Measure And Run Technology Operations
System reliability, availability — from 11 books.
Mike West, Editor · Leading With Data · leadingwithdata.guide/guides/it-analytics
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Measure And Run Technology Operations
System reliability, availability — from 11 books.
Mike West, Editor · Leading With Data · leadingwithdata.guide/guides/it-analytics
The problem
System reliability, availability and performance erodes when it is left to instinct instead of method.
You were taught the moves piecemeal, never the whole model.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
The model
- 01Continuous Delivery & Deployment Automation
- 02Loosely Coupled / Modular Architecture
- 03Code Complexity & Technical Debt
- 04Security, Fairness & Responsible Practices
- 05Monitoring & Observability
- 06Metric & Dashboard Design Quality
- 07Business / Strategic Alignment
- 08Data Quality & Management
How it grows
- New to the role0–1 yr
- Running the function1–3 yr
- Shaping the whole3+ yr
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Step 1 of 5 · Continuous Delivery & Deployment Automation
Capability, not cadence: aim to make on-demand release possible, then let the business decide how often to use it.
Misconception
Teams believe continuous delivery means deploying to production many times a day, so they dismiss it as irrelevant to their regulated or infrequently-shipping domain.
Reality
The capability is about being *able* to release safely on demand, not about release frequency itself; a bank that can deploy in an hour but chooses to deploy weekly still has the capability and reaps its stability benefits.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Step 2 of 5 · Loosely Coupled / Modular Architecture
Independent deployability, not service count, is the measure of a loosely coupled architecture.
Misconception
Practitioners think adopting microservices automatically gives them loose coupling and independent deployability.
Reality
Physically separate services can be tightly coupled through shared databases, synchronous call chains, and lockstep release requirements; the test is whether a team can change and deploy its component without asking permission or coordinating a release with others.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Step 3 of 5 · Code Complexity & Technical Debt
Prioritize debt by where change is frequent and failure-prone, not by raw complexity metrics.
Misconception
Teams treat technical debt as a purely internal engineering concern that can be paid down later during a dedicated refactoring sprint.
Reality
Debt accrues interest continuously as rising change cost and defect risk, and the 'big refactor later' rarely gets funded; managing it means continuous small repayment tied to areas you are already touching.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Step 4 of 5 · Security, Fairness & Responsible Practices
Integrated security correlates with faster delivery, not slower — it is not a speed tax.
Misconception
Leaders assume that adding security and compliance review at the end of delivery slows teams down and trades off against speed.
Reality
Teams that build security into daily work — through automated scanning, pre-approved libraries, and threat modeling during design — deploy faster *and* remediate faster, because integrated controls prevent the end-of-cycle blockages.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Step 5 of 5 · Monitoring & Observability
Observability means answering unanticipated questions, not displaying pre-built charts of known metrics.
Misconception
Teams equate more dashboards and more alerts with better observability.
Reality
Observability is the ability to answer novel questions about your system without shipping new code; a wall of static dashboards and threshold alerts often signals monitoring for known failures only, and volume of alerts inversely correlates with trust in them.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
A framework to use
The 24 Capabilities Model for High Performance
This framework is part of the full guide. See the guide →
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
The cheat sheet
- Continuous Delivery & Deployment AutomationCapability, not cadence: aim to make on-demand release possible, then let the business decide how often to use it.
- Monitoring & ObservabilityObservability means answering unanticipated questions, not displaying pre-built charts of known metrics.
- Metric & Dashboard Design QualityEvery metric should name the decision it informs and the objective it derives from.
- Business / Strategic AlignmentMaintain an explicit, traceable chain from business objectives down to operational metrics.
- Process Improvement Methodology & DisciplineThe practices — small batches, WIP limits, fact-based analysis — matter more than the framework's name.
- Leadership Commitment & Transformational LeadershipSponsorship persists only when leaders reallocate resources and defend the program during the first budget squeeze.
- Software/System Delivery PerformanceHigh performers achieve speed and stability at once; the trade-off is a myth of poor practices.
- System Reliability, Availability & PerformanceSet error budgets per journey and let budget burn — not metric spikes — trigger both alerts and feature freezes.
Measure And Run Technology Operations · Mike West, Editor · Leading With Data
Sources
- Accelerate The Science of DevOps — Nicole Forsgren, Jez Humble, Gene Kim
- Designing Machine Learning Systems — Chip Huyen
- Effective Data Science Infrastructure — Ville Tuulos
- IT Governance Metrics Measurement and Benchmarking Best Practice Workbook Roadmap, Implementation and Management - Ready to… — Ivanka Menken Gerard Blokdijk
- Metrics for IT service management (Brooks, Peter (Business consultant), author)
- Performance Dashboards Measuring, Monitoring, and Managing Your Business — Wayne W. Eckerson
- Practical Monitoring Effective Strategies for the Real World — Mike Julian
- Reliable Machine Learning Applying SRE Principles to ML in Production — Cathy Chen, Niall Richard Murphy etc.
- Software Architecture Metrics — Christian Ciceri et al
- Supply Chain Planning, 2nd Edition — etc.
+ 1 more sources in the full guide
Measure And Run Technology Operations · Mike West, Editor · Leading With Data