Make sure your Java microservices are ready for the AI era.

The AI-Native, Open Core solution for the AI era: its open-source core pinpoints what holds your Java back, while Axelix Enterprise enforces optimization policies across the whole ecosystem. At scale.

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Built for

Production

not only sandbox envs

Exposed to

Humans & agents

same RBAC, same audit

Install

Fast setup

docker · helm · Jar

what does Axelix offer?

Axelix provides vital insights for Java apps. Apply them, and watch your service change

LanguageJava 25

FrameworkSpring Boot 3.5

PersistenceSpring Data JPA · Hibernate

DatabasePostgreSQL

MessagingApache Kafka

BuildGradle

No massive rewrite, no new framework. Just apply the suggestions Axelix provides (either manually, or with AI Agents with the help of an embedded MCP server) to a regular Java Spring Boot application and watch the results.

How exactly?

No magic. Axelix pinpoints the real problems, on various layers

Every gain above starts with a concrete problem Axelix detected and surfaced: from the JVM up through the framework and into the data layer. The examples below are simplified, yet they generally reflect the real-world conditions based on our experience.

01 JVM Deployment level

Runtime Pitfalls

Inefficiencies that cost a lot at scale

The Dockerfile on the right does not use Project Leyden. Project Leyden alone can contribute 15-30% of RSS footprint drop, and reduce startup time by 40-50%. Axelix detects that.
Axelix will detect, that the app on the right is using Java 25. In Java 25, the Compact Object Headers feature is a stable production ready way to reduce the heap size by up to 20%. However, it is not enabled by default in Java 25 - Axelix will tell you about that.
The way most Docker images are built (the one on the right is not an exception) is by copying the fat jar into the image and use Spring Boot's URL classloader. That significantly increases the image size, along with the startup time.
Application on the right does not arrange any GC logging setup. Configuring GC logging is vrey important for overall performance analysis. Axelix will detect that.

Dockerfilesuboptimal

FROM eclipse-temurin:25-jdkUSER app:app
WORKDIR /app
COPY target/orders.jar app.jar
ENV JAVA_OPTS="-Xmx512m -X..."ENV TZ=America/Los_Angeles
ENTRYPOINT ["sh", "-c", "java $JAVA_OPTS -jar app.jar"]

02 Code Level

Enterprise Anti-Patterns

Access patterns that break under load

The iteration over retrieved Orders and subsequent "getLineItems()" causes the N + 1 problem. Axelix can detect that and make sure it is known by the team.
The Spring's "RestClient" will perform an HTTP network call, which is going to cause the currently active thread to go to interruptible sleep. The thread is also holding the connection open, which will lead to connection pool exhaustion. More importantly, such pattern invites hard-to-detect bugs and can cause inconsistency between systems because of the distributed data change. Axelix can detect those and will help you make sure such problems are gone.
Up until Hibernate 7.4 (and most deployments od not use Hibernate 7) queries with Spring Data's Pageable and JOIN FETCH caused the Hibernate to fetch all the records into memory, and then paginate in-memory. That is generally extremely bad, since it explodes the Java heap and introduces sever latency. To be clear - Hibernate itself issues a warning about that, but it cannot fix it for you. Axelix will detect that.
By default, @ManyToOne and @OneToOne relations are fetched eagerly. There were hopes that JPA 4 will change the fetch types, but it did not (for backward compatibility purposes). Still, a lot of applications suffer from EAGER fetching, and it was, as noted by the Hibernate team themselves, was a historical mistake. Axelix will help you to keep that technical debt under control.

OrderService.javaquiet time-ticking bomb

@Transactional(readOnly = true)public  Page<OrderSummary> recentOrders(Filter filter, Pageable page) {
  return orderRepository.findAll(OrderSpecs.matching(filter), page)    .map(order -> {      var items = order.getLineItems();         var fx = pricingClient.get()          .uri("/fx/{ccy}", order.currency())          .retrieve().body(FxRate.class);      return orderMapper.toSummary(order, items, fx);    });}

03 Application Configuration Level

Configuration Problems

Defaults that quietly cost you, surfaced.

This is probably one of the most dangerous default that Spring Boot applications have. It is enabled by default just for quickstart, but a lot of deployments still have it in production. OSIV leads to connections leaks, unexpected lazy loading and so on. For production systems, it absolutely must be turned off. Axelix will help you ensure that.
By default, for backward compatibility purposes, Virtual Threads are not enabled in Spring Boot apps. Still, at least since Java 24 they absolutely must be adopted by the Spring Boot applications. They generally significantly improve throughput without requiring the application re-write. Axelix will help you to keep track that the entire ecosystem adopted Virtual Threads.
There are a lot of bad properties that people still use in production for various purposes, and spring.jpq.show-sql=true is one of them. It is bad, since it arranges the synchronous output to stdout, which bypasses the logging system and degrades performance. There are other, more reliable and safe ways to log SQL queries.
This is one of the most common security breaches into Spring Boot applications. Although it is very compelling to use "*" as the value for the exposed endpoints, it also brings as security risk, such as that any library that introduces previously unknown Actuator endpoint to the classpath will automatically be exposed, which can easily lead to sensitive data leakage, or even RCE vulnerability.

application.ymlmisconfigured

spring:  jpa:    open-in-view: true    show-sql: true
management:  endpoints:    web:      exposure:        include: "*"

Debugging

Secure Spring Boot Runtime Debugging for both Humans & AI Agents

Axelix also allows you to look inside the living Spring Boot application - see its beans, properties, transactions, loggers and so on. Every capability listed below is exposed twice. Engineers reach it through a web console. AI agents get the same information through an embedded MCP server. A single role model gates both - each identity, human or agent, sees only the data and actions its role permits.

Web·MCP

Transactional inspection

Live transactions, durations, the SQL timeline of each one — the verbs your APM forgot.

Web·MCP

Configuration properties

Effective values for every @Value and bound prefix — and where they actually came from.

Loggers

Flip log levels per package, live — no redeploy, no SSH, fully audited.

org.hibernate.SQLtrace

o.s.webinfo

com.acme.svcdebug

Web·MCP

Beans & conditions

The live bean graph plus the @Conditional verdicts — why each bean is here, or isn't.

Web·MCP

Environment

Every env source the JVM sees, ranked by precedence — with selective masking.

Web·MCP

Caches

Cache managers, hit/miss rates, evict and clear — from a button or a tool call.

Web·MCP

Thread dump

Threads, states, locks and contention — on demand, no kill-switch required.

Web·MCP

Garbage collector

Live GC events, pause times and tuning signals — not just a chart, a feed.

Web·MCP

Scheduled tasks

Inspect cron and fixed-delay tasks; toggle, force-run, or rewrite expressions live.

Web·MCP

Conditions

Auto-configuration matched and not-matched, with the reason for every verdict.

Web·MCP

Instance details

Service metadata, build info, runtime version — the boring stuff you need at 3 AM.

Web·MCP

Diagnostic export

One-click bundle of dumps, beans, configs and conditions — for incidents and audits.

Install

Install Axelix Master. Add library & plugin - that's all you need

Pick how you run things - Docker Compose, Kubernetes or even on just VMs or bare metal. Install the Axelix Master, drop the starter and plugin into your app. The installation is intentionally very simple and requires very small amount of configuration.

Shell

# Run the docker image (optionally pulls an image)docker run \    --publish 8080:8080 \    -e AXELIX_MASTER_AUTH_JWT_ALGORITHM=HMAC256 \    -e AXELIX_MASTER_AUTH_JWT_SIGNING_KEY=8DrZJSOJ8vkbxdjUB3sSsyeiG4Xidf1sDNmJq1Slkkn \    --name axelix \    --detach \    ghcr.io/axelixlabs/axelix:

Step 1 of 4

Spring Boot 2 · 3 · 4JVM 11 — 25Docker · Helm

Enterprise · early access

Open core stays open. Enterprise lives on top.

Axelix Enterprise extends the open core with the controls, integrations and support platform, security and compliance teams ask for — without forking the surface engineers already learned. The OSS keeps shipping, in the open. Enterprise is what you reach for when one cluster becomes ten and audit asks who changed what at 3 AM.

Tier 3 · Support

Dedicated support & SLA

24/7 · named engineer · priority CVE

contract

Tier 2 · Extensions

Enterprise extensions

Enforcement Policies · Advanced RBAC · Audit & Compliance

licensed

Tier 1 · Foundation

Axelix OSS

LGPL-3.0 · forever free · the same console

always open

Same surface · same MCP · one product

SSO & identity

SAML / OIDC, SCIM provisioning, group → role mapping. Plug into your existing IdP.

Granular RBAC

Per-action policies, per-service scopes, per-environment guards. One model for humans and agents.

Compliance & audit

Immutable audit log, SOC 2 / ISO 27001 evidence pack, BYO-S3 export, retention policies.

Multi-cluster fleet

Federated masters across regions, single pane of glass, region-aware routing.

On-prem & air-gapped

Offline install bundle, no telemetry, BYO container registry. For everything that can't leave the network.

Dedicated support

Named engineer, SLA, priority CVE patches, roadmap input. A vendor at the end of an email.

Early access · Q3 2026

Want a seat in the first pilots?

We're picking a handful of teams to shape what ships first. Tell us about your fleet — we'll be in touch within a working day.

enterprise@axelix.io →

FAQ

Questions, answered.

Everything you'd ask before installing it into production - license, safety, platform support, and what's next.

The open-source solution for making sure your Java Spring Boot services are efficient, secure and memory-wise. Axelix OSS is the core of the product, which is Open Source and can be found on GitHub.
First of all, Axelix is an Open Core product. Our Axelix OSS core is free of charge to use for anybody. It is available on GitHub under LGPL. Axelix OSS is designed to assist the users to locate problems.

Axelix Enterprise adds a level on top, where it allows to configure policies-as-a-code to make sure your deployments stay efficient and performant.
On the high level, it works by starter gathering certain information about your application either at boot time, or at runtime. This information is then gathered in the Axelix Master, which stores it in its database.

We care about your deployments. Thus we specifically maintain a set of benchmarks to make sure we're not introducing any runtime/performance penalties for living applications.
Axelix has built-in RBAC. For small teams, it allows to create & store users in its own local database (Axelix Master - the central Axelix component - has the database). For large teams, Axelix supports OIDC and OAuth2 for SSO - this is all available in Axelix OSS, it is free of charge.
Currently we support Spring Boot 2, 3 and 4 through dedicated starter artifacts (axelix-spring-boot-2-starter, -3-starter, -4-starter) and a specific build plugin (for Maven or Gradle, it is the same for all Spring Boot versions). The master Java 25. No JVM agent, no flags, no custom boot order.
As of now - yes. That said, we have plans to extend the support so that deployments that does not use Spring Boot could benefit from Axelix as well. That may include Quarkus/Micronaut services, or services that have their own home-grown framework.
It's designed to run in production. The master speaks to your services over an authenticated channel; a single role model gates both human engineers and AI agents - each identity sees only the data and actions its role permits. Destructive operations are explicit and confirmable.

Still curious?

Reach the team — we reply within answer working day.

Architectural questions, production-readiness checks, enterprise pilots. Anything not answered above is the kind of thing we like answering directly.

hello@axelix.io →