The popularity of the Java programming language has led to its wide adoption in cloud computing infrastructures. However, Java applications running in untrusted clouds are vulnerable to various forms of privileged attacks. The emergence of trusted execution environments (TEEs) such as Intel SGX mitigates this problem. TEEs protect code and data in secure enclaves inaccessible to untrusted software, including the kernel and hypervisors. To efficiently use TEEs, developers must manually partition their applications into trusted and untrusted parts, in order to reduce the size of the trusted computing base (TCB) and minimise the risks of security vulnerabilities. However, partitioning applications poses two important challenges: (i) ensuring efficient object communication between the partitioned components, and (ii) ensuring the consistency of garbage collection between the parts, especially with memory-managed languages such as Java. We present Montsalvat, a tool which provides a practical and intuitive annotation-based partitioning approach for Java applications destined for secure enclaves. Montsalvat provides an RMI-like mechanism to ensure inter-object communication, as well as consistent garbage collection across the partitioned components. We implement Montsalvat with GraalVM native-image, a tool for compiling Java applications ahead-of-time into standalone native executables that do not require a JVM at runtime. Our extensive evaluation with micro- and macro-benchmarks shows our partitioning approach to boost performance in real-world applications