Skip to main content

Encore framework POC

I tried out the Encore go backend framework. I had no particular project to use it for; it was more that I wanted to do some go programming. Here are my two cents about it.

Encore uses a simple package-based structure to build simplistic services. It has the usual niceties with hot code reload, minimal boilerplate, easy authentication management, etc. An endpoint is defined by an annotated function with a set of defined parameters. Encore provides also a runtime platform with one command deploy (git push actually) which is rather cool. Perhaps the most opinionated feature to me was the transparent integration to PostgreSQL. If a service has a migration file with some DB calls, the run or the deploy command automatically creates a database for the service and runs the migrations.

The cloud console is pretty neat

Would I use Encore in an actual project?

Maybe not. Firstly, it's still in beta. If I'd start a plain old rest project with Postgres, sure, it takes away the boilerplate. It also provides a whole lot out of the box as in basic hosting, monitoring, API docs, analytics, and tracing with one deploy command. As with all frameworks, here lies the tradeoff; you are pretty much married to the Encore way of doing stuff (which certainly can be a good thing!). I also see it as more of a go application platform as it provides the whole cloud infrastructure and it would perhaps not be just up to me to decide where to run the thing.

Yeah, well, I don't have anything too unique or exciting to say about it. Take a look at my project to see how it runs.

Comments

Popular posts from this blog

RocksDB data recovery

I recently needed to do some maintenance on a RocksDB key-value store. The task was simple enough, just delete some keys as the db served as a cache and did not contain any permanent data. I used the RocksDB cli administration tool ldb to erase the keys. After running a key scan with it, I got this error Failed: Corruption: Snappy not supported or corrupted Snappy compressed block contents So a damaged database. Fortunately, there's a tool to fix it, and after running it, I had access to the db via the admin tool. All the data was lost though. Adding and removing keys worked fine but all the old keys were gone. It turned out that the corrupted data was all the data there was. The recovery tool made a backup folder, and I recovered the data by taking the files from the backup folder and manually changing the CURRENT file to point to the old MANIFEST file which is apparently how RocksDB knows which sst (table) files to use. I could not access the data with the admin tool, ...

I'm not a passionate developer

A family friend of mine is an airlane pilot. A dream job for most, right? As a child, I certainly thought so. Now that I can have grown-up talks with him, I have discovered a more accurate description of his profession. He says that the truth about the job is that it is boring. To me, that is not that surprising. Airplanes are cool and all, but when you are in the middle of the Atlantic sitting next to the colleague you have been talking to past five years, how stimulating can that be? When he says the job is boring, it is not a bad kind of boring. It is a very specific boring. The "boring" you would want as a passenger. Uneventful.  Yet, he loves his job. According to him, an experienced pilot is most pleased when each and every tiny thing in the flight plan - goes according to plan. Passengers in the cabin of an expert pilot sit in the comfort of not even noticing who is flying. As someone employed in a field where being boring is not exactly in high demand, this sounds pro...

PydanticAI + evals + LiteLLM pipeline

I gave a tech talk at a Python meetup titled "Overengineering an LLM pipeline". It's based on my experiences of building production-grade stuff with LLMs I'm not sure how overengineered it actually turned out. Experimental would be a better term as it is using PydanticAI graphs library, which is in its very early stages as of writing this, although arguably already better than some of the pipeline libraries. Anyway, here is a link to it. It is a CLI poker app where you play one hand against an LLM. The LLM (theoretically) gets better with a self-correcting mechanism based on the evaluation score from another LLM. It uses the annotated past games as an additional context to potentially improve its decision-making. https://github.com/juho-y/archipylago-poker