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-rw-r--r--posts/prometheus_in_early_2016.mdwn17
1 files changed, 8 insertions, 9 deletions
diff --git a/posts/prometheus_in_early_2016.mdwn b/posts/prometheus_in_early_2016.mdwn
index 36aa184..43dab7c 100644
--- a/posts/prometheus_in_early_2016.mdwn
+++ b/posts/prometheus_in_early_2016.mdwn
@@ -56,9 +56,8 @@ responses), you just run:
sum(rate(haproxy_log_requests_total[1m])) by (status_code)
-[[!img request_rate_by_status_code.png
- caption="Per second request rates, split by status code (key shown at the bottom)"
-]]
+[[!img request_rate_by_status_code.png ]]
+Per second request rates, split by status code (key shown at the bottom).
Perhaps you want to compare the performance of two servers for the different
request paths, you would run:
@@ -69,9 +68,9 @@ request paths, you would run:
http_request_path, server_name
)
-[[!img request_rate_by_request_path.png
- caption="Each metric represents the request rate for a single request path (e.g. /foo) for a single server"
-]]
+[[!img request_rate_by_request_path.png ]]
+Each metric represents the request rate for a single request path (e.g. /foo)
+for a single server.
And everything you can do with a simple counter, you can also do with
histograms for response duration. So say you want to know how a particular
@@ -86,9 +85,9 @@ request path is being handled over a set of servers, you can run:
)
)
-[[!img response_processing_duration_by_server_and_request_path.png
- caption="Each metric represents the 95 percentile request rate for a single request path, for a single server"
-]]
+[[!img response_processing_duration_by_server_and_request_path.png ]]
+Each metric represents the 95 percentile request rate for a single request
+path, for a single server.
This last query is aggregating the culamative histograms exported for each set
of label values, allowing very flexible views on the response processing