Live
Binding Cloudflare Workers to Specific VPCs per ConfigurationAgentic Regression Testing with Cached Playwright Replays: Implications for CI PipelinesBigQuery queries Databricks Iceberg tables through the borderless LakehouseCopilot harness public preview reshapes managed agent orchestrationPlatform‑Level Identity and Reach Controls Anchor Agent BoundariesManaging Regulated Workloads on AWS Elastic Beanstalk: From Fast Deploys to Long‑Term ComplianceAutomating PHP‑to‑Java Migration with Kiro and AWS TransformBuilding Intent‑Driven UI Testing on AWS with Nova Act and Bedrock AgentCore BrowserBinding Cloudflare Workers to Specific VPCs per ConfigurationAgentic Regression Testing with Cached Playwright Replays: Implications for CI PipelinesBigQuery queries Databricks Iceberg tables through the borderless LakehouseCopilot harness public preview reshapes managed agent orchestrationPlatform‑Level Identity and Reach Controls Anchor Agent BoundariesManaging Regulated Workloads on AWS Elastic Beanstalk: From Fast Deploys to Long‑Term ComplianceAutomating PHP‑to‑Java Migration with Kiro and AWS TransformBuilding Intent‑Driven UI Testing on AWS with Nova Act and Bedrock AgentCore Browser
AWS

Automating PHP‑to‑Java Migration with Kiro and AWS Transform

AI SummaryPowered by AI

A reusable engine now lets teams convert PHP applications to Java through a defined eight‑phase workflow driven by Kiro skill files. This makes migration repeatable, auditable, and scalable for engineers who need reliable parity between source and target code.

Engineers can now treat a PHP codebase as the single source of truth and run a scripted migration to Java that only passes when a parity test harness validates functional equivalence. The change is the introduction of a shared, file‑based methodology—packaged as php-to-java-migration and php-model-discovery skill files—that can be executed either interactively in Kiro or autonomously via AWS Transform.

How the Migration Engine Works

The engine is anchored in a .kiro/ directory that stores the skill packages and a steering file describing the eight phases: discovery, rulebook generation, translation, build, test, parity verification, review, and finalization. Each project folder under the workspace inherits this shared brain, so any improvement to the skill set instantly benefits all migrations.

Running the Engine: Interactive vs. Agentic

Kiro interactive mode loads the skill files when a developer opens the repository as a Kiro workspace. The AI agent walks the practitioner through each phase, pausing for explicit approval before proceeding. This gives fine‑grained control, lets engineers inspect generated Java, and ensures test suites pass before the next step.

AWS Transform mode consumes the same skill files without a human in the loop. The service launches parallel jobs across multiple repositories, applying the same discovery‑first, parity‑first discipline. The two paths share the same rulebook, so fixes made during a Kiro session propagate to future Transform runs.

Architectural and Operational Implications

  • Shared methodology layer: Centralizing migration logic in versioned markdown files decouples the process from any single tool, simplifying version control and audit trails.
  • Discovery scanner dependency: The engine requires PHP 8+ on the host machine to parse models and generate a manifest, and Java 21 with Maven to compile the output. Teams must provision compatible runtimes in CI pipelines.
  • Parity harness as gatekeeper: Functional equivalence is enforced before the Java code is considered valid, reducing post‑migration bugs and regression risk.
  • Scalability trade‑off: Interactive Kiro is suited for one‑off or novel frameworks, while AWS Transform enables bulk migration of many services, but the latter sacrifices per‑step human review.

Security and Compliance Considerations

The engine does not introduce new runtime controls, but practitioners should treat the generated Java code as a new attack surface. Reviewing the translation output for inadvertent exposure of sensitive data (e.g., hard‑coded credentials in configuration files) remains essential. Because the parity harness runs tests against the original PHP behavior, any security test suites present in the PHP project should be migrated alongside the code to maintain coverage.

Related CloudNinjas coverage: AWS.

What This Means For Practitioners

Adopt the shared skill files as the single source of migration truth and integrate the eight‑phase workflow into your CI/CD pipelines. Use Kiro for initial pilots to validate the rulebook, then switch to AWS Transform for bulk operations once confidence is established. Continuously update the skill packages to capture edge‑case translations, and ensure your existing security test suites are part of the parity verification step to keep the Java target as secure as the original PHP service.

Originally published atAWS Machine Learning Blog