I have Graphite running on a Docker container and I've fed 24 hours worth of data sampled at 20 minute intervals to nine metrics – far from being a large payload. If I graph each metric in the Graphite web app, the last six hours of data are invisible. If I pull the raw data from the render API, these data points are indeed null (timestamps with no value).
However, if I narrow the time range down to the last six hours, the graphs display all the data I would expect. Weirder still, if I try to view this data using Grafana, the same thing happens: the last six hours are not shown unless I shrink the time range.
Is there any way to fix this so that recent data points are visible while viewing more than 6 hours of data?
I would start by looking at the storage-schemas.conf and storage-aggregation.conf files.
Do you have a different retention after the 6 hour?
We had a similar issue with data disappearing after the first 24h where we had high resolution. We had to tune how data is aggregated to the "next level".
Or maybe it is just the data is not yet written to disk - and only exists in the carbon-cache at the moment.
Related
To get some "visual alerting", I'd like to draw simultaneously two curves on the same graph in Grafana:
current time-window graph
same graph but with 7 days ago data
The idea is to be able to compare data evolution on the same day in the previous week.
I could not find a Graphite function for that (but I may have missed something in the doc).
Is there a way to do it?
You can use timeShift to make a metric in grafana with your series shifted back a week.
This kind of thing is also a good application for series-specific display overrides in grafana, so you can make the shifted series display differently from the current data.
The goal flow report on my google analytics account shows some strange sampling behavior. While I can usually select up to a month of data before sampling starts it seems to be different for the goal flow report.
As soon as I select more than one day of data the used data set is getting smaller very fast. At three days the report ist based on only 50% of the sessions, which, according to analytics, comes to only 35 sessions.
Has anyone experienced a similar behavior of sampling although only very small data-sets are used?
Sampling is induced when your request is calculation-intensive; there's no 'garunteed point at which it trips.
Goal flow complexity will increase exponentially as you add goals, so even a low number of goals might make this report demand a lot of processing.
Meanwhile you'll find that moast of the standard reports can cover large periods of time without sampling; they are preaggreated, so it's very cheap to load them.
If you want to know more about sampling, see here:
https://stackoverflow.com/a/37386181/5815149
Is there a way to simply show the change of a value over the selected time period? All I'm interested in is the offset of the last value compared to the initial one. The values can vary above and below these over the time period, it's not really relevant (and would be exceptions in my case).
For an initial value of 100 and an final value of 105, I'd expect a single stat box displaying 5%.
I have the feeling I'm missing something obvious obvious, but can't find a method to display this deceptively simple task.
Edit:
I'm trying to create a scripted Grafana dashboard that will automatically populate disk consumption growth for all our various volumes. The data is already in Graphite, but for purposes of capacity management and finance planning (which projects/departments gets billed) it would be helpful for managers to have a simple and coarse overview of which volumes grow outside expected parameters.
The idea was to create a list of single-stat values with color coding that could easily be scrolled through to find abnormalities. Disk usage would obviously never be negative, but volatility in usage between the start and end of the time period would be lost in this view. That's not a big concern for us as this is all shared storage and such usage is expected to a certain degree.
The perfect solution would be to have the calculations change dynamically based on the selected time period.
I'm thinking that this is not really possible (at least not easily) to do with just Graphite and Grafana and have started looking for alternative methods. We might have to implement a different reporting system for this purpose.
Edit 2
I've tried implementing the suggested solution from Leonid, and it works after a fashion. The calculations seems somewhat off from what I expected though.
My test dashboard looks like follows:
If I were to calculate the change manually, I'd end up with roughly 24% change between the start (7,23) and end (8.96) value. Graphite calculates this to 19%. It's probably a reason for the discrepancy, probably something to do with it being a time-series and not discreet values?
As a sidenote: The example is only 30 days, even though the most interesting number would be a year. We don't have quite a year of data in Graphite yet and having a 30 day view is also interesting. It seems I have to implement several dashboards with static times.
You certainly can do that for some fixed period. For example following query take absolute difference betweent current metric value and value that metric has one minute ago (i.e. initial value) and then calculate it's percentage of inital value.
asPercent(absolute(diffSeries(my_metric, timeShift(my_metric, '1m'))), timeShift(my_metric, '1m'))
I believe you can't do that for time period selected in Grafana picker.
But is that really what you need? It's seems strange because as you said value can change in both directions. Maybe standard deviation would be more suitable for you? It's available in Graphite as stdev function.
I have been a happy user of Graphite+Grafana for a few months now and I have been advocating it around my firm.
My approach has been to measure data of interest and collect them into 1-minute or 5-minute buckets and send that information to Graphite. I was recently contacted by a group that processes quotes (billions a day!) and their approach has been to create a log line each time their applications process 1 million quotes. The problem is that the interval between 2 log lines can be highly erratic from 1 second to a few hours.
The dilemma is then: should I set my retention policy to a 1-second bucket so that I can see all measurements associated with spikes or should I use say a 1-minute bucket so that the number of data points to be saved and later on queried is much more manageable. FYI, when I set it to 1-second, showing the data for 8 or 10 charts, for a few days was bringing the system (or at least my browser) to a crawl because of the numbers of data points (mostly NULL) being pushed around from Graphite to Grafana
Here's my retention policy: 1s:10d,1m:36d,5m:180d
Alternatively, is there a way to configure Grafana+Graphite to only retrieve non-NULL data points?
What do you recommend?
You can always specify a lower retention period for 1s metrics so when you show a longer range Graphite will send you only the more coarse level.
For example, you can specify: 1s:2d, 1m:7d, 5m:180d
This way, if you show a range more than 2 days in the past you will get 1m resolution (and so on), which won't make your browser crawl, while you will still be able to inspect spikes in the last 2 days.
I have an application that publishes a number of stats to graphite via statsd. One of the stats simply sends a stat increment to statsd every time a message is received by the service. I need to display a graph that shows the the relative traffic over time for this stat. Generally speaking, I should be able to display a graph that refreshes every, say 10 seconds, and displays how many messages were recived in those 10 seconds as well as the history for a given period of time. However, no matter how I format my API query I cannot seem to get accurate data. I've read a number of articles including this one:
http://code.hootsuite.com/accurate-counting-with-graphite-and-statsd/
That seems to give some good insight but is still not quite giving me what I need. this is the closes I have come:
integral(hitcount(stats.recieved, "10seconds"))
However, I don't like the cumulative result of this and when I run this I get statistics that come nowhere near to what I see n my logs for messages received. I am ok with accepting some packet loss but we talking about orders of magnitude. I know I am doing something wrong. Just hoping someone can give me some insight as to what.
A couple of things to check/try:
Configure Graphite for Statsd
Check to make sure that you've used the retention schema and aggregation settings in Graphite that match how Statsd will be sending data (i.e. it sends one data point per 10 second flush interval).
Run a single Statsd aggregator
Be sure you are only running one instance of Statsd as running multiple statsd daemons will cause metrics to be dropped (as Graphite will be configured to only store one data point for it's highest precision of 10s:6h)
Limit the time range in the UI or URL API to less than 6 hours
When displaying graphs with data that crosses over the 6 hour threshold (e.g. from now to 7 hours ago), you will begin seeing 1 minute worth of aggregated count data for the displayed graph (if you've configured Graphite for statsd with retentions = 10s:6h,1min:7d,10min:5y). Rollups will occur based on the oldest data point in the time range (e.g. now till 7+ days = you'll get 10 min rollups).
If sending sparse or "bursty" data AND displaying old time range (triggering aggregation)
Confirm that your xFilesFactor is low enough that aggregation produces non null values even with a high rate of nulls. For example, 100 requests in the first 10 seconds, and none for the remaining 50 seconds in a minute would cause a storage of 100, null, null, null, null, null which would be summed up to null when the data ages if the XFilesFactor is higher than 1/6. Using the statsd recommended graphite configuration handles this, but it is good to know about... as this can give the appearance of lost data.
Saving schema or aggregation changes
If you changed the graphite schema or aggregation settings after any metrics were stored (in whisper = graphite's storage) you'll need to either delete the .wsp files for the metric (graphite will recreate them) or run whisper-resize.py.
Validating settings
You can verify the settings against some whisper data by running whisper-info.py on a .wsp file. Find the .wsp file for one of your metrics in /graphite/storage/whisper/
Run: whisper-info.py my_metric_data.wsp. whisper-info.py output should tell you more about how the storage settings are working.
TLDR;
You should ensure that Graphite is set to store one data point per 10 second interval for metrics coming from StatsD. You should make sure that Graphite is summing (not averaging) for count data coming from Statsd. Both of these can be handled by using the recommended Statsd configuration settings. Don't run more than one Statsd aggregator. When using the UI, limit the data returned to less than 6 hours OR understand what rollup you are viewing when looking at data that crosses retention thresholds. Lastly, make sure the settings take (if you've already been sending metrics).