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-rw-r--r--backends/WALKTHROUGH.md6
1 files changed, 3 insertions, 3 deletions
diff --git a/backends/WALKTHROUGH.md b/backends/WALKTHROUGH.md
index 0c330ee1a..d3666ef5d 100644
--- a/backends/WALKTHROUGH.md
+++ b/backends/WALKTHROUGH.md
@@ -209,7 +209,7 @@ Prometheus. In order to do this let’s keep our metrics page open for reference
http://localhost:19999/api/v1/allmetrics?format=prometheus&help=yes We are
setting out to graph the data in the CPU chart so let’s search for “system.cpu”
in the metrics page above. We come across a section of metrics with the first
-comments `# COMMENT homogeneus chart "system.cpu", context "system.cpu", family
+comments `# COMMENT homogeneous chart "system.cpu", context "system.cpu", family
"cpu", units "percentage"` Followed by the metrics. This is a good start now let
us drill down to the specific metric we would like to graph.
@@ -251,9 +251,9 @@ http://localhost:19999/api/v1/allmetrics?format=prometheus&help=yes&types=yes&so
If you choose to use this method you will need to use Prometheus's set of
functions here: https://prometheus.io/docs/querying/functions/ to obtain useful
metrics as you are now dealing with raw counters from the system. For example
-you will have to use the `irate()` function over a counter to get that metric’s
+you will have to use the `irate()` function over a counter to get that metric's
rate per second. If your graphing needs are met by using the metrics returned by
-NetData’s internal database (not specifying any source= url parameter) then use
+NetData's internal database (not specifying any source= url parameter) then use
that. If you find limitations then consider re-writing your queries using the
raw data and using Prometheus functions to get the desired chart.