Over the past three years, my work as a Staff Solutions Architect at VMware has exposed me to IT strategies across various Fortune 500 companies. One recurring theme in these engagements is the industry’s focus on creating a stable and secure initial state. While crucial, this emphasis often neglects the operational realities post-deployment. Each “initial state” creates operational debt, which compounds over time due to the dynamic nature of IT systems. This debt accounts for approximately 70% of operational spending, limiting innovation and agility in IT organizations.
Three significant factors exacerbate operational debt:
- Automation of Provisioning
- Public Cloud Adoption
- Dynamic Nature of Containers
Key Drivers of Operational Debt
1. Automation of Provisioning
Provisioning automation aims to reduce delivery times for development and production assets. While it increases agility, it often accelerates the accumulation of operational debt due to insufficient governance. Enhanced self-service capabilities increase consumption, compounding long-term operational demands.
2. Public Cloud Adoption
Initially adopted for cost savings, public cloud services now appeal for other reasons:
- Reduction of infrastructure operational debt.
- Access to unique services like machine learning and serverless functions.
- Proximity to data already in the cloud.
Although public clouds abstract infrastructure components into software and streamline operations, they still focus on the initial state. Operational costs and vendor lock-in remain critical concerns.
3. Dynamic Nature of Containers
Containers promise immutability and agility, but they introduce new challenges:
- Increased observability and management complexity.
- Rapid proliferation of containerized microservices, expanding operational scope.
- Short-lived container lifespans (minutes or hours) exacerbate operational demands.
For example, Google addressed container-driven complexity by creating the Site Reliability Engineer (SRE) role, blending development and operations to scale effectively.
Strategies for Reducing Operational Debt
1. Recognizing the Problem
Operational debt is split into two categories:
- Common Operational Debt: Shared across organizations (e.g., patching, monitoring, hardware refresh).
- Unique Operational Debt: Specific to the organization’s processes or systems.
2. Identifying Toil Tasks
Use the following criteria to identify toil tasks:
- Repetition: Use ticketing systems to track common tasks.
- No Human Judgment Needed: Tasks requiring no decision-making or creativity.
- Interrupt-Driven: Reactive tasks triggered by tickets or notifications.
3. Automating Toil Tasks
Once identified, prioritize automation of repetitive tasks. Focus on transitioning these tasks from human operators to automated systems, reducing latency and improving efficiency.
4. Adopting Service-Oriented Models
Operational tasks should be automated as part of the service deployment. This integration minimizes toil and aligns operations with service delivery.
A Roadmap to Address Operational Debt
The steps include:
- Implement Software Abstraction – Adopt software abstraction to enable automation and eliminate infrastructure debt.
- Prioritize Toil Automation – Leverage ticketing systems to create a prioritized list of repetitive tasks for automation.
- Transition to Declarative Models – Shift to declarative infrastructure models to enforce expected states post-deployment, reducing the need for manual oversight.
- Continually Reduce Toil – Even with declarative models, ongoing effort is required to address residual operational debt.
The Business Impact of Operational Debt Reduction
Organizations that adopt these strategies report up to a 50% reduction in operational costs, allowing IT to shift from a cost center to a strategic business enabler. This approach not only drives innovation but also enhances agility, empowering IT to better support organizational goals.
By proactively addressing operational debt, IT can unlock sustained efficiency gains and long-term value, transforming the enterprise’s approach to technology management.