The last time I configured Loki for logs collecting and monitoring was in February — almost a year ago, see the Grafana Labs: Loki — logs collecting and monitoring system post, when Loki was in its Beta state. The setup described below is more Proof of Concept as the Loki itself and its support in Grafana still under development. But now the Explore feature in Grafana supports aggregation and counting functions similarly to Prometheus — sumrateetc.
The promtail during the last year also added some new interesting abilities which will we use in this post. Loki will start by Docker Compose, create a loki-stack. In the same way repeat with Grafana using the 6. Log in with admin:admingo to the Datasources :. For now, there is nothing in the Grafana Explore as no logs are sent to the Loki yet.
Add the promtail to the Compose file, mount the config in there and specify a command for the promtail to let it know which config file to use:. The promtail 's output:. And check in the Grafana Explore:. Create a promtail 's config promtail-dev. And why no logs are tailed? And what happened with Loki? Well, can try to re-create containers:. Good — that helped, Loki went back now.
And it is caused by the… Spaces! It was a bit weird, but it works. In Grafana 6. Go to the Datasourcesand add Prometheus — but as Loki. Or Loki — as a Prometheus? And one new? A pipeline is used to transform a single log line, its labels, and its timestamp. A pipeline is comprised of a set of stages. There are 4 types of stages:. Filtering stages optionally apply a subset of stages or drop entries based on some condition.Loki is a Prometheus-inspired logging service for cloud native infrastructure.
Open sourced by Grafana Labs during KubeCon SeattleLoki is a logging backend optimized for users running Prometheus and Kubernetes with great logs search and visualization in Grafana 6. Loki was built for efficiency alongside the following goals:. As said, Loki is designed for efficiency to work well in the Kubernetes context in combination with Prometheus metrics.
The idea is to switch easily between metrics and logs based on Kubernetes labels you already use with Prometheus. Unlike most logging solutions, Loki does not parse incoming logs or do full-text indexing. This makes it significantly more efficient to scale and operate.
The logs are ingested via the API and an agent, called Promtail Tailing logs in Prometheus formatwill scrape Kubernetes logs and add label metadata before sending it to Loki.
This metadata addition is exactly the same as Prometheus, so you will end up with the exact same labels for your resources.
The easiest way to deploy Loki on your Kubernetes cluster is by using the Helm chart available in the official repository. You can follow the setup guide from the official repo.Session 1 (Monitoring): Infrastructure monitoring with Prometheus, Node Exporter and Grafana
This will deploy Loki and Promtail. Promtail is the metadata appender and log sending agent. The Promtail configuration you get from the Helm chart is already configured to get all the logs from your Kubernetes cluster and append labels on it as Prometheus does for metrics. However, you can tune the configuration for your needs. For example, if you want to get logs only for the kube-system namespace:.
For example, if you want to exclude logs from kube-system namespace:. For more info on the configuration, you can refer to the official Prometheus configuration documentation. It has a lot of input plugins and good filtering built-in.
You can refer to the installation guide on how to use the fluentd Loki plugin. Here is the fluentd configuration:. By default, Promtail is configured to automatically scrape logs from containers and send them to Loki.
Those logs come from stdout. But sometimes, you may like to be able to send logs from an external file to Loki. In this case, you can set up Promtail as a sidecar, i. Assuming you have an application simple-logger.On By Julien Garcia Gonzalez in tech.
Loki is a Prometheus-inspired logging service for cloud native infrastructure. Open sourced by Grafana Labs during KubeCon SeattleLoki is a logging backend optimized for users running Prometheus and Kubernetes with great logs search and visualization in Grafana 6.
As said, Loki is designed for efficiency to work well in the Kubernetes context in combination with Prometheus metrics. The idea is to switch easily between metrics and logs based on Kubernetes labels you already use with Prometheus. This makes it significantly more efficient to scale and operate. The logs are ingested via the API and an agent, called Promtail Tailing logs in Prometheus formatwill scrape Kubernetes logs and add label metadata before sending it to Loki.
This metadata addition is exactly the same as Prometheus, so you will end up with the exact same labels for your resources. The easiest way to deploy Loki on your Kubernetes cluster is by using the Helm chart available in the official repository. You can follow the setup guide from the official repo. Add Loki datasource in Grafana built-in support for Loki is in 6. The Promtail configuration you get from the Helm chart is already configured to get all the logs from your Kubernetes cluster and append labels on it as Prometheus does for metrics.
For example, if you want to get logs only for the kube-system namespace:. For example, if you want to exclude logs from kube-system namespace:. For more info on the configuration, you can refer to the official Prometheus configuration documentation. Fluentd is a well-known and good log forwarder that is also a CNCF project. It has a lot of input plugins and good filtering built-in. You can refer to the installation guide on how to use the fluentd Loki plugin.
By default, Promtail is configured to automatically scrape logs from containers and send them to Loki. Those logs come from stdout. In this case, you can set up Promtail as a sidecar, i. Assuming you have an application simple-logger.
So Loki looks very promising. The footprint is very low. It integrates nicely with Grafana and Prometheus. Having the same labels as in Prometheus is very helpful to map incidents together and quickly find logs related to metrics.
Another big point is the simple scalability, Loki is horizontally scalable by design. As Loki is currently alpha software, install it and play with it. Then, join us on grafana. Interested in finding out how Giant Swarm handles the entire cloud native stack including Loki?
Open Source is at the heart of what we do at Grafana Labs. Grafana v6. In Grafana v5. Viewing Loki data in dashboard panels is supported in Grafana v6. Just add it as a data source and you are ready to query your log data in Explore. You can use this functionality to link to your tracing backend directly from your logs, or link to a user profile page if a userId is present in the log line. These links will be shown in the log details.
Each derived field consists of:. You can use a debug section to see what your fields extract and how the URL is interpolated. Click Show example log message to show the text area where you can enter a log message.
The new field with the link shown in log details:. Querying and displaying log data from Loki is available via Exploreand with the logs panel in dashboards. Select the Loki data source, and then enter a log query to display your logs. A log query consists of two parts: log stream selectorand a search expression. For performance reasons you need to start by choosing a log stream by selecting a log label. The Logs Explorer the Log labels button next to the query field shows a list of labels of available log streams.
Press the enter key to execute the query. Multiple label expressions are separated by a comma:. Another way to add a label selector, is in the table section, clicking on the Filter button beside a label will add the label to the query expression.
This even works for multiple queries and will the label selector to each query. After writing the Log Stream Selector, you can filter the results further by writing a search expression. The search expression can be just text or a regex expression. Filter operators can be chained and will sequentially filter down the expression.
The resulting log lines will satisfy every filter. Loki supports Live tailing which displays logs in real-time. This feature is supported in Explore. Note that Live Tailing relies on two Websocket connections: one between the browser and the Grafana server, and another between the Grafana server and the Loki server. If you run any reverse proxies, please configure them accordingly.
Run Grafana Docker image
When using a search expression as detailed above, you now have the ability to retrieve the context surrounding your filtered results. Instead of hard-coding things like server, application and sensor name in your metric queries, you can use variables in their place. Variables are shown as drop-down select boxes at the top of the dashboard. These drop-down boxes make it easy to change the data being displayed in your dashboard.
Check out the Templating documentation for an introduction to the templating feature and the different types of template variables. You can use any non-metric Loki query as a source for annotations.
Log content will be used as annotation text and your log stream labels as tags, so there is no need for additional mapping.
Using Loki in Grafana
You can read more about how it works and all the settings you can set for data sources on the provisioning docs page. Grafana Cloud. Your browser does not support the video tag.
Terms of Service.Docker logging driver plugins extends Docker's logging capabilities. You can use Loki Docker logging driver plugin to send Docker container logs directly to your Loki instance or Grafana Cloud. Docker plugins are not yet supported on Windows; see Docker's logging driver plugin documentation.
If you have any questions or issues using the Docker plugin feel free to open an issue in this repository. You need to install the plugin on each Docker host with container from which you want to collect logs. You can install the plugin from our Docker hub repository by running on the Docker host the following command:. To check the status of installed plugins, use the docker plugin ls command. Plugins that start successfully are listed as enabled in the output:.
The Docker daemon on each Docker host has a default logging driver; each container on the Docker host uses the default driver, unless you configure it to use a different logging driver. Even if the container uses the default logging driver, it can use different configurable options. The following command configure the container grafana to start with the Loki drivers which will send logs to logs-us-west1.
Note : The Loki logging driver still uses the json-log driver in combination with sending logs to Loki, this is mainly useful to keep the docker logs command working.
You can adjust file size and rotation using the respective log option max-size and max-file. You can deactivate this behavior by setting the log option no-file to true. To configure the Docker daemon to default to Loki logging driver, set the value of log-driver to loki logging driver in the daemon.
The following example explicitly sets the default logging driver to Loki:. The logging driver has configurable options, you can set them in the daemon. The following example sets the Loki push endpoint and batch size of the logging driver:. Note : log-opt configuration options in the daemon.
Boolean and numeric values such as the value for loki-batch-size in the example above must therefore be enclosed in quotes ". Restart the Docker daemon and it will be configured with Loki logging driver, all containers from that host will send logs to Loki instance. You can also configure the logging driver for a swarm service directly in your compose file, this also work for a docker-compose deployment:. Note : stack name and service name for each swarm service and project name and service name for each compose service are automatically discovered and sent as Loki labels, this way you can filter by them in Grafana.
Loki can received a set of labels along with log line. These labels are used to index log entries and query back logs using LogQL stream selector. You can add more labels by using loki-external-labelsloki-pipeline-stage-filelabelsenv and env-regex options as described below.
Plugin logs can be found as docker daemon log. Depending on your system, location of Docker daemon logging may vary. Refer to Docker documentation for Docker daemon log location for your specific platform.
Skip to content. Branch: master. Create new file Find file History. Latest commit. See dicussions hereit seems that it can be confusing when using docker-compose.
Latest commit e4d78b9 Apr 16, Docker plugins are not yet supported on Windows; see Docker's logging driver plugin documentation If you have any questions or issues using the Docker plugin feel free to open an issue in this repository. Plugin Installation You need to install the plugin on each Docker host with container from which you want to collect logs.
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You signed out in another tab or window.At one of our customers we build a synthetic monitoring platform on top of Amazon Web Services AWS since due to very special requirements existing solutions are not sufficient for us.
To speed up development the synthetic checks are deployed as Lambda functions. Check results and metrics, collected with OpenCensusare stored in Prometheus and visualized with Grafana. This setups works pretty well, except for one little glitch. Developers are not able to access the Lambda execution logs! Why is this problematic? Lokia CNCF incubator project, is a Prometheus-inspired logging backend for cloud native applications.
Contrary to other logging solutions, Loki does not do full indexing or parse the incoming log stream. Instead, Loki indexes and groups log streams using the same labels already used with Prometheus. Starting with version 6. Grafana offers a full fledged exploring and visualization datasource for Loki. Thus, Loki and Grafana can be considered as a perfect match. Anyway, Loki is still beta software and not yet considered as production ready. After reading about Loki for the first time, we knew that we wanted to integrate it into our platform!
If this works out nicely, we would have solved our logging challenge and defined a single place of visualization for metrics as well as logs.
As shown in the figure below, the idea was quite simple. Since almost all our components were implemented as Lambda functions, the Loki-Shipper should also be one of them. High-level overview how logs are shipped from CloudWatch to Loki. Our setup did not include a Kubernetes cluster.
Hence, we did not use Loki as it was initially optimized for. Especially, w. A log stream is a sequence of log events that share the same source. Each separate source of logs into CloudWatch Logs makes up a separate log stream. A log group is a group of log streams that share the same retention, monitoring, and access control settings.Learn about Grafana the monitoring solution for every database.
Grafana Logging using Loki
Open Source is at the heart of what we do at Grafana Labs. Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate. It does not index the contents of the logs, but rather a set of labels for each log stream.
Loki is released under the Apache 2. Grafana Labs is proud to lead the development of the Loki project, building first-class support for Loki into Grafana, and ensuring Grafana Labs customers receive Loki support and features they need.
Learn more. Sign up now. Contact us now. Grafana Cloud. Loki Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. Want to work on Loki? Products and Services. Grafana Cloud: Hosted Logs Use our high-performance, hosted Loki service to store all your logs together in a single place.
Durably store logs for 30 days. No commitments: Pay for only what you use with our usage-based pricing. Enterprise Support for Loki Get support and training from Loki maintainers and experts.
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