workflows-samples VS language-server-protocol

Have you seen this? https://cloud.google.com/workflows

Cloud Workflows: A serverless workflow orchestration service

Workflows can trigger actions, like Cloud Run Jobs, in a sequence of steps. The Workflows product waits for the job to complete, fail, or time out before it moves on to the next step. It uses polling to check on the job, so there may be a delay between the job finishing and the next step.

Has anyone integrated firestore/realtime database together with GCP workflows? What was your use case? How was your experience with it? Why have you decided to go that way?

In the past few years, YAML (http://yaml.org) has become an essential part of software, particularly for infrastructure-as-code tools. Yaml at the heart of kubernetes configuration, kubernetes-inspired APIs like Google's config connector, and a number of workflow systems like Google Cloud Workflows and Github Actions.

If your routine is just a bunch of API calls, you can also replace steps 1-2 with Workflows.

I have come at this problem from a bit of a different angle by asking what is the closest I can possibly get to the hypothetical dream state of everything is automated, autoscaling blah blah blah as possible with the absolute smallest budget in terms of not only actual costs but time budget as well.

I only know the GCP ecosystem kind of well so I don't fully know to what extent these things exist in AWS and Azure but there I think there is a really nice path you can get on with the serverless route that skips K8s entirely but keeps you very well aligned in case you ever need to "upgrade" or get out of the GCP ecosystem.

I write very stock standard gRPC services and then put them onto Cloud Run (which has a very Heroku like workflow) and stick https://cloud.google.com/api-gateway in front of things and now my API is running on the exact same setup as any other service Google is running in production. Huge amounts of logic get moved out of my code base as a result.

If you are also willing to write your APIs a fairly particular way https://google.aip.dev/ it starts to become trivial to integrate other things like https://cloud.google.com/workflows, https://cloud.google.com/pubsub and https://cloud.google.com/tasks which is traditionally where a lot of the "state" and weirdly complicated logic previously lived in my code. I'm now not really writing any of that.

Now it's all declarative where I just say what I want to happen and I don't have to think about much else beyond that because it too is using that same internal GCP infrastructure to handle all the complicated parts around what to do when things go wrong.

But to me they are all extremely heavily aligned with the K8s path so the lock in certainly doesn't feel as scary.

Google Workflows combines Google’s cloud services and APIs to help developers build reliable large-scale applications, process automation, and deploy machine learning and data pipelines.

Lately, I build a system using Cloud Workflows which can combine Google Cloud Services such as Cloud Functions and Cloud Run. Sometimes, I was in a situation where I want to examine more efficiently using logs on Cloud Logging when debugging or daily monitoring.

Look at Cloud Workflows for simple workflows

But these are typically filling the usecases of productivity applications, not ‘engines’.

Microsoft Word doesn’t run its grammar checker as an external service and shunt JSON over a localhost socket to get spelling and style suggestions.

Photoshop doesn’t install a background service to host filters.

The closest pattern I can think of is the ‘language servers’ model used by IDEs to handle autosuggest - see https://microsoft.github.io/language-server-protocol/ - but the point of that is to enable many to many interop - multiple languages supporting multiple IDEs. Is that the expected usecase for local language assistants and image generators?

If you tried writing code like the one above, your Rust LSP should already be telling you that what you're doing is unacceptable:

A language server is an external program that follows the Language Server Protocol. The LSP specification defines what type of messages a language server can receive, and also how it should respond. The idea here is that any tool that follows the LSP specification can communicate with a language server.

> There's a strange dance of IDEs coming and going, with their idiosyncracies and partial plugins.

The Language Server Protocol [1] is the best thing to happen to text editors. Any editor that speaks it gets IDE features. Now if only they'd adopt the Debug Adapter Protocol [2]...

[1] https://microsoft.github.io/language-server-protocol/

[2] https://microsoft.github.io/debug-adapter-protocol/

The Gno Language Server (gnols) is an implementation of the Language Server Protocol (LSP) for the Gno programming language. It is similar to the equivalent “gopls” project for Go, as they can be plugged into your code editor through extensions and allow you to access handy features, such as autocompletion, formatting, and compile-time warnings/errors. Gnols makes writing code simpler, working with several editors to suit your preferences. To try it out, visit the CONTRIBUTING.md file, which contains instructions to get you started. Our current documentation targets Vim, Neovim, and SublimeText, but can likely be used with any editor that supports LSP. Feel free to contribute to improving Gnols and adding more features. It’s well-written, and simple to dive into the code and add more capabilities.

Honestly, you should read some of the docs [0] if these are the sorts of questions you're asking.

[0] https://microsoft.github.io/language-server-protocol/

hey HN. this is a Language Server[0] designed specifically for Postgres. A language server adds features to IDEs (VSCode, NeoVim, etc) - features like auto-complete, go-to-definition, or documentation on hover, etc.

there have been previous some attempts at adding Postgres support to code editors. usually these attempts implement a generic SQL parser and then offer various "flavours" of SQL.

This attempt is different because it uses the actual Postgres parser to do the heavy-lifting. This is done via libg_query, an excellent C library for accessing the PostgreSQL parser outside of the server. We feel this is a better approach because it gives developers 100% confidence in the parser, and it allows us to keep up with the rapid development of Postgres.

this is still in early development, and mostly useful for testers/collaborators. the majority of work is still ahead, but we've verified that the approach works. we're making it public now so that we can develop it in the open with input from the community.

a lot of the credit belongs to pganalyze[1] for their work on libg_query, and to psteinroe (https://github.com/psteinroe) who the creator and maintainer of the LSP.

[0] LSP: https://microsoft.github.io/language-server-protocol/

[1] pganalyze: https://pganalyze.com/

See: https://github.com/microsoft/language-server-protocol/issues/1164

The nxls is a language server based on the Language Server Protocol (LSP) and acts as the “brain” of Nx Console. It analyzes your Nx workspace and provides information on it, including code completion and more.

LSP stands for "Language Server Protocol", which defines how a language server and an editor (client) can communicate to provide code navigation, completion, etc. (source). Traditional IDE's would have something similar to this baked-in already, but proprietary to their software/language; whereas LSP is an open standard, so anything could implement it.