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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteThe shortest path to a useful local Loki installation is a Docker Compose stack containing Loki, Grafana Alloy, and Grafana. Alloy collects container logs and forwards them to Loki; Grafana lets you inspect and query the resulting streams. Treat this setup as an evaluation environment, not a production design. The sequence is: start the documented example, confirm each service is ready, check that logs arrive, then learn LogQL from label selectors to filters, parsing, and metric queries.
What you are building
Loki stores compressed log data and indexes stream metadata rather than the full text of every line. A local tutorial therefore needs three cooperating services:
- Loki: receives and stores log streams.
- Grafana Alloy: tails the example containers’ logs and forwards them to Loki.
- Grafana: provides Explore and Logs Drilldown for searching and visualizing the data.
Grafana publishes two local learning paths. The Quickstart to run Loki locally uses an evaluate-loki Compose example with sample log generation, Alloy, Loki, Grafana, and supporting services. The newer Loki Tutorial uses a single-binary (monolithic) Loki stack and a repository branch named getting-started. Both are documented procedures; choose one rather than combining files from both.
Prerequisites and the right tutorial path
Operating system
The newer tutorial assumes Linux or macOS. On Windows, use Windows Subsystem for Linux and run the Linux commands there. The quickstart is documented for Linux. Install Docker Engine or Docker Desktop with the Compose subcommand available as docker compose.
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Learning versus production
Docker and Compose are the documented choices for evaluation, testing, and development. Grafana recommends Helm or Tanka when you need a production deployment. The quickstart’s Simple Scalable Deployment mode is deprecated and scheduled for removal in Loki 4.0; verify the current deployment documentation before relying on that mode for anything durable.
Start the documented Compose example
For a first run, follow the newer tutorial’s repository-based procedure. Clone the getting-started branch of Grafana’s loki-fundamentals repository using the clone command shown on the current tutorial page, then enter the directory that contains its Compose file. Because repository locations and branch contents can change, copy the command and directory name from that page rather than substituting an unpinned example.
- Open a terminal in the tutorial directory.
- Start the stack in the background:
docker compose up -d - List service state and published ports:
docker compose ps - Read startup output if a service is not healthy:
docker compose logs --tail=200 loki
and repeat foralloyorgrafanawhen needed.
The quickstart follows the same Compose lifecycle but uses its own evaluate-loki files and sample generator. Do not copy a selector such as evaluate-loki-flog-1 into the other tutorial and expect it to exist.
Verify the services before querying
Verification prevents confusing an empty result with a broken query. The tutorial’s checks are:
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- Alloy: open the Alloy user interface and confirm its configuration is loaded and its log pipeline is running.
- Grafana: open the local Grafana URL printed by the Compose configuration, sign in with the credentials supplied by that example, and confirm that a Loki data source is configured.
- Loki: inspect its metrics endpoint or the service logs to confirm it is accepting requests.
- Incoming logs: in Grafana, open Explore (or the example’s Logs Drilldown view), select Loki, and run a broad query. You should see lines from the containers that Alloy tails.
Port numbers, initial credentials, and container names belong to the particular example files. Read those files or the current tutorial page instead of assuming a universal default.
Your first LogQL queries
Grafana’s rule is simple: Loki queries always start with a label selector.
A selector chooses streams by labels; filters and parsers then examine the lines inside those streams.
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1. Select one stream
{container="evaluate-loki-flog-1"}This example selects a container label used by the evaluation stack. If your result is empty, inspect the label browser in Explore and substitute a label value that actually exists in your deployment.
2. Filter text in matching lines
{container="evaluate-loki-flog-1"} |= "status"The |= operator keeps lines containing the literal text. Other line-filter operators can exclude text or use a regular expression; start with a literal filter while learning.
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{container="evaluate-loki-flog-1"} | json | status=`404`| json extracts fields from JSON log lines. The final expression keeps entries whose parsed status field is 404. Parsing happens after stream selection, so it does not replace the selector.
4. Turn logs into a metric
Use a metric query only after selectors and parsing make sense. Grafana’s progression demonstrates counting lines over time and aggregating by container:
sum by (container) (rate({container=~".+"}[1m]))The exact aggregation expression in your example may differ; the important model is that a range such as [1m] feeds rate, and an aggregation groups the resulting series. Keep high-cardinality values out of labels unless you have a specific operational reason.
Labels: the design decision that shapes every query
A Loki stream is identified by its label set. Labels describe log origin and make selection efficient; Grafana’s overview gives region, cluster, and environment as examples. You may also see labels for containers, jobs, namespaces, or hosts supplied by the collector configuration.
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- Use stable attributes that meaningfully partition streams.
- Discover the labels your Alloy pipeline actually emits before writing dashboards.
- Put rapidly changing request IDs or user IDs in the log body, not automatically into labels; excessive distinct values create many streams and complicate operations.
There is no single mandatory schema in the introductory material. Begin with the labels already present in the example, then change Alloy’s configuration deliberately and update queries with it.
Troubleshooting an empty or failing setup
No containers are running
Run docker compose ps. If a service exited, inspect docker compose logs SERVICE. Typical causes are a port already in use, insufficient Docker resources, or a configuration file copied from a different tutorial. Stop unrelated containers or change the conflicting port in the example’s Compose file, then recreate the stack with docker compose up -d.
Grafana opens but shows no Loki data source
Use the data-source configuration shipped with the selected tutorial. If provisioning did not load, inspect Grafana logs and the mounted provisioning path; do not mix the quickstart’s files with the monolithic tutorial’s files.
Alloy is healthy but streams are empty
Confirm that the sample containers are producing output and that Alloy’s UI shows an active tailing pipeline. Check the Loki endpoint configured in Alloy and inspect Alloy logs for connection or permission errors. Then refresh Explore and widen the time range.
A copied selector returns no lines
Container names differ between examples and may gain a Compose project prefix. In Explore, open the label values, choose an existing container value, and rerun the query. Also check the selected time range; a quiet generator can legitimately produce no entries.
JSON parsing produces errors or no matches
Use | json only on lines that are JSON. First run the stream selector without parsing, inspect a raw line, and then filter the field name and type exactly as emitted. A numeric field and a quoted string are not interchangeable.
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Check the published ports in docker compose ps, local firewall rules, and whether the service binds only to the loopback interface. Accessing a container name from the host is not the same as accessing it from another container; use the network and endpoint values supplied by the Compose configuration.
Security and production boundaries
Grafana states that Loki does not include an authentication layer. Never expose a local Loki HTTP endpoint directly to an untrusted network. Put an authenticating reverse proxy in front of Loki services, restrict network access, and configure TLS and authorization at that boundary.
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curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://grafana.example.com/d/your-dashboard -o dashboard.webpPython:
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r = requests.get("https://api.screenshotneo.com/v1/shot", params={"access_key": "YOUR_API_KEY", "url": "https://grafana.example.com/d/your-dashboard"}, timeout=90)
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FAQ
Can I run Loki without Grafana Alloy?
Loki can receive logs from other agents, but the documented beginner stack includes Alloy so the Compose example has a collector and forwarding pipeline. Removing it means designing and configuring another client yourself.
Why does a LogQL query begin with braces?
Braces contain the stream selector, for example {environment="dev"}. LogQL requires that initial label selection before line filters, parsers, or metric functions.
Is the local Compose stack suitable for a public service?
No. It is an evaluation and development path. Public access requires authentication in front of Loki and a production deployment model with explicit storage, scaling, and operational controls.
Frequently Asked Questions
Can I run Loki without Grafana Alloy?
Loki can receive logs from other agents, but the documented beginner stack includes Alloy so the Compose example has a collector and forwarding pipeline. Removing it means designing and configuring another client yourself.
Why does a LogQL query begin with braces?
Braces contain the stream selector, for example {environment="dev"}. LogQL requires that initial label selection before line filters, parsers, or metric functions.
Is the local Compose stack suitable for a public service?
No. It is an evaluation and development path. Public access requires authentication in front of Loki and a production deployment model with explicit storage, scaling, and operational controls.
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