I want to answer the question: what time window my servers are least used?
My idea is to have a 24h histogram (with 10min buckets) with the count of requests made to my server. In other words, I want to ignore date portion in datetime aggregations.
How do I create such graph in Kibana 4?
Related
I have a SpringBoot application that is under moderate load. I want to collect metric data for a few of the operations of my app. I am majorly interested in Counters and Timers.
I want to count the number of times a method was invoked (# of invocation over a window, for example, #invocation over last 1 day, 1 week, or 1 month)
If the method produces any unexpected result increase failure count and publish a few tags with that metric
I want to time a couple of expensive methods, i.e. I want to see how much time did that method took, and also I want to publish a few tags with metrics to get more context
I have tried StatsD-SignalFx and Micrometer-InfluxDB, but both these solutions have some issues I could not solve
StatsD aggregates the data over flush window and due to aggregation metric tags get messed up. For example, if I send 10 events in a flush window with different tag values, and the StatsD agent aggregates those events and publishes only one event with counter = 10, then I am not sure what tag values it's sending with aggregated data
Micrometer-InfluxDB setup has its own problems, one of them being micrometer sending 0 values for counters if no new metric is produced and in that fake ( 0 value counter) it uses same tag values from last valid (non zero counter)
I am not sure how, but Micrometer also does some sort of aggregation at the client-side in MeterRegistry I believe, because I was getting a few counters with a value of 0.5 in InfluxDB
Next, I am planning to explore Micrometer/StatsD + Telegraf + Influx + Grafana to see if it suits my use case.
Questions:
How to avoid metric aggregation till it reaches the data store (InfluxDB). I can do the required aggregation in Grafana
Is there any standard solution to the problem that I am trying to solve?
Any other suggestion or direction for my use case?
Heading ##CALL ga.timetree.single({time: 1463659567468, create: true})
https://github.com/graphaware/neo4j-timetree
https://graphaware.com/neo4j/2014/08/20/graphaware-neo4j-timetree.html
The above link says that time is in long format YYYYMMDDHHmmss. But the time parameter doesn't make any sense and random nodes are getting generated in neo4j. enter image description here
What does the time parameter hold and what is the meaning of it?
The time parameter is a millisecond timestamp, or milliseconds elapsed since the UNIX epoch, which is an extremely common means of storing time-related data, you can find this in use in nearly every digital system.
The timestamp cited here represents "2016-05-19 12:06:07". The timetree built starts from a root (this is a modeling convenience), and then its child is the year (2016) followed by the month (5), then the date of the month (19). Looks like it didn't automatically create any nodes for time resolutions beyond that.
Keep in mind that now that Neo4j has native temporal values that you can use in Cypher and store as properties (as well as index), time trees are going to be less useful, as you can always do index lookups on indexed temporal properties.
There are still some cases where time trees can still be very useful, however, such as when you're searching for events that happened within some unit of time that disregards its parent units...such as finding events that happened on Mondays regardless of month, or on Januaries regardless of year, and so forth.
Is it possible to write a InfluxDB query that will give me the number of milliseconds since the last entry in a time series? I'd like to add a single-stat panel in Grafana displaying how old the data is.
I don't think it is possible since you are not able to query the time alone. A influxdb query needs at least one non-time field in a query. You could workaround that by double saving the time in a extra field which you are able to query alone.
But you still want to use now() - "the extra time field". But as far as I found out you also can't use now() inside grafana.
Update: there is a [Feature-Request] now on grafanas github. Make sure to vote it up so it gets implemented one day: https://github.com/grafana/grafana/issues/6710
Update 2: The feature got finaly implemented -> See my answer here: How to show "33 minutes ago" on Grafana dashboard with InfluxDB?
I'm sending metrics in StatsD format to Telegraf, which forwards them to InfluxDB 0.9.
I'm measuring execution times (of some event) from multiple hosts. The measurement is called "execTime", and the tag is "host". Once Telegraf gets these numbers, it calculates mean/upper/lower/count, and stores them in separate measurements.
Sample data looks like this in influxdb:
TIME...FIELD..............HOST..........VALUE
t1.....execTime.count.....VM1...........3
t1.....execTime.mean......VM1...........15
t1.....execTime.count.....VM2...........6
t1.....execTime.mean......VM2...........22
(So at time t1, there were 3 events on VM1, with mean execution time 15ms, and on VM2 there were 6 events, and the mean execution time was 22ms)
Now I want to calculate the mean of the operation execution time across both hosts at time t1. Which is (3*15 + 6*22)/(3+6) ms.
But since the count and mean values are in two different series, I can't simply use "select mean(value) from execTime.mean"
Do I need to change my schema, or can I do this with the current setup?
What I need is essentially a new series, which is a combination of the execTime.count and execTime.mean across all hosts. Instead of calculating this on-the-fly, the best approach seems to be to actually create the series along with the others.
So now I have two timer stats being generated on each host for each event:
1. one event with actual hostname for the 'host' tag
2. second event with one tag "host=all"
I can use the first set of series to check mean execution times per host. And the second series gives me the mean time for all hosts combined.
It is possible to do mathematical operations on fields from two different series, provided both series are members of the same measurement. I suspect your schema is non-optimized for your use case.
How we can identify the differnece between two nodes in Neo4j from time to time.In other words i have two graph images and my task is to identify the delta between these two..
Any suggestions?
Here i will have access to a neo4j DB which will be updating by an application to whcih i dont have accesss.And my job is to identify the changes done to DB with in a time interval like for 4 hours once etc..here nodes doesn't have any time stamps. Previously i reffered as two images since my requirement is to identify the changes happened to the same DB with in some time gap.ex 1 pm( one graph intance) to 4 pm(second graph instance) with 4 hours time interval..
Hope my query is clear..
Thanks..