Backward compatibility
Backward compatibility is the property of a changed or newer system remaining usable by existing clients and consumers of its earlier interfaces, behavior, or data.
API Design Patterns
Backward compatibility is the property of a changed software interface remaining usable by previously written clients or consumers.
- How it is used
- Protects existing web API clients while services evolve through versioning.
- How deep it goes
- Defines client-server compatibility, tests semantic changes, and compares policy trade-offs, but leaves classification dependent on user expectations.
- Examples
- Uses v1-to-v1.1 traffic shifting, floating-point arithmetic, message timing, and soft deletion as compatibility cases.
- What you can do after
- Evaluate API changes against existing client behavior, user expectations, policy trade-offs, and versioning consequences.
Read how API Design Patterns explains backward compatibility →
Kafka for Architects
Backward compatibility is a schema compatibility policy in which consumers using the new schema can read messages produced with the previous schema.
- How it is used
- Enables consumer-first upgrades while producers and consumers exchange events written under different schema versions.
- How deep it goes
- Defines the policy, illustrates permitted field changes, and explains registry rejection and migration limits without a code-level implementation.
- Examples
- Uses a client-profile revision that removes age and adds a defaulted score, plus versioned-topic migration options.
- What you can do after
- Apply it via Schema Registry BACKWARD mode to assess schema changes and plan consumer-first rollouts or migrations.
Read how Kafka for Architects explains backward compatibility →
Unit Testing Principles, Practices, and Patterns
The ability of a system or communication contract to remain usable by existing external clients after internal changes.
- How it is used
- Preserves external communication contracts while allowing internal implementation changes and refactoring.
- How deep it goes
- Distinguishes inter-system from intra-system communication and specifies where mocks, spies, or no interaction verification belong.
- Examples
- Uses message-bus payloads, SMTP calls, application databases, email gateways, and a BusSpy to demonstrate stable and unstable boundaries.
- What you can do after
- Apply mocks or spies at system edges to verify externally visible message structures and calls without freezing internal collaborations.
Read how Unit Testing Principles, Practices, and Patterns explains backward compatibility →
The Design of Web APIs, Second Edition
Backward compatibility is the ability of a changed API to continue supporting existing consumers and their prior usage expectations.
- How it is used
- Protects consumers and end users while API capabilities, representations, and contracts evolve.
- How deep it goes
- Distinguishes compatible and breaking changes across data, operations, flows, and security, then connects them to versioning decisions.
- Examples
- Uses Shopping API category and price changes, transaction response schemas, transfer inputs, error models, and consumer migration scenarios.
- What you can do after
- Apply it to design safer API modifications, identify breaking changes, preserve old consumers, and choose when versioning is necessary.
Read how The Design of Web APIs, Second Edition explains backward compatibility →
Apache Kafka in Action
Backward compatibility is schema compatibility in which consumers using the current schema can read data written with older schemas.
- How it is used
- Keeps current Kafka consumers able to read historical records when a schema changes.
- How deep it goes
- Defines compatibility from the consumer’s perspective and works through field removal and rollout order, without detailing a registry configuration.
- Examples
- Uses supermarket product records to contrast removing a stock field with renaming fields.
- What you can do after
- Practice/perform a backward-compatible rollout by updating consumers before producers when removing a field.
Read how Apache Kafka in Action explains backward compatibility →
Web Components in Action
Compatibility of software with earlier browsers, platforms, or versions of a technology.
- How it is used
- Supports Web Components across browsers that lack Custom Elements or Shadow DOM.
- How deep it goes
- Builds a conditional rendering strategy, selector conversions, and a polyfill setup; defers the IE11 transpilation step.
- Examples
- Uses a color picker, a slider, CDN loading, conditional roots, class selectors, and host-context styling.
- What you can do after
- Operate/configure components that fall back from Shadow DOM while preserving rendering and styling behavior.
Read how Web Components in Action explains backward compatibility →
Terraform in Depth: Infrastructure as Code with Terraform and OpenTofu
Backward compatibility is the ability of a newer software version to preserve the behavior and interfaces expected by existing users or dependent code.
- How it is used
- Guides upgrades and release planning for shared Terraform modules whose users depend on existing interfaces.
- How deep it goes
- Explains version boundaries, constraints, tests, and reasons to bundle breaking changes, without detailing a full migration procedure.
- Examples
- Uses module changelog versions, `~> 1.1` constraints, and a Makefile switch between Terraform and OpenTofu.
- What you can do after
- Practice/perform compatible module release planning by choosing upgrade constraints, testing changes, and grouping necessary breaks.
Machine Learning System Design
The ability of new software or an interface version to support existing code or clients without changes.
- How it is used
- Preserves existing API clients while allowing machine-learning services to evolve.
- How deep it goes
- Explains compatibility through exposed outputs, layered APIs, and model versions, but stops short of a migration procedure.
- Examples
- Uses a classification endpoint that exposed a one-item label list and a layered API structure.
- What you can do after
- Apply it via stable external contracts, flexible internal implementations, and controlled component evolution.
Read how Machine Learning System Design explains backward compatibility →
Simple Object-Oriented Design: Create clean, maintainable applications
Backward compatibility is the ability of a changed software component or interface to continue supporting existing clients and usage patterns.
- How it is used
- Enables independently evolving modules to deploy interface changes without forcing all clients to update immediately.
- How deep it goes
- Defines compatible API evolution and explains coordination and request-handling tradeoffs, without prescribing an implementation strategy.
- Examples
- Illustrates versioned requests with missing fields or changed enumerated strings, plus an Invoice-to-Delivery dependency.
- What you can do after
- Evaluate/understand when an API change should preserve older clients or require advance migration notice.
Kafka Streams in Action, Second Edition
Backward compatibility is the ability of a newer software component or data schema to work with data produced using an older schema or interface.
- How it is used
- Coordinates rolling producer and consumer deployments while preserving interoperability across adjacent schema versions.
- How deep it goes
- Defines allowed field changes, default-value behavior, migration order, and transitive variants without detailing deserializer internals.
- Examples
- Uses deleted fields, added defaulted fields, mixed-version records, and a consumer-first migration diagram.
- What you can do after
- Operate rolling schema migrations by updating consumers first and validating changes with Schema Registry.
Read how Kafka Streams in Action, Second Edition explains backward compatibility →
Infrastructure as Code, Patterns and Practices: With examples in Python and Terraform
Backward compatibility is the property that a newer version continues to support interfaces, behaviors, or configurations expected by existing users or dependents.
- How it is used
- Guides incremental infrastructure-as-code tool upgrades while protecting existing configurations and production availability.
- How deep it goes
- Explains version pinning, staged resource updates, testing, rolling updates, and failure recovery, stopping short of tool internals.
- Examples
- Uses versions 1.7, 3.0, and 4.0, plus DNS, load balancers, servers, and a failing production override script.
- What you can do after
- Apply it to plan, test, stage, and safely recover from backward-compatible infrastructure-as-code tool upgrades.
The Art of Code
Backward compatibility is the ability of a changed software component or interface to continue working with existing clients and dependent systems.
- How it is used
- Guides evolution of public APIs and libraries without disrupting dependent users.
- How deep it goes
- Explains communication, deprecation, compatibility duration, and semantic versioning through policy and annotations rather than compatibility internals.
- Examples
- Uses Java, C#, Python, Kotlin, JavaScript, TypeScript, and C++ deprecation mechanisms as concrete examples.
- What you can do after
- Apply it via documentation, deprecation notices, compatibility periods, and semantic versioning when evolving public interfaces.
Learn Go with Pocket-Sized Projects
Backward compatibility is the ability of a newer software version to continue working with existing users, integrations, or client code.
- How it is used
- Preserves existing consumers while evolving Go packages and gRPC service contracts.
- How deep it goes
- Explains stable exported symbols, Protobuf field numbers, and request-response design, but stops short of migration procedures.
- Examples
- Uses a numbered Habit Protobuf message, CreateHabit request and response messages, and a Go logger package.
- What you can do after
- Apply it by designing stable Protobuf schemas, dedicated gRPC messages, and carefully controlled exported Go APIs.
Read how Learn Go with Pocket-Sized Projects explains backward compatibility →
Practices of the Python Pro
Backward compatibility is the ability of a newer software version to preserve compatibility with earlier interfaces, data, or behavior.
- How it is used
- Guides refactoring that separates responsibilities without immediately forcing consumers to update their code.
- How deep it goes
- Defines the practice, explains forwarding through an analogy, and demonstrates it with Python class properties and deprecation warnings.
- Examples
- Uses post-office mail forwarding and a Book-to-Author extraction with preserved properties.
- What you can do after
- Apply it by forwarding old interfaces to extracted classes and warning consumers about preferred replacements.
Read how Practices of the Python Pro explains backward compatibility →
Troubleshooting Java, Second Edition
Backward compatibility is the ability of a newer consumer or implementation to process data produced according to an older schema.
- How it is used
- Protects independently evolving services from breaking data-contract changes.
- How deep it goes
- Explains common mismatch symptoms and schema-evolution concerns, but stops short of a compatibility checklist or implementation procedure.
- Examples
- Uses added JSON fields, renamed Protobuf enums, optional fields, and Java version-UID mismatches as failure scenarios.
- What you can do after
- Diagnose compatibility risks by examining schema changes, ignored fields, default values, and deserialization errors.
Read how Troubleshooting Java, Second Edition explains backward compatibility →
Designing Deep Learning Systems: A guide for software engineers
The property of a system or data interface that allows newer changes to remain usable by existing consumers and projects.
- How it is used
- Protects existing model-training projects and dataset clients while upstream data collection evolves.
- How deep it goes
- Explains typed schemas, transformation boundaries, versioning, and new dataset types for breaking changes.
- Examples
- Uses separate ingestion and training schemas, schema enforcement, and new dataset types for incompatible requirements.
- What you can do after
- Operate a dataset management boundary that absorbs compatible data changes and isolates breaking changes.
gRPC Microservices in Go
Backward compatibility is the ability of a changed system to continue supporting existing users, integrations, or clients without requiring them to upgrade.
- How it is used
- Guides safe evolution of client-facing gRPC and protocol buffer APIs without forcing existing users to upgrade.
- How deep it goes
- Explains field numbering, reservations, type changes, and oneof data loss, but stops short of a broader migration procedure.
- Examples
- Uses CreateOrderRequest reservations and a CreatePaymentRequest change that moves promo_code into a oneof.
- What you can do after
- Evaluate protocol buffer message changes for field reuse, type conflicts, reservations, and oneof-related data loss.
Read how gRPC Microservices in Go explains backward compatibility →
Automating API Delivery
API compatibility is the ability of an API client application and API server to communicate successfully across a change.
- How it is used
- Guides API evolution while protecting consumers from changes that disrupt client-server communication.
- How deep it goes
- Defines compatibility and demonstrates automated path-removal checks, while treating planned sunsets as a special case.
- Examples
- Uses removal of GET /v1/catalog/categories and an oasdiff comparison as examples.
- What you can do after
- Diagnose API-definition changes with oasdiff by comparing versions and identifying removed paths.
Read how Automating API Delivery explains backward compatibility →
Related concepts
- breaking changecontrasts with · A breaking change is a modification to an interface, behavior, format, configuration, or contract that can prevent existing consumers from working correctly without changes.
- schema registryused by · A schema registry is a service that stores, versions, and provides schemas for structured data, often validating compatibility between schema versions.
- forward compatibilityincludes · Forward compatibility is the ability of older software, interfaces, or schemas to tolerate and interoperate with supported changes introduced by newer versions.
- Mapused by · A map is an associative data structure that stores key-value pairs and supports retrieving values by key.
- PostgreSQLused by · PostgreSQL is an open-source object-relational database management system that implements SQL and supports transactional data storage and extensibility.
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.