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Discovery

Discovery is a systematic process of finding or identifying previously unknown information, entities, patterns, problems, or possibilities.

How 4 Manning books explain it

Architecture Modernization: Socio-technical alignment of software, strategy, and structure

Discovery is work that investigates a problem, opportunity, or domain to establish sufficient understanding for subsequent design and delivery.

How it is used
Guides modernization teams in identifying opportunities and business outcomes before or alongside architectural design and delivery.
How deep it goes
Defines activities, trade-offs, feedback loops, and roadmap visibility, but stops short of prescribing a rigid discovery process.
Examples
Uses stakeholder interviews, Wardley Mapping, EventStorming, roadmaps, and CloudSuite’s discovery and ordering domain boundaries.
What you can do after
Apply it via stakeholder interviews, Wardley Mapping, EventStorming, and feedback loops to refine modernization priorities and boundaries.

Read how Architecture Modernization: Socio-technical alignment of software, strategy, and structure explains discovery →

Akka in Action, Second Edition

Discovery is a mechanism for locating actors, services, or cluster nodes across available network destinations.

How it is used
Locates cluster contact points so Akka Cluster Bootstrap can form and join an Akka cluster.
How deep it goes
Explains configuration, bootstrap decisions, runtime joining behavior, and Kubernetes label-based lookup without detailing discovery-provider internals.
Examples
Demonstrates two local nodes with fixed IPs, bootstrap logs, and a three-pod Kubernetes Deployment selected by labels.
What you can do after
Operate/configure local and Kubernetes-based contact-point discovery for an Akka cluster.

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Think Like a CTO

A discovery phase is a structured period of investigation in which systems, capabilities, problems, and improvement opportunities are examined before major execution begins.

How it is used
Uses investigation during an executive transition to establish facts before shaping plans or launching major initiatives.
How deep it goes
Descends from project review to direct inspection of code, data, servers, and infrastructure, then stops short of major execution.
Examples
Uses source-code reviews, data-store reviews, infrastructure checks, client visits, quick-fix lists, and project-scope adjustments.
What you can do after
Diagnose capability and operational gaps, identify quick wins, formulate plans, and adjust initiatives using observed evidence.

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Introduction to Generative AI, Second Edition

Discovery is the formal legal process in which parties to a lawsuit exchange information about witnesses and evidence to be presented at trial.

How it is used
Supports legal practice by organizing exchanged evidence and locating information relevant to litigation.
How deep it goes
Defines discovery and sketches document-search and LLM-assisted analysis without detailing legal procedures or implementation.
Examples
Uses thousands of exchanged documents, term searches, document summaries, and evidence supporting a legal argument as examples.
What you can do after
Evaluate potential uses of e-discovery software and LLMs for organizing documents and finding litigation-relevant evidence.

Read how Introduction to Generative AI, Second Edition explains discovery →

Related concepts

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.