Is the infrastructure management world turning into a software engineering business?

Setting the stage

The challenge around an organization’s digital landscape has always been about ensuring that this complex environment — made of a heterogeneous set of digital assets — drives profitability via economies of scale, such as standardizing asset landscapes and optimizing processes.
With the advent of cloud, that landscape has transformed completely, including the way it is being provisioned and managed. These transformations can have positive impacts beyond the pure cloud locations, now reaching data centers, on-premises edge computing and even network edge computing locations.

The automation of IT management is one of the fundamental means to reach that cost optimized state. More recently, cloud provisioning tools have increased the scope of automation from pure change management operations (Day 2) to include the actual provisioning automations (Day 1). That is the domain of new tooling like Terraform, Chef, Puppet and Ansible, to name a few.

Recent years have shown an acceleration in the adoption of public and private cloud hosted infrastructure. The maturity of these environments has kept increasing to a point that it starts to change not only the way we consider what is a proper IT landscape, but more fundamentally the way we need to provision and manage these environments at scale. Infrastructure-as-code and Everything-as-a-service – also known as “SaaSification” — is becoming the norm in public and hybrid clouds, which brings some interesting consequences on the tooling and skillsets of technology players.

The benefits of cloud technologies are now becoming more widely understood. IT departments appreciate cloud’s elasticity and its pay per use model. User communities like the increased speed of development teams, which bring them more frequent releases and fast evolutions. Business users like the scalable security and its ability to absorb demand peaks without being concerned about long and painful capacity management processes.

Adopting cloud is a genuinely transformative activity. If migrating first and transforming later is often viewed as the easy path, there is a relative dissatisfaction following a pure lift and shift strategy. The greater benefits of cloud adoption come from real transformation of the applications’ fundamental shape and structure, as well as the tooling and processes to manage them.

The instinct is now to decompose monolithic applications into microservices, adopt set infrastructure elements like containers, and the lifecycle management leans toward a destroy and recreate approach — rather than a fix in situ process.

This creates disruption with a move to software engineering practices that I will explain in a next blog. The risk is to underestimate the impacts of this shift by thinking of it as a pure tooling evolution. In doing so, you might miss the more fundamental evolution that is required for a proper adoption of these new cloud technologies. This could turn into a significant transformation of technical approaches and staff skillsets.

Please follow me in this series of articles exploring how this transformation is triggering a massive shift toward software engineering technologies. It will have an immediate effect on risk, liability, and the skillsets required to tackle these new challenges and bring business benefits to customers. In later articles, I will explore:

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