git clone https://github.com/MediaArea/BWFMetaEdit.git cd BWFMetaEdit/Project/GNU/CLI ./autogen.sh ./configure make Use code with caution. Copied to clipboard
Do look for a Kubernetes version. Just download the standard Windows executable:
initContainers: - name: descargar-bwf image: curlimages/curl:latest command: ['sh', '-c'] args: - | curl -L -o /tmp/bwfmetaedit.zip https://mediaarea.net/download/binary/bwfmetaedit/23.11/BWFMetaEdit_CLI_23.11_Windows_x86_64.zip && unzip /tmp/bwfmetaedit.zip -d /tools/ volumeMounts: - name: bin-tools mountPath: /tools containers: - name: main image: mcr.microsoft.com/windows/servercore:ltsc2022 command: ["/tools/bwfmetaedit.exe"] volumeMounts: - name: bin-tools mountPath: /tools volumes: - name: bin-tools emptyDir: {} descargar bwf metaedit exe kubernetes
FROM ubuntu:24.04 # Install dependencies RUN apt-get update && apt-get install -y \ wget \ libzen0v5 \ && rm -rf /var/lib/apt/lists/* # Download and install BWF MetaEdit CLI RUN wget https://mediaarea.net \ && dpkg -i bwfmetaedit_24.06_amd64.Ubuntu_24.04.deb \ && rm bwfmetaedit_24.06_amd64.Ubuntu_24.04.deb # Set the working directory WORKDIR /media # Default command ENTRYPOINT ["bwfmetaedit"] Use code with caution.
To run BWF MetaEdit in Kubernetes, you must package the application into a Docker image. Below are two approaches depending on your infrastructure. Option A: Standard Linux Architecture (Recommended) git clone https://github
Run jobs to validate metadata against FADGI or EBU standards automatically as files are uploaded to storage.
As engineering organizations shift toward cloud-native architectures, containerizing desktop-born or standalone CLI utilities like BWF MetaEdit is necessary. Running bwfmetaedit inside a cluster allows you to scale audio verification and embedding processes dynamically across distributed workloads. Why Run BWF MetaEdit in Kubernetes? To run BWF MetaEdit in Kubernetes, you must
Build and push your image to a container registry (like Docker Hub, AWS ECR, or Google Artifact Registry):
En este artículo, hemos cubierto los pasos necesarios para descargar BWF MetaEdit, crear una imagen Docker para él, y desplegarlo en un clúster de Kubernetes. Esta aproximación no solo facilita el uso de BWF MetaEdit en entornos de contenedores, sino que también abre la puerta a una mayor automatización y escalabilidad en el manejo de metadatos de audio.
Your media company ingests 1,000 audio files per hour. You need to automatically add preservation metadata to every file before sending it to cold storage. A Kubernetes cron job spins up a pod, runs bwfmetaedit --Description="Archived" /data/file.wav , and shuts down.
apiVersion: v1 kind: Pod metadata: name: bwfmetaedit-job spec: nodeSelector: kubernetes.io/os: windows containers: - name: bwfmetaedit image: mcr.microsoft.com/windows/servercore:ltsc2022 command: ["cmd", "/c"] args: ["bwfmetaedit.exe --IN=myfile.wav --OUT=output.wav"] volumeMounts: - name: audio-data mountPath: C:\data volumes: - name: audio-data persistentVolumeClaim: claimName