DZone Refcard #247, “Getting Started With Spring Boot and Microservices,” is a historical introduction to the architectural problems that appear when Java applications are split into independently deployed services. Its practical themes remain useful—shared state, asynchronous work, security, deployment, data evolution, and health monitoring—but its Hazelcast IMDG examples and Spring Security APIs are not a current setup guide. Treat them as design illustrations, then check documentation for the exact versions you plan to run.
What the Refcard covers
Written by Neil Stevenson, identified on the page as a Solution Architect at Hazelcast, the Refcard presents Spring Boot as a way to package and run standalone Java applications and Hazelcast IMDG as a distributed, in-memory data grid. It uses an online shop to show why independently deployed services need to share some information and coordinate some work. Read DZone Refcard #247.
The point is not that every microservice needs a data grid. It is that splitting an application into services changes where state lives, how work is handed off, and how the system is operated. Those choices should be explicit.
How the shopping example reveals the main design choices
Share state without relying on one service instance
If a customer’s basket exists only in the local memory of one basket-service instance, later requests must reach that same instance or the state must be lost. Request affinity can route requests to the same instance, but it ties access to that instance. A shared store or distributed data grid can make the basket accessible to multiple service instances, at the cost of introducing shared infrastructure and its own capacity, availability, and operational requirements.
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Separate checkout work from the request path
Checkout can involve payment, dispatch, and email. A synchronous chain makes the caller wait for downstream responses and makes progress depend directly on those services being reachable in time. With queued or published messages, work can be processed later and individual consumers can recover or catch up independently. Asynchrony changes timing and availability dependencies; it does not eliminate the contract between producer and consumer. Both still need to understand the message format and its meaning.
Distinguish identity from permission
A user may have one authenticated identity across an application while different services enforce different authorization rules. Being signed in does not automatically grant access to every operation. The Refcard illustrates shared sign-in alongside distinct service permissions, but its Spring Security configuration is from an older API era; do not copy it into a current application without checking the documentation for the Spring Security version in use.
Rank #2
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Choose where the data grid runs
The Refcard contrasts embedding a grid in service processes with connecting services to a separate client-server grid. Neither topology is universally preferable; the right choice depends on whether deployment simplicity or independent scaling and operational separation matter more.
| Consideration | Embedded grid | Client-server grid |
|---|---|---|
| Deployment and process count | Can simplify deployment by keeping the grid with service processes, but each service process also carries grid concerns. | Adds separately operated grid processes and connections to manage. |
| Scaling service compute and data capacity | Service replicas and grid capacity are more closely coupled when they share processes. | Allows service replicas and grid capacity to scale independently. |
| Separation of concerns | Service and grid responsibilities share a process. | Separates the service processes from the data-grid tier. |
| Upgrades and resilience | Changes to service processes can affect the embedded grid members and vice versa. | Provides a distinct tier to manage, though it also adds infrastructure that must be monitored and kept available. |
The Refcard illustrates grid growth by adding two processes to a ten-process grid: it describes each process’s share changing from one-tenth to one-twelfth and calls that a 20% capacity increase. This is an illustrative calculation in the Refcard, not a measured guarantee of real-world throughput or usable capacity.
Rank #3
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Plan deployment and operations as the service count grows
Spring Boot’s appeal in the Refcard is the ability to package an application as a bootable unit rather than requiring a separately managed application-server deployment. The current Spring Boot overview still documents executable JARs as well as traditional WAR deployments. A convenient deployment unit does not remove the work of operating many services: each process adds configuration, logs, health signals, upgrades, and failure modes to track.
For current implementation details, use the official Spring Boot system requirements and reference documentation for the version you select. At the time covered by the supplied current-version information, Spring Boot 4.1.1 was listed as stable and required Java 17 or later, Spring Framework 7.0.9 or later, Maven 3.6.3 or later, and Gradle 8.14+ or 9.x. These version facts can change; verify them before starting a new project.
Rank #4
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Make data changes compatible with rolling evolution
Services and their stored data rarely change all at once. During a rolling deployment, old and new application instances may run at the same time, so a data-format change that only one version understands can break the other. The Refcard advocates version-aware data evolution as a way to handle change, but its named Hazelcast API is historical. Decide how readers and writers will handle old and new formats, and consult current Hazelcast documentation for supported mechanisms and product-version compatibility rather than assuming the older API still applies.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use health and metrics endpoints deliberately
Monitoring matters more as service count increases, but endpoint names and exposure rules are version-specific. The Refcard’s /health and /metrics paths should not be treated as current Spring Boot defaults. Spring Boot documents Actuator as its production-ready monitoring and management feature set, and lists spring-boot-starter-actuator as the starter. Its current metrics documentation describes /actuator/metrics; that endpoint is not available by default and must be exposed. Choose exposure and access controls deliberately rather than assuming operational data should be public.
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For current starter names, Spring Boot’s documentation lists spring-boot-starter-hazelcast for Hazelcast integration and spring-boot-starter-actuator for monitoring and management. Those names do not establish that a particular Hazelcast release is compatible with Spring Boot 4.1.1. Confirm the supported combination and current configuration guidance in Hazelcast’s documentation before adopting the integration.
A practical way to apply the ideas
- Map the state. Identify which service owns each piece of data, which other services need it, and whether local state, a shared store, or a data grid best fits the access and availability needs.
- Choose communication per interaction. Use a synchronous request when the caller needs an immediate answer; use queued or published work when deferred processing and reduced timing dependence are useful. Define and evolve message schemas deliberately.
- Keep identity and authorization separate. Establish how services receive and validate identity, then define permissions for each service operation using the APIs supported by your framework version.
- Pick topology based on scaling boundaries. Prefer embedding when a simpler deployment is worth coupling service and grid processes; consider client-server when compute replicas and data capacity need to scale independently.
- Design for mixed-version operation. Make rolling upgrades safe for both stored data and messages, and test how old and new instances behave during the transition.
- Operate services as a system. Set up health and metrics collection, logging, alerting, and controlled endpoint exposure for the versions actually deployed.
Where to continue learning
The Refcard is offered as a free PDF and is useful for its architectural framing, not as a current API reference. For implementation, rely on the versioned Spring Boot requirements and reference pages, the current Hazelcast documentation for compatibility and topology, and the documentation for the Spring Security version in use. A book-length option, Beginning Spring Boot 2: Applications and Microservices with the Spring Framework, is explicitly scoped to Spring Boot 2 and should be treated as historical learning material rather than guidance for the current Spring Boot release.
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