You have to start out with a monolith and only if you realise along the way that some components might work better as a service (micro or not) you should extract those. Until then, commonplace modularisation will serve you just fine.
Once you have more than 1 microservice running infrastructure becomes a huge problem. There's no real turnkey solution for deploying and running internal / on-premises microservices yet. You basically have to build monitoring, orchestration and logging infrastructure yourself.
The number of different services is close to the number of people on the team.
This is working very well for us, and it provides us with some welcome isolation when there are problems with one of the microservices. Maybe we can go into read-only mode or stop processing batch jobs for a while, depending on what services have problems.
But we also have good infrastructure support, which makes this a lot easier.
Just for every team that I see that has a good use case for micro services, and does the hard work of instrumentation and deployment, I see 8 teams that go with microservices because they think it's a magic bullet. Then they don't spend the time and effort necessary to get instrumentation and orchestration up and running. They don't aggregate logs, they don't spend the time to create defined contracts between the services, they don't make services robust to the failure of other services. They just complicate their debugging, deployment, uptime, and performance scenario without getting any of the benefits.
It's also a lot easier to prioritize process scheduling than it is to prioritize thread scheduling.
I had a system where the main running cost was MySQL. It turned out that I needed to provision a lot of MySQL capacity because there was one table that had a high rate of selects and updates.
The hot table did not use many MySQL features and could easily be handled by a key-value store with highly tuned data structures. That's a place where a "microservice" which has it's own address space, if not machine, makes it possible to scale parts of the system that need to be scaled without scaling the rest.
One table is small in terms of data but involves an interactive service that might generate 50 updates/sec at peak times.
With the "hot" service implemented on top of a key-value store, the database is the ultimate commodity, I have many choices such as in-memory with logging, off-heap storage, distributed key-value stores, etc.
The service is not "in front" of MySQL, but is on the side of it so far as the app is concerned.
I'm lucky that the project that I'm working on has support to use JHipster (https://jhipster.github.io/) with microservices deployed to OpenShift (https://www.openshift.com/). I used MiniShift to test my deployments, metrics, monitoring, orchestration, and logging locally. This was mostly for a proof-of-concept.