gomacro
vector
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gomacro | vector | |
---|---|---|
11 | 96 | |
2,134 | 16,512 | |
- | 5.7% | |
6.4 | 9.9 | |
4 months ago | 2 days ago | |
Go | Rust | |
Mozilla Public License 2.0 | Mozilla Public License 2.0 |
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gomacro
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Go superset
gomacro added macros and generics several years before generics reached release.
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Alternative REPL to "gore"
I use https://github.com/cosmos72/gomacro when I want to quickly try some code.
- Gomacro: Go Interpreter and REPL
- Interpreters built in Go
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".. beat the Crap out of ..", really liked that wording. You can't trump that.
Officially, it's not much scripting friendly, but there are unofficial support to make it a proper scripting option like the gomacro.
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How to run a go main package from another go program?
If it's a simple program I guess you could use gomacro:https://github.com/cosmos72/gomacro
- Scripting in Go
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go-notebook
Thanks to gomacro we can import no standard libraries on the notebook :P
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DoorDash: Migrating From Python to Kotlin for Our Backend Services
For our use (debugging and running small scripts to update data), gomacro should work well enough, despite being an "almost complete" Go interpreter. This isn't the same as the Python REPL which uses entirely the same code to run, but it should be up to the task.
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Hy: A dialect of Lisp that's embedded in Python
I keep meaning to play with https://github.com/cosmos72/gomacro
vector
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
job "vector" { datacenters = ["dc1"] # system job, runs on all nodes type = "system" group "vector" { count = 1 network { port "api" { to = 8686 } } ephemeral_disk { size = 500 sticky = true } task "vector" { driver = "docker" config { image = "timberio/vector:0.30.0-debian" ports = ["api"] volumes = ["/var/run/docker.sock:/var/run/docker.sock"] } env { VECTOR_CONFIG = "local/vector.toml" VECTOR_REQUIRE_HEALTHY = "false" } resources { cpu = 100 # 100 MHz memory = 100 # 100MB } # template with Vector's configuration template { destination = "local/vector.toml" change_mode = "signal" change_signal = "SIGHUP" # overriding the delimiters to [[ ]] to avoid conflicts with Vector's native templating, which also uses {{ }} left_delimiter = "[[" right_delimiter = "]]" data=<
- FLaNK AI Weekly 18 March 2024
- Vector: A high-performance observability data pipeline
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Hacks to reduce cloud spend
we are doing something similar with OTEL but we are looking at using https://vector.dev/
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About reading logs
We don't pull logs, we forward logs to a centralized logging service.
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Self hosted log paraer
opensearch - amazon fork of Elasticsearch https://opensearch.org/docs/latestif you do this an have distributed log sources you'd use logstash for, bin off logstash and use vector (https://vector.dev/) its better out of the box for SaaS stuff.
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creating a centralize syslog server with elastic search
I have done something similar in the past: you can send the logs through a centralized syslog servers (I suggest syslog-ng) and from there ingest into ELK. For parsing I am advice to use something like Vector, is a lot more faster than logstash. When you have your logs ingested correctly, you can create your own dashboard in Kibana. If this fit your requirements, no need to install nginx (unless you want to use as reverse proxy for Kibana), php and mysql.
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Show HN: Homelab Monitoring Setup with Grafana
I think there's nothing currently that combines both logging and metrics into one easy package and visualizes it, but it's also something I would love to have.
Vector[1] would work as the agent, being able to collect both logs and metrics. But the issue would then be storing it. I'm assuming the Elastic Stack might now be able to do both, but it's just to heavy to deal with in a small setup.
A couple of months ago I took a brief look at that when setting up logging for my own homelab (https://pv.wtf/posts/logging-and-the-homelab). Mostly looking at the memory usage to fit it on my synology. Quickwit[2] and Log-Store[3] both come with built in web interfaces that reduce the need for grafana, but neither of them do metrics.
- [1] https://vector.dev
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Retaining Logs generated by service running in pod.
Log to stdout/stderr and collect your logs with a tool like vector (vector.dev) and send it to something like Grafana Loki.
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Lightweight logging on RPi?
I would recommend that you run vector as a systems service so you don't have to worry about managing it. Here is a basic config to do that - https://github.com/vectordotdev/vector/blob/master/distribution/systemd/vector.service .
What are some alternatives?
yaegi - Yaegi is Another Elegant Go Interpreter
graylog - Free and open log management
gophernotes - The Go kernel for Jupyter notebooks and nteract.
Fluentd - Fluentd: Unified Logging Layer (project under CNCF)
mypyc - Compile type annotated Python to fast C extensions
agent - Vendor-neutral programmable observability pipelines.
hissp - It's Python with a Lissp.
syslog-ng - syslog-ng is an enhanced log daemon, supporting a wide range of input and output methods: syslog, unstructured text, queueing, SQL & NoSQL.
beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
OpenSearch - 🔎 Open source distributed and RESTful search engine.
go-pry - An interactive REPL for Go that allows you to drop into your code at any point.
tracing - Application level tracing for Rust.