Clarify first: directed or undirected? Weighted edges, or all hops equal? Could there be cycles, so I need visited-tracking to avoid looping? Roughly how wide versus deep is the graph — that drives the space trade-off.

Both are O(V + E) time. The real choice is shape and goal. BFS expands level by level with a queue, so the first time it reaches a node is along the fewest edges — that's why BFS gives shortest paths in an unweighted graph. DFS plunges down one branch with a stack or recursion and backtracks, which is the natural fit for "explore every path", topological ordering, and cycle detection. Space differs: BFS holds a whole frontier, up to O(V) and painful on a wide graph; DFS holds a single path, O(h) for depth h, but risks a deep recursion stack.

function bfs(start) {
  const queue = [start];
  const visited = new Set([start]);
  while (queue.length > 0) {
    const node = queue.shift();
    for (const nb of node.neighbors) {
      if (!visited.has(nb)) { visited.add(nb); queue.push(nb); }
    }
  }
}

function dfs(node, visited) {
  visited.add(node);
  for (const nb of node.neighbors) {
    if (!visited.has(nb)) dfs(nb, visited);
  }
}

So for "fewest hops between two services" I'd reach for BFS; for "is there a dependency cycle" I'd reach for DFS and track nodes on the current recursion path. Both need visited-tracking or they loop forever on a cyclic graph.