Correct a couple of "timeseries" -> "time series".

content/docs/concepts/data_model.md

@@ -8,7 +8,7 @@ sort_rank: 1
 Prometheus fundamentally stores all data as [_time
 series_](http://en.wikipedia.org/wiki/Time_series): streams of timestamped
 values belonging to the same metric and the same set of labeled dimensions.
-Besides stored timeseries, Prometheus may generate temporary derived timeseries
+Besides stored time series, Prometheus may generate temporary derived time series
 as the result of queries.
 
 ## Metric names and labels

content/docs/introduction/comparison.md

@@ -55,13 +55,13 @@ api_server_http_requests_total{method="POST","handler="/tracks",status="500",ins
 Graphite stores time series data on local disk in the
 [Whisper](http://graphite.readthedocs.org/en/latest/whisper.html) format, an
 RRD-style database that expects samples to arrive at regular intervals. Every
-timeseries is stored in a separate file, and new samples overwrite old ones
+time series is stored in a separate file, and new samples overwrite old ones
 after a certain amount of time.
 
 Prometheus also creates one local file per time series, but allows storing
 samples at arbitrary intervals as scrapes or rule evaluations occur. Since new
 samples are simply appended, old data may be kept arbitrarily long. Prometheus
-also works well for many short-lived, frequently changing sets of timeseries.
+also works well for many short-lived, frequently changing sets of time series.
 
 ## Prometheus vs. InfluxDB
 

content/docs/introduction/overview.md

@@ -51,7 +51,7 @@ its ecosystem components:
 
 Prometheus scrapes metrics from instrumented jobs, either directly or via an
 intermediary push gateway for short-lived jobs. It stores all scraped samples
-locally and runs rules over this data to either record new timeseries from
+locally and runs rules over this data to either record new time series from
 existing data or generate alerts. PromDash or other API consumers can be used
 to visualize the collected data.
 

content/docs/operating/storage.md

@@ -5,7 +5,7 @@ nav_icon: database
 
 # Storage
 
-Prometheus stores its timeseries data under the directory specified by the flag
+Prometheus stores its time series data under the directory specified by the flag
 `storage.local.path`. If you suspect problems caused by corruption in the
 database, or you simply want to erase the existing database, you can easily
 start fresh by deleting the contents of this directory:

content/docs/practices/instrumentation.md

@@ -174,7 +174,7 @@ See also the [naming](../naming) section.
 
 ### Do not overuse labels
 
-Each labelset is an additional timeseries that has RAM, CPU, disk, and network
+Each labelset is an additional time series that has RAM, CPU, disk, and network
 costs. Usually the overhead is negligible, but in scenarios with lots of
 metrics and hundreds of labelsets across hundreds of servers, this can add up
 quickly.

content/docs/querying/rules.md

@@ -45,7 +45,7 @@ file:
 
 Some examples:
 
-    // Saving the per-job HTTP in-progress request count as a new set of timeseries:
+    // Saving the per-job HTTP in-progress request count as a new set of time series:
     job:http_inprogress_requests:sum = sum(http_inprogress_requests) by (job)
 
     // Drop or rewrite labels in the result time series:

content/docs/visualization/promdash.md

@@ -155,9 +155,9 @@ as the global setting remains unchanged.
 The legend settings menu tab allows you to configure when to show the legend on
 a graph, as well as defining how it should be formatted.
 
-By default, each timeseries will be displayed with their full name (metric name
-plus all label names and values) in the legend. If you have many timeseries or
-timeseries with many labels, this can quickly lead to unusably long legends.
+By default, each time series will be displayed with their full name (metric name
+plus all label names and values) in the legend. If you have many time series or
+time series with many labels, this can quickly lead to unusably long legends.
 
 The `Legend format` builder allows you to create a list of format strings which
 you can then assign to expressions in the `Datasources` tab. Each format string