Stream Logs from Two Services in a Single Docker Container to Grafana Cloud Loki with Alloy

Hello, I'm Maneshwar. I'm building git-lrc, an AI code reviewer that runs on every commit. It is free, unlimited, and source-available on Github. Star Us to help devs discover the project. Do give it a try and share your feedback for improving the product.

I'm working on FreeDevTools online currently building **one place for all dev tools, cheat codes, and TLDRs** — a free, open-source hub where developers can quickly find and use tools without any hassle of searching all over the internet.

Stream Logs from Multiple DockerServices to Grafana Cloud with Alloy (Part 2)

In Part 1, we set up a basic pipeline using Grafana Alloy to stream logs from a Docker container to Grafana Cloud Loki.

Now let’s level up.

This time, we’re collecting logs from two services — liveapi-backend an
d runner — each writing to their own file, and we’ll push them to Loki with proper labels so filtering and visualizing in Grafana feels effortless.

The Services

We’re logging from two separate backend services inside our containerized environment:

• liveapi-backend → /code/liveapi-backend/liveapi.log
• runner → /code/runner/runner.log

Each of these logs need to be:

• Watched by Alloy
• Parsed and labeled
• Shipped to Grafana Cloud Loki

Let’s walk through the configuration.

The Config File

Path: /etc/alloy/config.alloy

# Match log file paths for both services
local.file_match "liveapi_backend" {
  path_targets = [
    { "__path__" = "/code/liveapi-backend/liveapi.log" }
  ]
  sync_period = "5s"
}

local.file_match "runner" {
  path_targets = [
    { "__path__" = "/code/runner/runner.log" }
  ]
  sync_period = "5s"
}

# Source log lines from files and send to processors
loki.source.file "liveapi_backend_log_scrape" {
  targets       = local.file_match.liveapi_backend.targets
  forward_to    = [loki.process.liveapi_backend_filter_logs.receiver]
  tail_from_end = true
}

loki.source.file "runner_log_scrape" {
  targets       = local.file_match.runner.targets
  forward_to    = [loki.process.runner_filter_logs.receiver]
  tail_from_end = true
}

# Attach static labels to each log line
loki.process "liveapi_backend_filter_logs" {
  forward_to = [loki.write.grafana_loki.receiver]

  stage.static_labels {
    values = {
      job          = "liveapi-backend"
      service_name = "liveapi-backend"
    }
  }
}

loki.process "runner_filter_logs" {
  forward_to = [loki.write.grafana_loki.receiver]

  stage.static_labels {
    values = {
      job          = "liveapi-runner"
      service_name = "liveapi-runner"
    }
  }
}

# Loki write target — this is your Grafana Cloud endpoint
loki.write "grafana_loki" {
  endpoint {
    url = "https://YOUR_INSTANCE_ID:[e-mail]/api/prom/push"
  }
}

Replace the url with your actual Grafana Cloud Loki push endpoint.

You can find it under Logs → Details → Grafana Agent in your Grafana Cloud account.

Breakdown: What’s Happening?

Let’s decode the setup:

local.file_match

These blocks define which files Alloy watches and how often it checks for changes (sync_period).

loki.source.file

This is where log ingestion begins. Each source:

• Reads logs from the matched file path
• Starts tailing from the end (avoids re-sending old logs)
• Sends logs to the defined processor

loki.process

Adds metadata (aka labels) to each log line. These are critical for querying in Grafana. You can add whatever makes sense — service_name, env, region, etc.

loki.write

Defines the output — in our case, Grafana Cloud Loki. The URL includes:

• Your Grafana Cloud ID
• A Loki API key with write permissions

Useful Commands

Need to troubleshoot or inspect your setup?

Validate syntax and format the config

alloy fmt <config.alloy>

View the config

sudo cat /etc/alloy/config.alloy

Restart Alloy

sudo systemctl restart alloy

View logs (if running under systemd)

journalctl -u alloy -n 50 --no-pager

If journalctl isn’t available (common in Docker):

alloy run /etc/alloy/config.alloy > /var/log/alloy.log 2>&1 &

This will run Alloy in the background and dump its logs to /var/log/alloy.log.

Use tail -f /var/log/alloy.log to monitor.

Syntax Help

Want to learn more about the config language? Alloy uses a custom HCL-inspired syntax.
You can explore the syntax rules here:

🔗 https://grafana.com/docs/alloy/latest/get-started/configuration-syntax/syntax/

---

🧑‍🎨 Visual Config Generator

You don’t have to write everything by hand.

Use the Alloy Configurator to visually create a config file.

🚦 Final Thoughts

This setup gives you fine-grained control over what you ship and how you tag it.

With Alloy and Grafana Cloud Loki, you're not just centralizing logs — you’re making them searchable, filterable, and visual.

You can now:

• Split logs by service
• Add filters in Grafana using labels like {job="liveapi-runner"}
• Build dashboards basedon log content

I’ve been building A collection of UI/UX-focused tools crafted to simplify workflows, save time, and reduce friction in searching tools/materials.

Any feedback or contributors are welcome!

It’s online, open-source, and ready for anyone to use.

👉 Check it out: ⭐ Star it on GitHub: Let’s make it even better together.

*AI agents write code fast. They also silently remove logic, change behavior, and introduce bugs -- without telling you. You often find out in production.

git-lrc fixes this. It hooks into git commit and reviews every diff before it lands. 60-second setup. Completely free.*

Any feedback or contributors are welcome! It's online, source-available, and ready for anyone to use.

⭐ Star it on GitHub:

HexmosTech / git-lrc

Free, Unlimited AI Code Reviews That Run on Commit

git-lrc

Free, Unlimited AI Code Reviews That Run on Commit

---

AI agents write code fast. They also silently remove logic, change behavior, and introduce bugs -- without telling you. You often find out in production.

git-lrc fixes this. It hooks into git commit and reviews every diff before it lands. 60-second setup. Completely free.

See It In Action

See git-lrc catch serious security issues such as leaked credentials, expensive cloud operations, and sensitive material in log statements

git-lrc-intro-60s.mp4

Why

• 🤖 AI agents silently break things. Code removed. Logic changed. Edge cases gone. You won't notice until production.
• 🔍 Catch it before it ships. AI-powered inline comments show you exactly what changed and what looks wrong.
• 🔁 Build a habit, ship better code. Regular review → fewer bugs → more robust code → better results in your team.
• 🔗 Why git? Git is universal. Every editor, every IDE, every AI…

View on GitHub