Comparison
Vertical autoscalingvsVertical scaling
Vertical autoscaling
something watched the workload for a week and rewrote its requests, and traditionally had to restart it to apply them.
Adjusting a workload's requests and limits automatically from observed usage, rather than changing how many copies there are. It solves the request-guessing problem that wrecks bin packing, and it is most useful on workloads that cannot be scaled out at all. Historically it required a restart to take effect, which is why many teams run it in recommendation-only mode and let humans apply the numbers.
Full entry →Vertical scaling
you move the database to a machine with four times the RAM, which takes an afternoon instead of a re-architecture.
Adding CPU, memory or faster disks to an existing machine. It is dramatically simpler than scaling out — no partitioning, no distributed transactions, no consistency questions — and it is the correct first answer far more often than architecture discussions admit. It ends at the largest instance available, and it usually requires a restart.
Full entry →