Axelix: the agentic platform for Spring Boot in production

Seewhich property value won, and where it came from

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Install with your AI agent

01What AI changed

AI ships more code, faster. Production pays for it.

The 2025–2026 research points the same way: more incidents per change, lower code quality, and a record number of vulnerabilities in the libraries we depend on.

01 · Incidents

3.4×

more production incidents per merged PR in teams with high AI adoption. Monthly incidents rose 57.9%.

Faros AI Engineering Report 2026 · 22,000 developers ↗

Incidents per PR up 23.5% and change failure rate up about 30% year over year. Cortex Engineering Benchmark 2026 ↗

02 · Quality

1.7×

more issues in AI-authored pull requests. Performance problems such as excessive I/O appeared nearly 8× more often.

CodeRabbit, State of AI vs Human Code, Dec 2025 ↗

AI adoption continues to have a negative relationship with software delivery stability. DORA 2025 · ~5,000 professionals ↗

03 · Vulnerabilities

59k

CVEs forecast for 2026, the first year above 50,000. 2025 closed at a record 49,972.

FIRST Vulnerability Forecast 2026 ↗

A growing share of software depends on end-of-life releases that receive no patches, so their vulnerabilities become permanent. Sonatype SSCR 2026 ↗

Axelix does two jobs, from one install and one console.

02Stop known issues before they shipCatch known anti-patterns in your code, configuration, dependencies and JVM setup before they reach production.See how ↓03Find the cause of incidents fastLook inside the running service with your AI agent and find the root cause without a redeploy.See how ↓

02Known issues detection

Problematic code does not reach production.

Axelix knows the patterns that cause incidents in the Spring stack. It reads every layer of the service, from code and configuration to dependencies, points to the exact line and stops the release, whether a human or an AI agent wrote the code.

Code · Order.java

Mappings that look fine and break under load.

JPA and Lombok shortcuts pass code review and show up in production as extra queries, lost rows and slow writes.

1

@Data on a JPA entitywarning

Generated equals, hashCode and toString touch lazy associations and trigger extra queries.

2

CascadeType.ALL on @OneToManyblocker

Includes REMOVE: deleting an order silently deletes every line. Cascade only PERSIST and MERGE.

3

List on @ManyToManyblocker

A List is a bag: removing one tag deletes all join rows and re-inserts the rest. Use a Set.

src/main/resources/application.yml3 findings · 2 blockers

1spring:

2 application:

3 name: orders-service

4 datasource:

5 url: jdbc:postgresql://db:5432/orders

6 jpa:

1 show-sql: true

8 properties:

9 hibernate:

2 enable_lazy_load_no_trans: true

11management:

12 endpoints:

13 web:

14 exposure:

3 include: "*"

src/main/java/com/acme/orders/Order.java3 findings · 2 blockers

1@Entity

1@Data

3@Table(name = "orders")

4public class Order {

5

6 @Id

7 @GeneratedValue

8 private Long id;

9

2 @OneToMany(cascade = CascadeType.ALL)

11 private List<OrderLine> lines;

12

13 @ManyToMany

3 private List<Tag> tags;

15}

Configuration · application.yml

Settings that work on a laptop.

Common properties that make development easier and cause trouble in production.

1

show-sql: truewarning

Prints every statement to stdout, bypassing your logging setup and flooding logs under load.

2

enable_lazy_load_no_transblocker

Each lazy access outside a transaction opens a new session and connection. Hides N+1 queries and exhausts the pool.

3

exposure.include: "*"blocker

Publishes heapdump, env and threaddump over HTTP. A heap dump holds credentials and user data.

03Live debugging with AI agents

Debug the live service. Cut mean time to recovery.

When an incident hits, look inside the running application: beans, effective configuration, live transactions, loggers, thread dumps and GC. Engineers use the web console; AI agents get the same data through the embedded MCP server, under one role model.

✓Inspect beans, effective configuration, transactions, threads and GC of the running service
✓Change log levels and caches live, without a redeploy
✓Give AI agents the same view through the built-in MCP server

claude code · payments-serviceaxelix mcp connected

>

Open source or Enterprise?

The open-source core is free under LGPL-3.0. Enterprise is a drop-in distribution that adds control at scale.

Compare editions →Get started free

04Install

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)# Uses the built-in JWT key: fine for a trial, set your own for productiondocker run \    --publish 2935:2935 \    --name axelix \    --detach \    ghcr.io/axelixlabs/axelix:

Step 1 of 4

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

05FAQ

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 requires 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 →