<｜begin▁of▁sentence｜>### Instruction:
As the Systems Administrator for our company's IT infrastructure, we've been tasked with optimizing network interconnectivity for our four key servers to enhance performance and redundancy. I propose we leverage NetworkX alongside Graphviz to model our current server topology – essentially a complete graph scenario where each server node is interconnected with every other.

To approach this systematically, let's compute the network layout utilizing the 'dot' algorithm provided by Graphviz. This will give us a clear visual representation of our server interconnectivity layout. In the spirit of thorough documentation and ease of future reference, we'll encapsulate our network architecture in a Graph Modeling Language (GML) file aptly named "complete_graph_4_nodes.gml."

Could you devise a strategy to execute this visualization using the specified tools while maintaining the integrity of our network structure? The objective is to ensure we have an optimized layout for the existing set of nodes (representing our servers) within our network infrastructure.
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Create a complete graph with 4 nodes
G = nx.complete_graph(4)

# Get positions for the nodes using Graphviz layout
pos = nx.nx_pydot.graphviz_layout(G, prog='dot')

# Draw the graph
nx.draw(G, pos, with_labels=True)
plt.show()
<|EOT|>
