The theory

To store measurements for a longer time, it must be stored with a Retention Policy of desired length. It doesn’t make sense to store ALL data for the specified time: When Grafana shows values from a month in a graph, it physically cannot display data at 50 millisecond accuracy. Having a lot of data at very short intervals takes a lot of processing, bandwidth and disk space. So you must think about downsampling the data as well.

Downsampling and retaining data is done with two tools:

• Continuous Query (CQ) - an automatically, periodically run query which collects and downsamples data

• Retention Policy (RP) - Definition of how long the data is kept

InfluxDB 1.8 documentation

• Downsample and retain data

• Continuous queries

• Retention policies

Using already existing data

The ID service may have already added Continuous Queries and Retention Policies that meet your needs. Check the existing queries with the influx prompt:

Above we see from the first result that there exists a query called openid_api_requests_hourly which collects a field called count which is a sum of auth_header_exists values (e.g. a count of requests), grouped with 1 hour accuracy for each path and method combination. It is available in the one_year retention policy with name openid_api_requests_hourly.

This existing continuous query data can be used in Grafana with the following configuration:

Open

Creating a new RP and CQ

Let’s suppose there isn’t a CQ and RP that meet our requirements.

Requirements

We need to have a Grafana display which shows Management API request counts by path, and we need to show data for the last 30 days. We need to be able to display data for quite a short interval, so let’s pick an interval of 5 minutes.

In summary:

• We need to store metrics data about Management API requests

• For 30 days

• With 5 minute interval accuracy

• This means we will have 30 * 24 * (60/5) = 8640 measurements per any stored tag combination. This is a reasonable amount of data to process.

What we already have

We can show a graph for the last 24 hours with the following Grafana Panel configuration:

Open

The essential info we see from this configuration is:

• Data is stored with the default retention policy (which we know is one_day by using the show retention policies command) with measurement name mgmg_api_request.

• There’s a field or tag called auth_header_exists, and in this graph we display the number of them by using the count() function.

• We group by time and also the tag path.

• The path tag is also used as an alias, the value of which is shown in the legend.

Create a Retention Policy

We need a retention policy that is at least 30 days long. Let’s see what is available:

We see that one_day is indeed the default, and the next longest is one_year. Since that is too long, we should create a new RP called one_month that has a duration of 30 days, or 720 hours.

Now we can confirm that it was added.

Create a Continuous Query

Let’s create a CQ that collects everything usable from default mgmt_api_request data. We can find the tag and field names with commands like SELECT * FROM mgmt_api_request LIMIT 1.

CREATE CONTINUOUS QUERY "mgmt_api_requests_5min_for_1month" ON "oneportal" BEGIN SELECT count(auth_header_exists) AS "count_requests", sum("request_duration") AS "sum_request_duration", mean("request_duration") AS "mean_request_duration" INTO "one_month"."mgmt_api_requests" FROM "mgmt_api_request" GROUP BY time(5m), "path", "method", "api_client_id", "oauth2_client_id" END

We could have created a CQ that collects only the number of requests and groups them by path, but in anticipation of other needs, we collect more data and more tags.

Note:

• The data will be stored with RP one_month and name mgmt_api_requests

• It will have the following values:

  • count_requests: The number of requests made during 5 minutes. This is needed in our example.

  • sum_request_duration: A sum of the duration of request processing during 5 minutes. This can be used to display which requests are slowest to process and might be the causes of performance problems.

  • mean_request_duration: The mean duration of request processing during 5 minutes. This can be used to display how long requests take on average.

  • Tags path, method, api_client_id and oauth2_client_id. Of these path is needed for our example, others can be used in other graphs.

• The fields response_code, request_uri apparently cannot be used for grouping in a CQ, so they are not included.

Test the Continuous Query

Make a few Management API calls to add data.

Wait 5 minutes for the CQ to run. Then run the query:

We see that 6 such requests were made, with an average processing time of 1.83 ms.

Update the Grafana panel

Make a duplicate of the original panel as a backup. Update the panel query configuration:

• In FROM use the one_month RP and the mgmt_api_requests name,

• change the SELECT parameters to use field count_requests and the function to sum() since we now need to add the counts up.

Open

The equivalent query is: SELECT sum("count_requests") FROM "one_month"."mgmt_api_requests" WHERE $timeFilter GROUP BY time($__interval), "path" fill(0).

The graph now shows the expected correct values. You should change the Min interval to 5m to match the CQ, and to visualise that the data covers a 5 minute period.

Open

More CQ examples

Number of Management API requests that ended if error code (>= 400):

CREATE CONTINUOUS QUERY mgmt_api_request_errors_5min_for_1month ON oneportal BEGIN SELECT count(auth_header_exists) AS count_requests INTO oneportal.one_month.mgmt_api_request_errors FROM oneportal.one_day.mgmt_api_request WHERE response_code >= 400 GROUP BY time(5m), api_client_id, oauth2_client_id, path END

Number of Management API requests that ended in successful code (200 to 399):

CREATE CONTINUOUS QUERY mgmt_api_request_successes_5min_for_1month ON oneportal BEGIN SELECT count(auth_header_exists) AS count_requests INTO oneportal.one_month.mgmt_api_request_successes FROM oneportal.one_day.mgmt_api_request WHERE response_code >= 200 AND response_code < 400 GROUP BY time(5m), api_client_id, oauth2_client_id, path END

Number of OpenID API requests, similar to number of Management API requests in the above example:

CREATE CONTINUOUS QUERY "openid_api_requests_5min_for_1month" ON "oneportal" BEGIN SELECT count(auth_header_exists) AS "count_requests" INTO "one_month"."openid_api_requests" FROM "openid_api_request" GROUP BY time(5m), "path", "method" END

Number of log entries:

CREATE CONTINUOUS QUERY "log_entries_5min_for_1month" ON "oneportal" BEGIN SELECT count("event_id") AS "count_entries" INTO "one_month"."log_entries" FROM "log_entry" GROUP BY time(5m), "source" END