarchies are replaced with autonomous, self-managing teams that execute in fast decision and learning cycles, thus enabling an agile organization.
• At the operational level, the transition from IT Ops to DevOps and SRE enables a "Mission Control" approach to operations.
• At the architecture level, enterprises transition from monolithic applications first to microservices and shared business services before embracing organic federated growth, which ultimately leaves them with a service landscape.
• At the middleware level, traditional integrations are replaced first by APIs, then by gateway solutions and eventually service meshes. This gives enterprises control over how their services interact.
• Finally, at the infrastructure level, enterprises typically move traditional virtual machine deployments to PaaS, SaaS, container platforms or even serverless environments. This provides them with the ecosystem of cloud services that their new agile operating model requires.
  

In practice, individual journeys may assign different weights to the various sub-journeys. For instance, a traditional enterprise looking to modernize aggressively on the organizational level may be able to leapfrog some stages or de-emphasize individual sub-journeys.

How Does the Role of Operators Change When Running a Service Landscape?

While a service landscape is ideally suited to adapt to the rapidly changing business needs of an agile organization, its complex and continually evolving nature makes it prone to unpredictable and disruptive behaviors. These behaviors arise from often subtle changes in the interaction patterns between services. They are large-scale and systemic in nature and tend to occur unexpectedly, presenting operations teams with two fundamentally new challenges: detecting them quickly enough and, once they are detected, responding to them in real-time. As a result, and like leadership in an agile enterprise in general, the role of operations in a service landscape evolves into one that sets direction and enables quick remediation.

What Does It Take to Manage a Service Landscape Successfully?

Given the complexity and dynamic nature of a service landscape, conventional observability is no longer enough. The key to successfully managing the unpredictable behaviors in a service landscape is to put a cloud traffic controller into place that provides both high-level observability and real-time control to avoid outages and costly downtime. Fixing the underlying issue becomes secondary to observing behaviors in real-time and exerting control to maintain the stability of the system as a whole.

Examples of such measures of control include predictable operational patterns such as ringfencing ("quarantining") new deployments, inserting bulkheads between architectural partitions, exerting backpressure against disruptive service interactions or shedding load to protect compromised services via circuit breakers. These operational patterns are operational concerns that are in the purview of the "mission control" level, above those of developers.

As organizations today move inexorably forward in the transition to the model of an agile enterprise that is supported by an equally agile service landscape, observability and control are critical in assuring the health and digital experience of their environments and achieving operational excellence.

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About the Author

Tobias Kunze is the co-founder and CEO of Glasnostic, where he is on a mission to help enterprises control their rapidly evolving application landscapes. Prior to Glasnostic, he was the co-founder of Makara, an enterprise PaaS that became Red Hat OpenShift.