What does the equation in Lasso :Sparse Learning method mean



Sparse learning is one of the methods used for dimensionality reduction and Lasso is one of the popular sparse learning methods.
In the above image I could not understand the the equation in the graph,so if somebody could please help me with that.
Here is a link to the source of the image


The equation is saying
Minimize (SSR + lamba*(sum of modulus of all coefficients))
SSR - sum of squares of residuals
lamba - shrikage factor
sum of modulus of all coefficients - l1 loss

The chart is depicting the case of two variable Lasso, with coefficients beta1 (along x axis) and beta2 (along Y axis). The above term l1 loss i.e. sum of modulus of all coefficients i.e.|beta1| + |beta2| needs to be minimized then the condition will be met by all points in the red diamond.