Risk
Risk is the possibility and potential impact of an adverse outcome arising from uncertainty.
Investing for Programmers
Investment risk is the possibility that an investment will produce an unfavorable outcome, including loss or lower-than-expected returns.
- How it is used
- Frames risk as the basis for investment decisions, portfolio construction, and disciplined challenge of optimistic claims.
- How deep it goes
- Explains classification, systemic threats, risk matrices, hedging, and portfolio pairing through practical scenarios rather than dense quantitative modeling.
- Examples
- Uses LiDAR stocks, AI companies, Coca-Cola, Apple, Pfizer, speculative technologies, risk matrices, and stable-versus-speculative allocations.
- What you can do after
- Evaluate/understand investment risk by identifying threats, ranking severity and likelihood, challenging assumptions, and selecting mitigation approaches.
Software Testing with Generative AI
The possibility that an action, system, or technology will cause harm, loss, failure, or another undesirable outcome.
- How it is used
- Guides testing toward specific quality concerns before selecting techniques, prompts, test cases, or exploratory sessions.
- How deep it goes
- Develops identification, prioritization, mitigation, and LLM augmentation, while stopping short of a fixed procedure for discovering risks.
- Examples
- Uses fast-food ordering, file upload, booking reports, generated test cases, and exploratory charters to make risk-focused testing concrete.
- What you can do after
- Apply it to identify concerns, challenge LLM suggestions, select proportionate testing activities, and prioritize exploratory work.
Read how Software Testing with Generative AI explains risk →
Architecture Modernization: Socio-technical alignment of software, strategy, and structure
Risk is the possibility that uncertainty will adversely affect an objective, investment, or change initiative.
- How it is used
- Prioritizes modernization opportunities by exposing threats to timely delivery and their consequences.
- How deep it goes
- Frames risk through causes and consequences in a context-specific scorecard rather than prescribing a universal scoring model.
- Examples
- Uses a workflow automation subdomain, promised customer features, a modernization initiative, and a legacy monolith.
- What you can do after
- Evaluate modernization candidates by comparing delivery threats with business value and learning value.
Delivering Machine Learning Projects: From design to deployment
Project risk is the possibility that uncertainty in a project will cause adverse effects such as cost escalation, unmet targets, or failure to deliver.
- How it is used
- Uses pre-project investigation and governance to reduce uncertainty before committing resources and accepting delivery obligations.
- How deep it goes
- Descends from risk sources to registers, mitigation confidence, premiums, documentation, review meetings, and accountable sign-off.
- Examples
- Uses risk registers, mitigation estimates, $500-to-$1,000 premium examples, weekly stakeholder reviews, and fixed-price delivery scenarios.
- What you can do after
- Apply it via a risk register, mitigation estimates, risk premiums, budget review, documentation, and accountable sign-off.
Read how Delivering Machine Learning Projects: From design to deployment explains risk →
Functional Design and Architecture: Examples in Haskell
A risk is a potential problem whose occurrence can increase the cost, delay, or failure likelihood of a software project.
- How it is used
- Guides architecture, simplicity, planning, and testing decisions intended to keep delivery and maintenance problems manageable.
- How deep it goes
- Illustrates architectural and complexity risks through scenarios, then identifies testing approaches without providing a complete risk-management procedure.
- Examples
- Uses incompatible independently built components, overcomplicated code, and black-box, white-box, functional, and integration testing.
- What you can do after
- Diagnose threats arising from architectural mismatch and overcomplication, then recognize testing as a way to reduce specific project risks.
Read how Functional Design and Architecture: Examples in Haskell explains risk →
Data-Driven Cybersecurity
The potential for loss, harm, or adverse impact arising from a threat exploiting a vulnerability or hazardous condition.
- How it is used
- Frames risk assessment as a bounded method for analyzing assets, threats, vulnerabilities, likelihood, and impact.
- How deep it goes
- Explains scope, assets, threats, and vulnerabilities procedurally, but stops short of teaching complete threat assessment.
- Examples
- Uses products, changes, implementations, critical assets, locations, data centers, and custom software without CVE entries as examples.
- What you can do after
- Evaluate risk by defining scope, identifying relevant threats and vulnerabilities, and relating likelihood and impact to reporting.
Bootstrapping Microservices, Second Edition: With Docker, Kubernetes, GitHub Actions, and Terraform
Deployment risk is the possibility that releasing a software change will cause failures or disruption in an application.
- How it is used
- Uses deployment risk to justify service boundaries and independent updates in microservices.
- How deep it goes
- Explains localized failures and rollback consequences but stops short of prescribing deployment procedures.
- Examples
- Uses service updates, partial application failures, and rolling back a small system part as concrete examples.
- What you can do after
- Evaluate how service boundaries can localize failures and make rollbacks smaller.
Authorization in Action
Risk is the possibility of an unfavorable outcome or failure arising from dependence on uncertain actions or conditions.
- How it is used
- Uses risk to select authorization signals, assurance, freshness, and delegation controls for different operational decisions.
- How deep it goes
- Connects risk to signal freshness, data quality, latency, and authority boundaries, stopping short of formal risk calculation.
- Examples
- Uses document viewing, production deployment, customer platforms, employee access, and engineering tools to contrast risk-sensitive decisions.
- What you can do after
- Evaluate authorization designs by matching signal assurance and freshness to the consequences of stale or insufficient context.
Related concepts
- risk matrixmeasured by · A risk matrix is a tabular or graphical tool that classifies risk levels by combining estimated likelihood and potential impact.
- security controladdressed by · A security control is a safeguard, policy, or restriction designed to reduce security risks or enforce security objectives.
- batch sizeproduced by · Batch size is the number of items grouped together for processing or computation as a single batch.
- market riskincludes · Market risk is the risk that movements in the overall market will reduce an investment’s value.
- code coveragecontrasts with · Code coverage measures the extent to which a test suite exercises a program’s code elements, execution paths, or behaviors.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.