You have to prove:
$$\begin{eqnarray*}d_X(x_1,x_3)^2+d_Y(y_1,y_3)^2 &\leq& d_X(x_1,x_2)^2+d_X(x_2,x_3)^2+d_Y(y_1,y_2)^2+d_Y(y_2,y_3)^2\\&+&2\sqrt{\left(d_X(x_1,x_2)^2+d_Y(y_1,y_2)^2\right)\left(d_X(x_2,x_3)^2+d_Y(y_2,y_3)^2\right)}\end{eqnarray*}$$
where the Cauchy-Schwarz inequality ensures that the last square root is greater or equal than:
$$ d_X(x_1,x_2)\,d_X(x_2,x_3)+d_Y(y_1,y_2)\,d_Y(y_2,y_3)$$
hence it is sufficient to show that:
$$d_X(x_1,x_3)^2+d_Y(y_1,y_3)^2\leq\left(d_X(x_1,x_2)+d_X(x_2,x_3)\right)^2+\left(d_Y(y_1,y_2)+d_Y(y_2,y_3)\right)^2$$
that just follows from the triangle inequality for $d_X$ and $d_Y$.
There are two things to be done:
a) Define a metric on $X \times Y$ (based on $d_X$ and $d_Y$). The product of the metrics won't work (as then the distance is already $0$ for points like $(x,y)$ and $(x,y')$, to name an easier reason), but the sum or max both work and are convenient choices. So e.g. (my favourite choice for 2 spaces) define
$$d((x_1, y_1), (x_2, y_2)) = \max(d_X(x_1, x_2), d_Y(y_1, y_2))$$
and check that this indeed gives a metric on $X \times Y$.
b) Secondly, and quite importantly, one has to check that the topology of $(X \times Y, d)$ is actually the same as the product topology on $X \times Y$. That will show that the product of $X \times Y$, which by definition/convention will have the product topology, can also be induced by a metric, i.e. is metrisable.
E.g. check that $$B_d((x,y), r) = B_{d_X}(x,r) \times B_{d_Y}(y, r)$$
which shows that open balls under $d$ are indeed open in the product topology of $(X,d_X)$ and $(Y,d_Y)$, so $\mathcal{T}_d \subseteq \mathcal{T}_{\text{prod}}$. The reverse also needs showing: suppose $O$ is product open, and let $(x,y) \in O$. Then there is an open set $U$ in $\mathcal{T}_X$ (topology induced by $d_X$) and an open set $V$ in $\mathcal{T}_Y$, such that
$(x,y) \in U \times V \subseteq O$. This means that there is some $r_1>0 $ such that $x \in B_{d_X}(x,r_1) \subseteq U$ and some $r_2>0$ such that $y \in B_{d_Y}(y,r_2) \subseteq V$. But then, setting $R =\min(r_1, r_2)>0$:
$$(x,y) \in B_d((x,y), R) = B_{d_X}(x,R) \times B_{d_Y}(y,R) \subseteq B_{d_X}(x,r_1) \times B_{d_Y}(y,r_2) \subseteq U \times V \subseteq O$$
showing $O \in \mathcal{T}_d$ as required. So the product topology coincides with the topology generated by $d$.
As a final remark: one can show that this extends to countable products of metric spaces as well. This is somewhat more work, and then a sum metric is the most suitable:
$$d((x_n)_{n \in \mathbb{N}}, (y_n)_{n \in \mathbb{N}}) = \sum_{n \in \mathbb{N}} \frac{1}{2^n}\min(d_{X_n}(x_n, y_n), 1)$$
will then do as a metric on $\prod_n X_n$ that induces the product topology. See this answer for more details.
Also s
Best Answer
Note that
$$d_Z((x,y),(x',y'))=\lVert\big(d_X(x,x'), d_Y(y,y')\big)\rVert$$
where $\lVert\cdot\rVert$ is the Euclidean norm in $\mathbb{R}^2$. Then we have:
$$d_Z\big((x,y),(x'', y'')\big)+d_Z\big((x'', y''),(x',y')\big)=$$ $$=\lVert\big(d_X(x,x''), d_Y(y,y'')\big)\rVert+\lVert\big(d_X(x'',x'), d_Y(y'',y')\big)\rVert\geq$$ $$\geq\lVert\big(d_X(x,x''), d_Y(y,y'')\big) + \big(d_X(x'',x'), d_Y(y'',y')\big)\rVert=$$ $$=\lVert\big(d_X(x,x'')+d_X(x'', x'), d_Y(y,y'')+d_Y(y'',y')\big)\rVert\geq$$ $$\geq \lVert\big(d_X(x,x'), d_Y(y,y')\big)\rVert=$$ $$d_Z\big((x,y), (x',y') \big)$$
The first inequality is because every norm is subadditive. The second one because $d_X$ and $d_Y$ satisfy the triangle inequality.