While operational and analytical data gets rigorous treatment in terms of the pillars of good architecture such as purview, privacy, security, governance, encryption at rest and in transit, aging, tiering and such others, DevOps tasks comprising Extract-Transform-Load, backup/restore and such others, is often brushed aside but never eliminated for the convenience they provide. This is inclusive of the vast vector stores that have now become central to building contextual copilots in many scenarios.

One of the tools to empower access of data for purposes other than transactional or analytics is the ability to connect to it with a client native to the store where the data resides. Even if the store is in the cloud, data plane access is usually independent of the control plane command-line interfaces. This calls for a creating a custom image that can be used on any compute to spin up a container with ability to access the vectors. For example, this Dockerfile installs clients:

FROM python:3.13-latest-dev

USER root

RUN apt-get update && \

    apt-get install -y ksh \

    ldap-utils \

    mysql-client \

    vim \

    wget \

    curl \

    libdbd-mysql-perl \

    libcurl4-openssl-dev \

    rsync \

    libev4 \

    tzdata \

    jq \

    pigz \

    python3-minimal \

    python3-pip && \

    apt-get clean && \

    rm -rf /var/lib/apt/lists/* && \

    pip3 install s3cmd

RUN apk add --no-cache mariadb mariadb-client

RUN pip install azure-storage-blob requests

RUN pip install requests

WORKDIR /app

COPY custom_installs.py .

RUN mysqldump --version

RUN mysql --version

ENTRYPOINT ["python", "custom_installs.py"]