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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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lowdefy
The config web stack for business apps - build internal tools, client portals, web apps, admin panels, dashboards, web sites, and CRUD apps with YAML or JSON.
cough how can you leave out https://github.com/purpleidea/mgmt/ =D
https://cuetorials.com/ is probably more hands-on than the homepage which is slightly more theoretical. For validating sequences see https://cuelang.org/docs/tutorials/tour/types/lists/ .
Started working on a JS version a few weeks ago [1]. Even with 20% of the features it’s already so useful we’re building systems with it. And not just config - model all the things!
Overrides and inheritance are a world of pain. Unification and commutative operations restore sanity to the actual work of coding with a domain representation language because WYSIWYG. And you get type safety for your domain model.
The project is still at the “Read the Source, Luke” stage so caveat emptor until we get a respectable release out.
* https://github.com/rjrodger/aontu
Is there any plans to support model generation in future as can be done with JSON schema through something like https://github.com/quicktype/quicktype ?
If you are looking to do data validation from the JVM, you may try Baleen (written in Kotlin): https://github.com/ShopRunner/baleen/
I'm one of the contributors. We created a DSL in the language to describe the data and create tests. You can then use that data description to validate against json, csv, avro... One of the neat things we came up with was the concept of a data trace which is like a stack trace but is a path through the data to a particular error.
re: Grafana (i'm the author of the linked issue) - i'm quite excited, i do think there's a world of possibilities here.
Two-way sync with a git repo is one possible path, and we've talked a lot internally at GL about how to best support it. My sense is that we can do it with relatively little friction and likely will - but if you're just syncing with a git repo, there's still a lot of arbitrary, opaque repo layout decisions that still have to be made (how do you map a filesystem position for a dashboard to a position in Grafana? In a way that places the dashboards next to the systems they're intended to observe? With many teams? With many Grafana instances?) which induce new kinds of friction at scale.
Fortunately - and not mutually exclusively with the above - by building the system for schema in CUE, we've made a composable thing that we can make into larger systems. That's what we're starting to do with Polly: https://github.com/pollypkg/polly
Conveniently, my parts of a Grafanaconline talk tomorrow discusses both of these https://grafana.com/go/grafanaconline/2021/dashboards-as-cod... :D
Very excited to see someone doing this! Right now, Grafana is [planned to] relying on an anemic CUE->Typescript translator for getting its schema to the frontend - https://github.com/sdboyer/cuetsy. (Somebody also pointed me to Project Cambria recently, which could be an interesting compilation target for what we have https://www.inkandswitch.com/cambria.html)
Being able to work with CUE natively in TS, though, would be a huge gamechanger for what we can do with CUE in Grafana
We've been building dashboards in YAML for a while now using Lowdefy - https://github.com/lowdefy/lowdefy
It is very flexible. Will publish more examples soon!