This is not from first hand knowledge, so it may be wrong, but my understanding of the downsides:<p>Tooling sort of sucks; this helps python, but deploying other Lambda apps is not very nice. I have no idea how you debug these services either, which is related to the fact that...<p>You have no access to the underlying host, so you can&#x27;t install software, configure the kernel, etc<p>Startup latency can be up to 10s, so they recommend having a scheduled task that keeps your servers warmed up, which will reduce your cost savings by having some parts always-on, but you&#x27;ll still run into the startup latency when you run out of capacity on your existing lambda VMs.<p>You will need to architect your app differently for lambda vs normal servers, e.g. lamba has an enforced maximum run time, but also where your data lives; keeping local databases for things like MaxMind isn&#x27;t an option any more, you&#x27;ll need to access all of your long lived data from other servers and have a cache.<p>So, unless you actually need the <i>fast</i> scaling capability (10s vs 10m) or you need autoscaling, but don&#x27;t want to build it yourself, the only potential reason to use this is cost, and at the low end it&#x27;s not much in savings (I pay $16&#x2F;month for a few small servers 24&#x2F;7 in AWS) and will cost you more in your own time.