Java developers modernise long-lived enterprise systems: upgrading from Java 8 or 11 to a current long-term support release, migrating Spring Boot across major versions including the package namespace change, moving off application servers into containers, and tuning JVM memory and garbage collection. Most Java engagements are modernisation rather than new development.
The typical Java system we are asked to work on runs critical operations, was written eight to fifteen years ago, sits on a version that no longer receives free security updates, and has no original authors available. That is a modernisation problem rather than a development problem. TechEsperto Solutions treats it accordingly.
Systems written for it stay in production for a very long time, which means the installed base is dominated by applications built against practices from a decade ago. Meanwhile the language and platform moved substantially, security support ended on versions still widely deployed, and the framework ecosystem introduced a package namespace change that affects almost every dependency. Rewriting is tempting and usually more expensive than upgrading, because the undocumented business rules live in the code. TechEsperto Solutions places developers who upgrade rather than restart.
Our engagements cover version upgrades to a current long-term support release, Spring Framework and Spring Boot major upgrades including the namespace migration, application server to container moves, JVM performance and memory analysis, build tool modernisation, and adding test coverage to systems that have none. Almost all of it is on applications that must keep running throughout. Clients comparing routes review our Java development services alongside hiring developers directly.
Sequential upgrades with dependency compatibility assessed first, removed APIs replaced deliberately, and the application deployable at every step rather than broken for the duration.
Recent major versions require a current Java release and moved the enterprise package namespace, which affects most dependencies. Handled as distinct steps rather than one combined change.
Moving from a traditional server deployment to a self-contained service in a container, with configuration externalised, memory limits set correctly, and health endpoints added.
Garbage collection log analysis, heap dump investigation, thread dump review for contention, and collector selection based on measurement rather than on general advice.
Migration from older build systems onto a current tool with reproducible builds, dependency locking, and reasonable build times. Frequently the prerequisite for everything else.
Characterisation tests capturing existing behaviour before any change, so an upgrade can be verified rather than hoped for. This is what makes modernising a documentation-free system safe.
Assessment for this work tests platform depth rather than language syntax. The valuable skills are reading a garbage collection log, interpreting a heap dump, resolving classpath and module conflicts, working through a namespace migration across dozens of dependencies, and reasoning about thread pool sizing. Container and deployment work is frequently staffed alongside our cloud consulting team.
The enterprise package rename affects servlets, persistence, validation, and messaging across the dependency tree. Working through it requires patience and a systematic approach rather than search and replace.
Choosing between collectors based on heap size, pause tolerance, and throughput requirements, then tuning against measured behaviour. Copied flags from an internet post are the most common cause of poor performance.
Reading a heap dump to find what is retaining memory, and a thread dump to find contention or deadlock. These skills resolve production incidents that otherwise get restarted and forgotten.
Split packages, illegal reflective access, and dependencies not designed for the module system. A recurring source of upgrade failures with solutions that are unobvious the first time.
Configuration classes, conditional beans, profiles, and property binding. Older applications frequently mix annotation and XML configuration, and consolidating that is part of upgrade work.
Pool sizing relative to workload type, avoiding unbounded queues, and handling rejection. Virtual threads change some of this calculus on current releases and are worth assessing per workload.
Most clients begin with a modernisation assessment, because the sequence matters enormously and the right first step is frequently not the one expected. Options then include version upgrade projects, framework major upgrades, containerisation, an embedded developer, and a maintenance retainer. Larger programmes are staffed through our dedicated development team model. Transparent pricing, an executed NDA, and full intellectual property transfer apply throughout.
We inventory your Java version, framework versions, dependencies, build tooling, test coverage, and deployment target, then report a recommended upgrade sequence with effort estimated per step.
Sequential progression to a current long-term support release, quoted per step so cost is predictable. Includes removed API replacement and dependency compatibility work.
Spring Boot and Spring Framework major version migration including the namespace change, handled as distinct phases with test verification after each.
Application server deployment replaced with a self-contained containerised service, configuration externalised, memory settings appropriate to container limits, and health endpoints exposed.
One specialist inside your team delivering features while progressing modernisation. Suits organisations that cannot pause delivery to upgrade and need both happening together.
Dependency updates, security patching, periodic version upgrades, and JVM configuration review. Systems kept current cost dramatically less than systems rescued every eight years.
Upgrade sequence is the difference between a predictable project and an overrun. We establish a build and test baseline first, because verifying an upgrade requires knowing what correct behaviour looks like. The build tool is modernised before the language, since older build systems cannot express current requirements. The package namespace change is handled as its own step rather than combined with a version bump, because mixing them makes failures impossible to attribute. Removed APIs are replaced deliberately. Dependencies are upgraded in a separate pass. And the application stays deployable throughout. Clients working with TechEsperto Solutions get upgrades delivered as increments.
A reproducible build and characterisation tests capturing current behaviour. Without these, an upgrade cannot be verified and every subsequent step is an act of faith.
Older build systems frequently cannot target current releases or express modern dependency requirements. Doing this first removes a blocker that otherwise appears mid-project.
The enterprise package rename touches imports, configuration, and dependency coordinates across the whole application. As a separate change it is tedious and tractable; combined, it is confusing.
Components removed from the platform in recent releases need explicit replacement dependencies. Identifying these during assessment prevents discovering them during a failing build.
Library upgrades and platform upgrades each introduce their own breakages. Separating them means any failure has one plausible cause rather than several.
Every step ends with a deployable artefact and passing tests. Long-lived upgrade branches that break everything for months are the ones that get abandoned when priorities shift.
Deployment target shapes the work as much as the code does. An application on a licensed application server has different constraints from a containerised service, and both differ from batch processing running overnight. Our developers work across these environments and assess yours specifically rather than assuming a container is always the answer. Larger platform programmes run alongside our enterprise software development practice.
Traditional deployments with server-managed resources, shared classloaders, and vendor-specific configuration. Migration is usually worthwhile and requires careful mapping of what the server was providing.
Self-contained services with externalised configuration. Memory settings must respect container limits rather than the host, which is a common misconfiguration producing unexplained restarts.
Overnight jobs processing large volumes where throughput matters and latency does not. Different tuning entirely, favouring throughput-oriented collectors and larger heaps.
Services consuming from brokers with acknowledgement handling, retry, and dead letter queues. Idempotency matters because redelivery is normal rather than exceptional.
Systems where pause times matter, favouring low-pause collectors and careful allocation behaviour. Tuning here is measurement-driven and worth the effort only where latency is genuinely a requirement.
Where startup time dominates, which the JVM historically handled poorly. Ahead-of-time compilation and framework startup optimisation both help, and sometimes another runtime is the honest answer.
//www.techesperto.com/legacy-software-modernization/" target="_blank" rel="noopener"> legacy software modernisation page.
The entry point is a free modernisation assessment. Give us read access to the repository and build configuration, and we return a written inventory covering Java version, framework versions, dependency currency and known vulnerabilities, build tooling, test coverage, and deployment target, with a recommended upgrade sequence and effort estimated per step. Upgrades are quoted per step, which keeps approval incremental. Your team interviews the matched developers, onboarding completes inside a week, and retainers stay optional.
A few days of inventory and a written report with a recommended sequence. Clients frequently execute it with their own team, which is a reasonable outcome from our side.
Every dependency listed with its current version, latest version, known vulnerabilities, and whether a compatible release exists for your target. This determines scope more than your own code does.
Each version step or migration phase quoted individually with acceptance criteria covering passing tests and a deployable artefact. Budget certainty without approving the whole programme upfront.
Profiles arrive with relevant upgrade, framework, and JVM experience. You assess them against your standards, decline at no cost, and matching continues until the fit is right.
Repository access, build environment, database access, and sprint planning handled immediately. Larger enterprises frequently take longer on access provisioning than we do on setup.
Support begins with dependency updates and security patching, expanding into periodic version upgrades so the system never falls far behind again.
Our work and story have been picked up by news outlets and databases worldwide.
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Assessments are free. Version upgrades are quoted per step, which makes budgeting incremental and predictable. Framework major upgrades are quoted after dependency assessment, since third-party compatibility drives the effort. Containerisation is a defined project. Embedded developers are quoted monthly.
A version step on a medium application with reasonable test coverage typically takes two to four weeks. Moving from Java 8 to a current long-term support release usually runs three to six months in total, including the framework and namespace work. Applications with no tests need a characterisation phase first, adding two to four weeks.
Upgrades are best led by one senior developer for consistency, with a second joining for the mechanical dependency and namespace work on larger codebases. Containerisation adds infrastructure capacity. Feature delivery alongside modernisation scales with your roadmap.
Our developers join your repository, board, and chat workspace and follow your change control process. Weekly sessions cover the current step, test results, and remaining sequence. Direct developer access throughout.
Read access for the assessment, then contributor access and a build environment if we proceed. A mutual NDA is signed first. We work in your environment rather than copying code elsewhere, and nothing from a client engagement is reused.
We staff for at least four hours of daily overlap with your business day across North American, UK, European, and Australian schedules. Change windows, reviews, and release coordination sit inside that window.
Dependency updates and security patching, because Java dependency trees are large and advisories appear regularly. Retainers also cover periodic version upgrades treated as scheduled maintenance, which prevents the situation where a system is three long-term support releases behind.
Upgrading in place is right far more often than it is chosen. It preserves the business rules embedded in the code, costs less, and delivers value in weeks rather than years. Gradual replacement, where new functionality is built alongside and traffic is moved feature by feature, suits systems that genuinely cannot be upgraded or where the architecture itself is the constraint, and it avoids the risk of a single cutover. A full rewrite is justified only when the platform is entirely unsupported, the requirements have changed fundamentally, or the existing code is genuinely beyond comprehension. We assess the codebase and give a direct recommendation, and it is usually the first option.
Tell us what you’re building. Our team will get back to you within one business day with a clear, no-obligation plan.
