With https://community.ops.io/la3mmchen/grafana-loki-28b9 I've shared some words on Loki as an introduction.
Lets follow up with some practical stuff: How can we run Loki an our local notebook with docker-compose?
Loki
As Grafana provides a good enough container images we just use the one from docker hub to get a local instance running.
---
version: "3.9"
services:
loki:
image: "grafana/loki:2.5.0"
ports:
- "3100:3100"
As Loki follows the unix philosophy "Do One Thing and Do It Well" it's just a backend to send logs to and to query logs from.
Plain speaking: there is no graphical user interface in the Loki server.
We interact with the Loki instance with curl using the http api:
$ curl http://localhost:3100/ready
ready
$ curl http://localhost:3100/loki/api/v1/labels
{"status":"success","data":["__name__"]}
As the second request shows there are not many labels in the system yet.
Lets change this.
interact with curl
Loki offers a http api to send metrics. The data format is described at http push api, we use the following curl to create a new event stream:
$ curl -S -H "Content-Type: application/json" -XPOST -s http://localhost:3100/loki/api/v1/push --data-raw '{"streams": [{ "stream": { "app": "app1" }, "values": [ [ "1653855518000000000", "random log line" ] ] }]}'
$ curl http://localhost:3100/loki/api/v1/labels
{"status":"success","data":["__name__","app"]}
As you can see in the second curl there is now a new label named "app". We can explore possible values for this label with the following curl.
$ curl http://localhost:3100/loki/api/v1/label/app/values
{"status":"success","data":["app1"]}
And finaly see the stream with this label:
$ curl -G -Ss http://localhost:3100/loki/api/v1/query_range --data-urlencode 'query={app="app1"}' | jq .
{
"status": "success",
(...)
"values": [
[
"1653855518000000000",
"random log line"
]
]
}
(...)
(output shorted)
logcli
A more covenient way to interact with Loki from the command line is using logcli
$ LOKI_ADDR=http://localhost:3100 logcli labels
http://localhost:3100/loki/api/v1/labels?end=1653856566774536000&start=1653852966774536000
__name__
app
$ LOKI_ADDR=http://localhost:3100 logcli query '{app=~".+"}'
http://localhost:3100/loki/api/v1/query_range?direction=BACKWARD&end=1653856568404563000&limit=30&query=%7Bapp%3D~%22.%2B%22%7D&start=1653852968404563000
Common labels: {app="app1"}
2022-05-29T22:18:38+02:00 {} random log line
http://localhost:3100/loki/api/v1/query_range?direction=BACKWARD&end=1653855518000000001&limit=30&query=%7Bapp%3D~%22.%2B%22%7D&start=1653852968404563000
Common labels: {app="app1"}
in case you do not want to install logcli locally just add another container to our docker-compose setup from the beginning of this article:
(..)
logcli:
image: "grafana/logcli:2.5.0-amd64"
environment:
- "LOKI_ADDR=http://loki:3100"
with this container you can just do:
$ docker-compose run logcli labels
Creating loki_logcli_run ... done
(..)
__name__
app
following up
in the next post we will add a grafana instance to our docker-compose that will enable us to click something ;-)
references
links
code reference
---
version: "3.9"
services:
loki:
image: "grafana/loki:2.5.0"
ports:
- "3100:3100"
logcli:
image: "grafana/logcli:2.5.0-amd64"
environment:
- "LOKI_ADDR=http://loki:3100"
Top comments (16)
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That’s a solid setup for getting Loki running locally — thanks for sharing such a clear walkthrough! I’ve been working on some local deployments myself and totally get the satisfaction of seeing it run smoothly. After coding sessions like these, I often grab something from the Texas Roadhouse catering menu for the team — their hearty meals make debugging marathons way more enjoyable! You can visit thetexasroadhousemenu.com to explore more about catering menu!
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Here are a few short comment options for Loki, cURL, and LogCLI:
Powerful combo for log management and analysis! 🔥
Loki + cURL + LogCLI = efficient logging workflow. 💻
Great tools for developers and DevOps teams! ⚙️
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Loki, Curl, and Logcli are powerful tools for managing and querying logs efficiently. ⚙️🔥 Together, they make log analysis faster and more flexible — perfect for developers and system admins who need reliable observability and real-time monitoring. Parivahan sewa
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