Everything we do is about quality and delivering value. The principles below are how we pursue that: they guide how we think about building and operating systems. They are not mutually exclusive; they reinforce one another. Together they add up to what we mean by architecturally sound: fit for purpose, maintainable, and improving over time.
This post states those principles in a general way. It is our philosophical view — applicable to software, platforms, and processes — not a description of any single product.
Composability and Disposability
We favor composable building blocks: small, well-defined pieces that can be combined in clear ways. You can reason about each part and replace or evolve it without rewriting the whole. Composable systems are easier to understand, test, and change.
We also value disposability: components and workflows should be replaceable or removable without bringing down the rest. No single part is irreplaceable. The system degrades gracefully and can be repaired or upgraded in place. Disposability reduces fear of change and makes evolution possible.
Cloud-Friendly and Cloud-Native (Where It Fits)
We design for the reality that many systems run in the cloud and use managed services. Where it applies, we follow cloud-friendly and cloud-native patterns: APIs over tight coupling, event-driven updates, stateless coordination where possible, and integration with the existing ecosystem instead of replacing it. The goal is to work with the environment, not against it.
No Lock-In
We believe that users and customers should retain control of their data, their configuration, and their ability to operate without the platform. Systems should minimize the hold they have on their users. No lock-in is both an ethical stance and an architectural one: design so that exit is possible and that the source of truth lives where the user owns it.
Stability, Availability, and Scalability
We aim for stability: behavior that is predictable and repeatable. When the rules are clear and consistent, people can rely on the system. That stability makes availability meaningful — when the system is up, it behaves as expected.
Scalability should be addressed by design, not as an afterthought. Prefer coordination mechanisms (e.g. events, queues, immutable records) that allow the system to grow without a single monolithic bottleneck. Scale with usage rather than requiring disproportionate scaling of any one component.
Security and Performance
Security should be built in from the start, not bolted on later. Access control, auditability, and the principle of least privilege are first-order constraints. We treat security as part of the architecture, not a separate concern.
Performance (speed) matters: fast feedback and short, reliable flows reduce waiting and rework. We optimize for throughput and latency where they directly improve outcomes. Slow, opaque systems create drag and encourage workarounds.
Ease of Use, Ease of Adoption, and Aesthetics
A system that is hard to use or unpleasant to work with will be avoided or misused. We care about ease of use: clear workflows, consistent terminology, and self-service where it makes sense. We care about ease of adoption: onboarding and documentation that let people get value quickly without a long, painful integration.
We also value aesthetics in the sense of clarity and coherence. The interface and the mental model should feel consistent and purposeful. A well-organized, readable experience is part of an architecturally sound system — not a nice-to-have.
Reduce Cost and Waste
We aim to reduce, eliminate, or avoid cost where it doesn't add value: unnecessary moving parts, duplicate systems, or complexity that doesn't serve users. Cost here includes time, money, and cognitive load.
We apply a lean lens to how work flows:
- Excess inventory: Avoid building or holding artifacts that sit unused or obsolete. Keep inventory visible and minimal. Lean practitioners often regard excess inventory as the worst form of waste, because it drives or hides all the others: it encourages batch processing, creates waiting and handoffs, masks defects (so rework happens late), and ties up capacity that could be used for improvement. Reducing inventory forces the system to surface and fix flow problems instead of hiding behind stock.
- Duplicative work: Eliminate or reduce duplicative effort. One source of truth where possible; avoid maintaining the same information in multiple places. When the same work or the same data is replicated across people or systems, waste and inconsistency grow. Consolidate and automate so that effort is done once and reused.
- Standardization: Standardize so that work can be proceduralized — written down, repeated consistently, and improved. Once a procedure exists, assess whether the bang for the buck justifies automation. Automate when it makes sense; don't automate chaos. Standardization is the foundation that makes both proceduralization and selective automation possible.
- Excessive movement or motion: Movement and motion for their own sake are waste and should be minimized or eliminated. Reduce unnecessary handoffs and context switches. Make paths clear and auditable.
- Rework: Catch problems earlier so that fewer defects propagate. Make rollback and recovery first-class: when something goes wrong, the fix should be a known, repeatable operation, not ad-hoc firefighting. We value fail fast, fix fast — surface failures quickly, then fix them quickly. The goal is to avoid rework by detecting and correcting early, and to make the cost of remaining rework low when it does occur.
- Waiting: Reduce waiting on manual steps and batch jobs. Visibility into status reduces "waiting to find out": people should see where work is and what state it's in, instead of waiting for someone to tell them. We also value genchi genbutsu (go and see): rather than wait for reports or secondhand information, go to the place where the work happens and observe. Design for fast feedback so that waiting is the exception, not the norm.
- Batch processing: Favor small, frequent updates over large, infrequent batches where continuous flow is possible. One-piece flow is the goal: move work in small units through the value chain so that issues show up immediately and flow is smooth. Large batches hide problems, delay feedback, and increase the cost of failure. Where we can, we prefer continuous or near-continuous flow to batch.
- Handoffs: Minimize handoffs in the value chain. Every handoff is a place where information can be lost, queues can form, and "who does what" can become ambiguous. Where handoffs are necessary, make roles and responsibilities clear and make handoffs visible and accountable — so that ownership is explicit and delays or dropped handoffs are obvious.
- Lost opportunity to innovate: By reducing firefighting, rework, and waiting, we free time and attention for improvement and innovation. A stable, visible system is a foundation for experimenting safely.
Continuously Measure and Improve
We believe in continuous measurement and monitoring to find and act on improvement opportunities. Systems should be observable: metrics, logs, and feedback loops that show where time is spent and where failures occur. We don't just collect data; we structure it so people can identify bottlenecks, track trends, and decide where to optimize. Architecturally sound systems are observable and improvable.
In Short: Architecturally Sound
These principles — composability and disposability, cloud-friendly design, no lock-in, stability, availability, scalability, security, performance, ease of use and adoption, aesthetics, cost and waste reduction, and continuous measurement — are not a checklist we tick once. They are a philosophical stance in service of quality and delivering value. They guide how we design and evolve systems and how we judge what we build. Together they add up to what we call architecturally sound: reliable, maintainable, and getting better over time.
We try to live by them in what we build at essesseff. We offer this as our view, in the hope that it resonates with others who care about quality, value, and the same things we do.
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