Java Development CompanyJVM · SPRING
Few teams choose Java for the syntax. They choose it because a typed codebase, long support windows and profilers that tell you the truth are what a system needs once the people who wrote it have moved on.
Spring Boot · Java 21
RUNNINGWhy the JVM
Java's reputation for verbosity is largely earned. What the verbosity buys is a compiler that removes a whole class of mistakes before anything ships, and a codebase a new engineer can navigate by types and call hierarchies alone. That matters far more in year six than in week two.
Spring is the other half of the argument. Dependency injection, transaction boundaries, security filters and data access are settled problems with conventions most Java engineers already carry with them, so a service written by someone who has since left is still readable. The cost is a framework with real depth — Spring rewards teams who learn where the magic actually happens, and bites the ones who don't.
The platform also moves slowly on purpose. LTS releases carry patches for years, JFR and async-profiler answer performance questions with data instead of opinion, and virtual threads in Java 21 let blocking code scale without a reactive rewrite. That is why Java keeps showing up wherever a system has to be maintained rather than replaced.
Long-term support release
Core stack
Java Services
Server-rendered apps and JSON back ends on Spring MVC, or WebFlux where the traffic pattern justifies it. Sessions, CSRF, auth and templating come from parts of the framework that have been hardened for years, so the effort goes into the domain instead of the plumbing.
Greenfield services where the business logic is the hard part — pricing, rules engines, scheduling, settlement. Typed domain models and a test suite you can trust in CI are the deliverable; the repository and the build are yours from the first commit.
Systems with many callers and no appetite for surprises: ERP and CRM back ends, internal platforms, multi-tenant services. The difficulty is transaction boundaries, idempotency and the audit trail — not the framework you pick to hold them.
A lot of working software still runs on EJB, JMS and an application server, and a rewrite is rarely the cheapest answer. We keep those systems supported, move them across the javax-to-jakarta namespace break, and modernise only the parts that actually hurt.
Content platforms, document workflows and publishing back ends written in Java: versioned content models, workflow states with real approvals, search indexing, and rendering that holds up as the catalogue grows.
Java is still first-class on Android, and most mobile teams need a back end more than they need another SDK. We build both sides: the app in Java or Kotlin, and the Spring services behind it handling auth, sync, push and offline conflicts.
Java 8 to 21, Spring Boot 2 to 3, monolith to services where it genuinely pays. The work happens incrementally behind a facade, with the old path still serving traffic until the new one has proved itself in production.
A 30-minute call with an engineer who will read the code before proposing a rewrite.
What the JVM gives you
Java is not the quickest language to prototype in, and nobody picks it for elegance. It wins on the unglamorous axes — types, tooling, patch windows — and those are the ones that decide whether a system survives its fifth year.
Spring Security handles authentication, authorisation, CSRF and session fixation with defaults that have survived a lot of scrutiny. The JVM's cryptography APIs are old enough that the sharp edges are documented rather than discovered in production.
The JIT compiles hot paths against real profiles, so a long-running JVM is quicker than its first minute suggests. The trade is a slow start — which is why CDS or a GraalVM native image is worth it when cold-start time actually matters.
The same JAR runs on a laptop, a build agent and a production node. Containers made that less remarkable than it once was, but it still removes an entire category of environment drift.
Explicit types turn refactoring into a mechanical operation rather than search-and-hope. An IDE renames safely across a large codebase, and the compiler catches the call site you missed — not a test failing at 3am.
JFR, async-profiler, heap dumps, JMH, Testcontainers. Performance and memory questions on the JVM end in evidence, and that is not true of every runtime.
Virtual threads let ordinary blocking code hold a very large number of in-flight requests, which removes most of the reason teams adopted reactive stacks — along with the debugging pain those brought with them.
Maven Central covers most of what a back-office system needs, with libraries maintained for a decade or more. The flip side is dependency weight, so we keep the tree pruned and watch CVEs instead of pretending it is free.
LTS releases keep taking security patches long after release, so upgrades can be planned around your roadmap. Deferring them indefinitely is what turns a routine bump into a project — the javax-to-jakarta break being the obvious example.
Why Choose Aryavos
People who have chased a memory leak through a heap dump and sat through a GC pause in a live incident, not just read about generational collection. That shows up in the design decisions, long before it shows up in the code.
We would rather stand up a facade and move one endpoint at a time than schedule a rewrite that lands all at once. Slower on the plan, far less likely to end badly.
Records, sealed types, pattern matching and virtual threads when they make the code simpler; the boring construct when they don't. New syntax is not a reason to narrow the set of people who can maintain the system.
Support scope is agreed per engagement, with the people who wrote the code answering the ticket rather than a first line working from a script.
Hourly, part-time, full-time, embedded in your team or running a workstream on your behalf. Scope and rate are agreed before anyone opens an editor.
NDA, source ownership and access are settled before work starts. Code lands in your repository from the first commit, and the build has to be reproducible without us.
Incremental delivery · Flexible engagement · Your repository, your IP
How the work runs
Five stages. The durations are what each phase usually takes on a new build — work on an existing codebase starts at stage one regardless, reading the code.
We start from the constraints: what the system integrates with, what the data actually looks like, and what your operations team can realistically run. The stack argument only makes sense afterwards — Spring Boot services, a modular monolith, or leaving a working J2EE core in place and building around it.
Key Deliverables
Java front ends usually mean tables, filters, bulk actions and long forms. We design against the real record shapes and the real permission model, so the screens still work in the first week with production-sized data behind them. Keyboard paths and accessibility are designed in, not retrofitted.
Key Deliverables
Development runs in sprints against a build that stays releasable. JUnit and Mockito for unit tests, Testcontainers where a real database is the only honest fixture, and a Maven or Gradle pipeline that runs the lot on every commit. A suite slow enough that people skip it is a defect, and we treat it as one.
Key Deliverables
Load tests with JMeter or Gatling against production-shaped data, a pass over the OWASP list, and a release plan that can be undone. Deployment to containers or to the application server you already run — blue-green or canary, with the previous version reachable until the metrics say otherwise.
Key Deliverables
Monitoring with dashboards someone can actually read, JVM and GC tuning driven by flight recordings rather than folklore, dependency and CVE patching, and LTS upgrades taken on a schedule instead of when a security bulletin forces the issue.
Key Deliverables
Where Java lands
Java rarely gets chosen for the demo. It gets chosen for the system underneath — the one with money, records or devices on the other side of it.
Account hierarchies, territory rules and activity histories that only ever grow. The hard parts are the permission model and keeping list views fast once a customer has ten years of records behind them.
Device registries, MQTT or AMQP ingestion, and a time-series store that survives a whole fleet reporting on the same schedule. Java carries the sustained throughput; the design work goes into back-pressure and out-of-order data.
Ledgers, reconciliation and payment flows where a retried message must not become a second charge. Idempotency keys, exactly-once handling at the boundary, and an audit trail that can reconstruct any balance on request.
Catalogue, pricing, promotions and checkout under traffic that arrives in spikes. Inventory correctness under concurrency is the part that bites — optimistic locking and reservation windows rather than hope.
Feeds, follows and notifications sitting next to transactions. The fan-out strategy is the decision that determines whether the system scales or falls over at an entirely predictable size.
Multi-vendor catalogues, commission and payout logic, split settlements and vendor-facing reporting. Money moving between three parties is where the edge cases live.
ERP, SCM and HR platforms with long-lived records, multi-tenancy and reporting duties. Designed to support the retention and access rules agreed for your sector, with the audit trail built in rather than bolted on.
REST or gRPC APIs behind iOS and Android clients: token refresh, push, versioned endpoints, and sync rules that reconcile a phone which has been offline for a week.
Spring Boot behind REST or GraphQL, serving a React or Angular front end — or rendering server-side where that is simply less machinery. The interesting decisions are caching and session strategy, not the framework.
JavaFX or Swing tools for trading desks, labs and operations floors: places where a browser is not an option and a keyboard-driven interface beats a good-looking one.
Nightly runs, file transfers and message-driven integrations — the unglamorous jobs that quietly carry the business. Restartability, poison-message handling and knowing exactly which rows failed matter more than raw throughput.
Frequently Asked Questions
The questions engineering leaders actually ask before starting a Java project with us. Have others? Ask a Java engineer.
The problem, who it's for, and where you are now. That's enough for us to come back with something useful.
hello@aryavos.com
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What happens after you send it
A developer reads it, not an auto-responder. Expect questions about scope and constraints first, then a suggested way to start.
