Infinispan Embedded Extension blog post (#2199)

Author: karesti

_posts/2024-12-18-quarkus-infinispan-embedded.adoc

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+---
+layout: post
+title: 'Quarkus Infinispan Embedded extension'
+date: 2024-12-18
+tags: infinispan cache library
+synopsis: 'Quarkus Infinispan Embedded extension release'
+author: karesti
+---
+
+We are excited to announce the first release of the Quarkus Infinispan Embedded Extension!
+This extension is now available in the Quarkiverse Hub. It is a big step forward for developers
+who want to use Infinispan in embedded mode with Quarkus.
+
+== What is Infinispan Embedded Mode?
+
+Infinispan is a powerful, distributed in-memory data store and cache.
+In embedded mode, Infinispan runs within your application, in library mode, without needing a separate server.
+This means your app can handle data caching and storage directly in its own process, making it faster and simpler.
+
+== Why Use the Quarkus Infinispan Embedded Extension?
+The new extension makes it easy to use Infinispan with Quarkus requiring minimal setup and
+delivering fast in-memory performance to your Quarkus apps.
+
+== Use cases for Infinispan Embedded in Quarkus
+Here are some scenarios where using Infinispan in embedded mode with Quarkus might be a great fit:
+
+*In-Memory Caching:* Use Infinispan as a local cache to speed up data retrieval and
+reduce database load in your application.
+
+*Temporary Data Processing:* Manage and process temporary or short-lived data directly within
+the application.
+
+*Local Data Storage for Microservices:* Use Infinispan as a lightweight,
+in-memory store for individual microservices that don’t require centralized data persistence.
+
+*Offline Applications:* When working with offline or edge applications where an external server is not available,
+Infinispan embedded mode ensures data is stored locally and efficiently.
+
+*Data Replication in Small Clusters:* Use Infinispan to handle data replication across a few nodes
+without the overhead of a separate Infinispan server.
+
+== Trade-offs of Using Infinispan in Embedded Mode
+While running Infinispan in embedded mode offers simplicity and speed, there are some trade-offs to consider.
+Since Infinispan runs within your application's process, it shares the same memory and CPU resources.
+This can increase your application's resource usage, especially as the data size grows.
+Additionally, embedded mode is best suited for single-node or small-scale deployments; for larger, distributed systems,
+using Infinispan in remote mode with a dedicated server may offer better scalability and separation of concerns.
+
+=== Infinispan Embedded and Kubernetes deployments
+When running applications on Kubernetes, using Infinispan in embedded mode can introduce additional challenges.
+For instance, scaling an embedded Infinispan setup requires scaling the entire application pod, which may not be
+as efficient as scaling an external Infinispan cluster independently.
+Kubernetes' ability to handle distributed workloads aligns better with remote Infinispan setups, where storage
+and application layers can scale separately for improved resource management.
+
+For more information, check the https://infinispan.org/docs/stable/titles/tuning/tuning.html[performance and tuning guides]
+in the official Infinispan documentation.
+
+== How to get started
+Getting started is very easy. Just add the dependency to your Quarkus application:
+
+[source, xml]
+----
+<dependency>
+    <groupId>io.quarkiverse.infinispan</groupId>
+    <artifactId>quarkus-infinispan-embedded</artifactId>
+    <version>1.0.1</version>
+</dependency>
+----
+
+Then you can Inject the `EmbeddedCacheManager` and interact with Infinispan.
+
+[source, java]
+----
+@Inject
+private EmbeddedCacheManager cacheManager;
+----
+
+To enable Protobuf serialization, you define a schema like this:
+
+[source, java]
+----
+@Proto
+public record Greeting(String name, String message) {
+    @ProtoSchema(includeClasses = { Greeting.class }, schemaPackageName = "io.quarkiverse.infinispan")
+    public interface GreetingSchema extends GeneratedSchema {
+    }
+}
+----
+Using the `EmbeddedCacheManager` you will be able to create caches on the fly.
+
+[source, java]
+----
+Configuration config = new ConfigurationBuilder()
+                .encoding().mediaType(MediaType.APPLICATION_PROTOSTREAM)
+                .clustering().cacheMode(CacheMode.DIST_ASYNC).build();
+
+// Create a cache
+Cache<String, Greeting> cache = cacheManager.administration()
+.withFlags(CacheContainerAdmin.AdminFlag.VOLATILE)
+.getOrCreateCache("mycache", config);
+
+// Put a value in the cache
+cache.put(id, greeting);
+
+// Read a value from the cache
+cache.get(id);
+----
+
+== Native Support and Future Features
+
+The Quarkus Infinispan Embedded Extension supports native mode, but some advanced
+features may be limited. We encourage developers to test it, share feedback, and help us enhance its
+capabilities.
+
+== Where to Learn More
+
+For detailed documentation and examples, check out the project in the Quarkiverse Hub:
+https://github.com/quarkiverse/quarkus-infinispan-embedded[Quarkiverse Infinispan Embedded Extension]
+
+== Come Join Us
+We welcome your feedback and contributions to improve the extension. Feel free to open issues, suggest features,
+or contribute code on the project’s GitHub repository.
+Thank you for being part of the Quarkus community. We hope you enjoy the new Infinispan Embedded Extension!
+If you are a Quarkus user or just curious, don't be shy and join our welcoming community:
+
+ * provide feedback on https://github.com/quarkiverse/quarkus-infinispan-embedded/issues[GitHub issues];
+ * craft some code and https://github.com/quarkiverse/quarkus-infinispan-embedded/pulls[push a PR];
+ * ask your questions on https://github.com/quarkiverse/quarkus-infinispan-embedded/discussions[GitHub discussions].
+ * discuss with us on https://infinispan.zulipchat.com/[Infinispan Zulip], https://quarkusio.zulipchat.com/[Quarkus Zulip] or on the https://groups.google.com/d/forum/quarkus-dev[mailing list];