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Docs: updates for file-based menu (#28500)
* initial * cleanup * remove bad aliases * cleanup, fix links * add docs-file-based-command * update docs * update readme * fix broken links * fix spelling Co-authored-by: Diana Payton <52059945+oddlittlebird@users.noreply.github.com>
This commit is contained in:
Robby Milo
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title = "Getting started"
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type = "docs"
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[menu.docs]
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name = "Getting started"
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identifier = "getting-started"
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weight = 10
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title = "Getting started with Grafana and Prometheus"
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description = "Guide for getting started with Grafana"
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keywords = ["grafana", "intro", "guide", "started"]
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type = "docs"
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aliases = ["/docs/grafana/latest/guides/gettingstarted","/docs/grafana/latest/guides/getting_started"]
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[menu.docs]
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identifier = "getting_started-grafana-prometheus"
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parent = "guides"
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weight = 300
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title = "Getting started with Grafana"
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description = "Guide for getting started with Grafana"
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keywords = ["grafana", "intro", "guide", "started"]
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type = "docs"
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aliases = ["/docs/grafana/latest/guides/gettingstarted","/docs/grafana/latest/guides/getting_started"]
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[menu.docs]
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identifier = "getting_started-grafana"
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parent = "guides"
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weight = 200
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@ -43,7 +39,7 @@ To create your first dashboard:
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## Next steps
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Continue to experiment with what you have built, try the [explore workflow]({{< relref "../explore/index.md" >}}) or another visualization feature. Refer to [Data sources]({{< relref "../datasources/_index.md" >}}) for a list of supported data sources and instructions on how to [add a data source]({{< relref "../datasources/add-a-data-source.md" >}}). The following topics will be of interest to you:
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Continue to experiment with what you have built, try the [explore workflow]({{< relref "../explore/index.md" >}}) or another visualization feature. Refer to [Data sources]({{< relref "../datasources" >}}) for a list of supported data sources and instructions on how to [add a data source]({{< relref "../datasources/add-a-data-source.md" >}}). The following topics will be of interest to you:
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- [Panels]({{< relref "../panels/panels-overview.md" >}})
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- [Dashboards]({{< relref "../dashboards/_index.md" >}})
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title = "Glossary"
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description = "Grafana glossary"
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keywords = ["grafana", "intro", "glossary", "dictionary"]
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type = "docs"
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aliases = ["/docs/grafana/latest/guides/glossary"]
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[menu.docs]
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name = "Glossary"
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identifier = "glossary"
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parent = "guides"
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weight = 500
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@ -114,7 +109,7 @@ This topic lists words and abbreviations that are commonly used in the Grafana d
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<tr>
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<td style="vertical-align: top">Transformation</td>
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<td>
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Transformations process the result set of a query before it’s passed on for visualization.
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Transformations process the result set of a query before it’s passed on for visualization.
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</td>
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</tr>
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<tr>
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title = "Histograms and heatmaps"
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description = "An introduction to histograms and heatmaps"
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keywords = ["grafana", "heatmap", "panel", "documentation", "histogram"]
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type = "docs"
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[menu.docs]
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name = "intro-to-histograms"
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parent = "panels"
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weight = 400
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title = "Time series dimensions"
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description = "time series dimensions"
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keywords = ["grafana", "intro", "guide", "concepts", "timeseries", "labels"]
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type = "docs"
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aliases = ["/docs/grafana/latest/guides/timeseries-dimensions"]
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[menu.docs]
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name = "Time series dimensions"
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identifier = "time_series_dimensions"
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parent = "guides"
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weight = 300
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title = "Time series"
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description = "Introduction to time series"
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keywords = ["grafana", "intro", "guide", "concepts", "timeseries"]
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type = "docs"
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aliases = ["/docs/grafana/latest/guides/timeseries"]
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[menu.docs]
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name = "Time series"
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identifier = "time_series"
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parent = "guides"
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weight = 300
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@ -38,7 +33,7 @@ While each of these examples are sequences of chronologically ordered measuremen
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- New data is appended at the end, at regular intervals—for example, hourly at 09:00, 10:00, 11:00, and so on.
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- Measurements are seldom updated after they were added—for example, yesterday's temperature doesn't change.
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Time series are powerful. They help you understand the past by letting you analyze the state of the system at any point in time. Time series could tell you that the server crashed moments after the free disk space went down to zero.
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Time series are powerful. They help you understand the past by letting you analyze the state of the system at any point in time. Time series could tell you that the server crashed moments after the free disk space went down to zero.
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Time series can also help you predict the future, by uncovering trends in your data. If the number of registered users has been increasing monthly by 4% for the past few months, you can predict how big your user base is going to be at the end of the year.
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@ -65,9 +60,9 @@ In the IT industry, time series data is often collected to monitor things like i
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### Time series databases
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A time series database (TSDB) is a database explicitly designed for time series data. While it's possible to use any regular database to store measurements, a TSDB comes with some useful optimizations.
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A time series database (TSDB) is a database explicitly designed for time series data. While it's possible to use any regular database to store measurements, a TSDB comes with some useful optimizations.
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Modern time series databases take advantage of the fact that measurements are only ever appended, and rarely updated or removed. For example, the timestamps for each measurement change very little over time, which results in redundant data being stored.
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Modern time series databases take advantage of the fact that measurements are only ever appended, and rarely updated or removed. For example, the timestamps for each measurement change very little over time, which results in redundant data being stored.
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Look at this sequence of Unix timestamps:
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title = "What is Grafana?"
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description = "Overview of Grafana and features"
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keywords = ["grafana", "intro", "guide", "started"]
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type = "docs"
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[menu.docs]
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aliases = ["/docs/grafana/latest/guides/what-is-grafana"]
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name = "What is Grafana?"
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identifier = "what_is_grafana"
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parent = "guides"
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weight = 200
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@ -17,7 +12,7 @@ This topic provides a high-level look at Grafana, the Grafana process, and Grafa
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Grafana is open source visualization and analytics software. It allows you to query, visualize, alert on, and explore your metrics no matter where they are stored. In plain English, it provides you with tools to turn your time-series database (TSDB) data into beautiful graphs and visualizations.
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After creating a dashboard like you do in [Getting started]({{< relref "getting-started.md" >}}), there are many possible things you might do next. It all depends on your needs and your use case.
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After creating a dashboard like you do in [Getting started]({{< relref "getting-started.md" >}}), there are many possible things you might do next. It all depends on your needs and your use case.
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For example, if you want to view weather data and statistics about your smart home, then you might create a playlist. If you are the administrator for a corporation and are managing Grafana for multiple teams, then you might need to set up provisioning and authentication.
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@ -25,13 +20,13 @@ The following sections provide an overview of things you might want to do with y
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## Explore metrics and logs
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Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side by side.
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Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side by side.
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Refer to [Explore]({{< relref "../explore/index.md" >}}) for more information.
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## Alerts
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If you're using Grafana alerting, then you can have alerts sent through a number of different [alert notifiers]({{< relref "../alerting/notifications.md" >}}), including PagerDuty, SMS, email, VictorOps, OpsGenie, or Slack.
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If you're using Grafana alerting, then you can have alerts sent through a number of different [alert notifiers]({{< relref "../alerting/notifications.md" >}}), including PagerDuty, SMS, email, VictorOps, OpsGenie, or Slack.
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Alert hooks allow you to create different notifiers with a bit of code if you prefer some other channels of communication. Visually define [alert rules]({{< relref "../alerting/alerts-overview.md" >}}) for your most important metrics.
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## Dashboard variables
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[Template variables]({{< relref "../variables/_index.md" >}}) allow you to create dashboards that can be reused for lots of different use cases. Values aren't hard-coded with these templates, so for instance, if you have a production server and a test server, you can use the same dashboard for both.
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[Template variables]({{< relref "../variables/_index.md" >}}) allow you to create dashboards that can be reused for lots of different use cases. Values aren't hard-coded with these templates, so for instance, if you have a production server and a test server, you can use the same dashboard for both.
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Templating allows you to drill down into your data, say, from all data to North America data, down to Texas data, and beyond. You can also share these dashboards across teams within your organization—or if you create a great dashboard template for a popular data source, you can contribute it to the whole community to customize and use.
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@ -69,7 +64,7 @@ Refer to [Grafana Enterprise]({{< relref "../enterprise/_index.md" >}}) for more
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## Provisioning
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While it's easy to click, drag, and drop to create a single dashboard, power users in need of many dashboards will want to automate the setup with a script. You can script anything in Grafana.
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While it's easy to click, drag, and drop to create a single dashboard, power users in need of many dashboards will want to automate the setup with a script. You can script anything in Grafana.
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For example, if you're spinning up a new Kubernetes cluster, you can also spin up a Grafana automatically with a script that would have the right server, IP address, and data sources preset and locked in so users cannot change them. It's also a way of getting control over a lot of dashboards.
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