Projects with the tag process-improvement
- Python provisioning system that stands up the complete Nova Sonic inference stack on one developer machine.
- Deploys several Triton model containers plus the C++ node-graph orchestrator, wired together and ready to take speech-to-speech traffic.
- Took a fifteen-person team from sharing a couple of hand-built demo environments to every engineer having their own.
- Same pattern as L3Dockerize: make the right environment the cheap one.
- The legacy ASR engine, roughly 500k lines of C++, was built by its owners with GCC and plain CMake for the cloud. The on-device team consumed it as a library across about 7 ARM toolchains from the Android NDK plus 4 x86 gcc/clang variants, through a Conan-based build layer.
- Before: on-device releases were hand-curated snapshots of the upstream engine, maintained in forks of every ASR package and re-merged periodically. Each release took days at minimum and often weeks, as toolchain-specific breakage surfaced and needed patches.
- Fix: point all engine code at a single virtual build-system package. In the cloud dependency universe it resolves to bare CMake; in the device universe it resolves to the Conan layer, which drives the same CMake underneath. About 40 packages converted; one source tree builds for all 12 toolchains.
- Kept it that way with a pre-merge analyzer that compiles every pull request against the device toolchains before it can land, so device compatibility is checked at merge time rather than discovered at release time.
- Python-based Docker container builder.
- Dynamically resolves and fetches software component dependencies to build Docker images.
- Intended to serve as a low/zero cost tool for developers to convert existing software installs to more easily monitorable, scalable, and extensible docker-based installations.
- Concept evaluated in a system-wide CIT test of an L3Harris hardware product.
- Python/Bash Scripting Toolkit for cross-project refactoring.
- Uninvasive, agile solution to deal with problem of poorly-isolated dependencies impacting many components.
- Core application written in Python, per-project scripts writable in any language.
- Designed according to Unix ”simple, clear, modular, extensible” philosophy to facilitate integration into existing toolchains and processes.
- Successfully deployed to automatically upgrade the dependencies of approx. 60 components without user intervention.