diff --git a/docker/1.7-1/base/Dockerfile.cpu b/docker/1.7-1/base/Dockerfile.cpu
index 6ce800c4..c44cdd6c 100644
--- a/docker/1.7-1/base/Dockerfile.cpu
+++ b/docker/1.7-1/base/Dockerfile.cpu
@@ -4,6 +4,7 @@ ARG IMAGE_DIGEST=c2d95c9c6ff77da41cf0f2f9e8c5088f5b4db20c16a7566b808762f05b9032e
 
 FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu${UBUNTU_VERSION}@sha256:${IMAGE_DIGEST}
 
+# Argument Variables
 ARG MINICONDA_VERSION=4.9.2
 ARG CONDA_PY_VERSION=39
 ARG CONDA_CHECKSUM="b4e46fcc8029e2cfa731b788f25b1d36"
@@ -13,93 +14,56 @@ ARG PYARROW_VERSION=14.0.1
 ARG MLIO_VERSION=0.9.0
 ARG XGBOOST_VERSION=1.7.4
 
+# Environment Variables
 ENV DEBIAN_FRONTEND=noninteractive
 ENV LANG=C.UTF-8
 ENV LC_ALL=C.UTF-8
-
-# Python won’t try to write .pyc or .pyo files on the import of source modules
-# Force stdin, stdout and stderr to be totally unbuffered. Good for logging
 ENV PYTHONDONTWRITEBYTECODE=1
 ENV PYTHONUNBUFFERED=1
 ENV PYTHONIOENCODING='utf-8'
+ENV PATH=/miniconda3/bin:${PATH}
 
-RUN apt-key del 7fa2af80 && \
-        apt-get update && apt-get install -y --no-install-recommends wget && \
-        wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-keyring_1.0-1_all.deb && \
-        dpkg -i cuda-keyring_1.0-1_all.deb && \
-        apt-get update && \
-    apt-get -y upgrade && \
-    apt-get -y install --no-install-recommends \
+# Install system dependencies, clean up, and install Miniconda in a single RUN
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
         build-essential \
         curl \
         git \
-        jq \
+        ca-certificates \
         libatlas-base-dev \
-        nginx \
         openjdk-8-jdk-headless \
         unzip \
         wget \
-        && \
-    # MLIO build dependencies
-    # Official Ubuntu APT repositories do not contain an up-to-date version of CMake required to build MLIO.
-    # Kitware contains the latest version of CMake.
-    wget http://es.archive.ubuntu.com/ubuntu/pool/main/libf/libffi/libffi7_3.3-4_amd64.deb && \
-    dpkg -i libffi7_3.3-4_amd64.deb && \
-    apt-get -y install --no-install-recommends \
-        apt-transport-https \
-        ca-certificates \
-        gnupg \
-        software-properties-common \
-        && \
-    wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | \
-        gpg --dearmor - | \
-        tee /usr/share/keyrings/kitware-archive-keyring.gpg >/dev/null && \
-    echo 'deb [signed-by=/usr/share/keyrings/kitware-archive-keyring.gpg] https://apt.kitware.com/ubuntu/ bionic main' | tee /etc/apt/sources.list.d/kitware.list >/dev/null && \
-    apt-get update && \
-    rm /usr/share/keyrings/kitware-archive-keyring.gpg && \
-    apt-get install -y --no-install-recommends \
-        autoconf \
-        automake \
-        build-essential \
-        cmake \
-        cmake-data \
-        doxygen \
-        kitware-archive-keyring \
-        libcurl4-openssl-dev \
-        libssl-dev \
-        libtool \
         ninja-build \
+        cmake \
+        zlib1g-dev \
         python3-dev \
         python3-distutils \
         python3-pip \
-        zlib1g-dev \
-        && \
-    rm -rf /var/lib/apt/lists/*
-
-# Install conda
-RUN cd /tmp && \
-    curl -L --output /tmp/Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-py${CONDA_PY_VERSION}_${MINICONDA_VERSION}-Linux-x86_64.sh && \
-    echo "${CONDA_CHECKSUM} /tmp/Miniconda3.sh" | md5sum -c - && \
-    bash /tmp/Miniconda3.sh -bfp /miniconda3 && \
-    rm /tmp/Miniconda3.sh
-
-ENV PATH=/miniconda3/bin:${PATH}
-
-# Install MLIO with Apache Arrow integration
+        libssl-dev \
+        libcurl4-openssl-dev \
+        doxygen \
+        libtool \
+        && rm -rf /var/lib/apt/lists/* && \
+    cd /tmp && \
+    curl -L --output Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-py${CONDA_PY_VERSION}_${MINICONDA_VERSION}-Linux-x86_64.sh && \
+    echo "${CONDA_CHECKSUM}  Miniconda3.sh" | md5sum -c - && \
+    bash Miniconda3.sh -bfp /miniconda3 && \
+    rm Miniconda3.sh && \
+    apt-get clean && rm -rf /var/lib/apt/lists/*
 
-# We could install mlio-py from conda, but it comes  with extra support such as image reader that increases image size
-# which increases training time. We build from source to minimize the image size.
-RUN echo "conda ${CONDA_PKG_VERSION}" >> /miniconda3/conda-meta/pinned && \
-    # Conda configuration see https://conda.io/projects/conda/en/latest/configuration.html
-    conda config --system --set auto_update_conda false && \
+# Install Conda dependencies and Python packages
+RUN conda config --system --set auto_update_conda false && \
     conda config --system --set show_channel_urls true && \
     echo "python ${PYTHON_VERSION}.*" >> /miniconda3/conda-meta/pinned && \
-    conda install -c conda-forge python=${PYTHON_VERSION} && \
-    pip install requests==2.27.0 && \
-    conda install conda=${CONDA_PKG_VERSION} && \
+    conda install -c conda-forge python=${PYTHON_VERSION} requests==2.27.0 conda=${CONDA_PKG_VERSION} pyarrow=${PYARROW_VERSION} && \
     conda update -y conda && \
-    conda install -c conda-forge pyarrow=${PYARROW_VERSION} && \
-    cd /tmp && \
+    pip install --upgrade pip && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Build MLIO and clean up build tools afterward
+RUN cd /tmp && \
     git clone --branch v${MLIO_VERSION} https://github.com/awslabs/ml-io.git mlio && \
     cd mlio && \
     build-tools/build-dependency build/third-party all && \
@@ -114,12 +78,12 @@ RUN echo "conda ${CONDA_PKG_VERSION}" >> /miniconda3/conda-meta/pinned && \
     cmake --build . --target mlio-arrow && \
     cd ../../src/mlio-py && \
     python3 setup.py bdist_wheel && \
-    python3 -m pip install typing && \
-    python3 -m pip install --upgrade pip && \
     python3 -m pip install dist/*.whl && \
     cp -r /tmp/mlio/build/third-party/lib/libtbb* /usr/local/lib/ && \
     ldconfig && \
-    rm -rf /tmp/mlio
+    apt-get remove --purge -y cmake ninja-build build-essential && \
+    apt-get autoremove -y && \
+    rm -rf /tmp/mlio /tmp/mlio/build /var/lib/apt/lists/*
 
-# Install latest version of XGBoost
+# Install XGBoost
 RUN python3 -m pip install --no-cache -I xgboost==${XGBOOST_VERSION}
diff --git a/docker/1.7-1/final/Dockerfile.cpu b/docker/1.7-1/final/Dockerfile.cpu
index ab36823c..60d0102b 100644
--- a/docker/1.7-1/final/Dockerfile.cpu
+++ b/docker/1.7-1/final/Dockerfile.cpu
@@ -19,17 +19,16 @@ RUN python3 -m pip install git+https://github.com/awslabs/sagemaker-debugger.git
 # Copy wheel to container #
 ###########################
 COPY dist/sagemaker_xgboost_container-2.0-py2.py3-none-any.whl /sagemaker_xgboost_container-1.0-py2.py3-none-any.whl
-RUN rm -rf /miniconda3/lib/python3.8/site-packages/numpy-1.21.2.dist-info && \
-    python3 -m pip install --no-cache /sagemaker_xgboost_container-1.0-py2.py3-none-any.whl && \
+RUN python3 -m pip install --no-cache-dir /sagemaker_xgboost_container-1.0-py2.py3-none-any.whl && \
     python3 -m pip uninstall -y typing && \
-    rm /sagemaker_xgboost_container-1.0-py2.py3-none-any.whl
+    rm /sagemaker_xgboost_container-1.0-py2.py3-none-any.whl && \
+    rm -rf /miniconda3/lib/python3.8/site-packages/numpy-1.21.2.dist-info
 
 ##############
 # DMLC PATCH #
 ##############
-# TODO: remove after making contributions back to xgboost for tracker.py
 COPY src/sagemaker_xgboost_container/dmlc_patch/tracker.py \
-   /miniconda3/lib/python${PYTHON_VERSION}/site-packages/xgboost/dmlc-core/tracker/dmlc_tracker/tracker.py
+    /miniconda3/lib/python${PYTHON_VERSION}/site-packages/xgboost/dmlc-core/tracker/dmlc_tracker/tracker.py
 
 # Include DMLC python code in PYTHONPATH to use RabitTracker
 ENV PYTHONPATH=$PYTHONPATH:/miniconda3/lib/python${PYTHON_VERSION}/site-packages/xgboost/dmlc-core/tracker
@@ -37,25 +36,16 @@ ENV PYTHONPATH=$PYTHONPATH:/miniconda3/lib/python${PYTHON_VERSION}/site-packages
 #######
 # MMS #
 #######
-# Create MMS user directory
-RUN useradd -m model-server
-RUN mkdir -p /home/model-server/tmp && chown -R model-server /home/model-server
-
-# Copy MMS configs
+# Create user, directories, and set permissions
+RUN useradd -m model-server && \
+    mkdir -p /home/model-server/tmp /opt/ml/models /tmp/plugins /etc/dask && \
+    chown -R model-server /home/model-server && \
+    chmod +rwx /opt/ml/models && \
+    chmod +x /tmp/plugins/endpoints-1.0.jar
+
+# Copy MMS configs and setup
 COPY docker/${SAGEMAKER_XGBOOST_VERSION}/resources/mms/config.properties.tmp /home/model-server
-ENV XGBOOST_MMS_CONFIG=/home/model-server/config.properties
-
-# Copy execution parameters endpoint plugin for MMS
-RUN mkdir -p /tmp/plugins
 COPY docker/${SAGEMAKER_XGBOOST_VERSION}/resources/mms/endpoints-1.0.jar /tmp/plugins
-RUN chmod +x /tmp/plugins/endpoints-1.0.jar
-
-# Create directory for models
-RUN mkdir -p /opt/ml/models
-RUN chmod +rwx /opt/ml/models
-
-# Copy Dask configs
-RUN mkdir /etc/dask
 COPY docker/configs/dask_configs.yaml /etc/dask/
 
 # Required label for multi-model loading
@@ -64,22 +54,21 @@ LABEL com.amazonaws.sagemaker.capabilities.multi-models=true
 #####################
 # Required ENV vars #
 #####################
-# Set SageMaker training environment variables
+# Set SageMaker environment variables
 ENV SM_INPUT /opt/ml/input
 ENV SM_INPUT_TRAINING_CONFIG_FILE $SM_INPUT/config/hyperparameters.json
 ENV SM_INPUT_DATA_CONFIG_FILE $SM_INPUT/config/inputdataconfig.json
 ENV SM_CHECKPOINT_CONFIG_FILE $SM_INPUT/config/checkpointconfig.json
-# See: https://github.com/dmlc/xgboost/issues/7982#issuecomment-1379390906 https://github.com/dmlc/xgboost/pull/8257
-ENV NCCL_SOCKET_IFNAME eth 
-                            
-
-# Set SageMaker serving environment variables
+ENV NCCL_SOCKET_IFNAME eth
 ENV SM_MODEL_DIR /opt/ml/model
 
-# Set SageMaker entrypoints
+# Sagemaker entrypoints
 ENV SAGEMAKER_TRAINING_MODULE sagemaker_xgboost_container.training:main
 ENV SAGEMAKER_SERVING_MODULE sagemaker_xgboost_container.serving:main
-
-EXPOSE 8080
 ENV TEMP=/home/model-server/tmp
+
+# Required for SageMaker
 LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
+
+# Expose port for the serving container
+EXPOSE 8080