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| Deployment | ||
| ---------- | ||
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| ### Deploy on Ubuntu | ||
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| upstart script etc | ||
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| ### Deploy on EC2 | ||
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| ready made ami |
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| Examples | ||
| -------- | ||
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| here be dragons |
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| HTTP API | ||
| -------- | ||
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| FIXPAUL: blah blah | ||
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| ### GET /metric/:key | ||
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| Retrieves a metric's value(s) at a specified point in time or in a specified time interval | ||
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| Parameters: | ||
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| <table> | ||
| <tr> | ||
| <th>key <i>(mandatory)</i></th> | ||
| <td> | ||
| key of this metric (e.g. my-counter-sum-15) | ||
| </td> | ||
| </tr> | ||
| <tr> | ||
| <th>since / until</th> | ||
| <td> | ||
| when the since and until parameters are set, all values in the supplied time | ||
| interval are returned. values can be a timestamp or a timespec like... since/until | ||
| are mutually exclusive with at | ||
| </td> | ||
| </tr> | ||
| <tr> | ||
| <th>at</th> | ||
| <td> | ||
| if set, returns a single value at this point in time. content can be a timestamp | ||
| or a timespec like -3m... mutually exclusive with since/until | ||
| </td> | ||
| </tr> | ||
| <tr> | ||
| <th>format</th> | ||
| <td> | ||
| response format csv, json or xml (also use HTTP-Accept) | ||
| </td> | ||
| </tr> | ||
| </table> | ||
| <br /> | ||
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| Examples: | ||
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| >> GET /metric/total_sales_in_euro-sum-30?at=-5m&format=json | ||
| << HTTP/1.1 200 OK | ||
| << ... | ||
| << { "value": 23426 } | ||
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| >> GET /metric/total_sales_in_euro-sum-30?since=-2min&until=now&format=json | ||
| << HTTP/1.1 200 OK | ||
| << ... | ||
| << { "values": { 1360804571: 4233, 1360804581: 4636, 1360804591: 3621, ... } } | ||
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| ### POST /metric/:key | ||
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| Sample/add a value to a metric. | ||
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| Parameters: | ||
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| <table> | ||
| <tr> | ||
| <th>key <i>(mandatory)</i></th> | ||
| <td> | ||
| key of this metric (e.g. my-counter-sum-15) | ||
| </td> | ||
| </tr> | ||
| <tr> | ||
| <th>value <i>(mandatory)</i></th> | ||
| <td> | ||
| the value to add/sample to this metric | ||
| </td> | ||
| </tr> | ||
| </table> | ||
| <br /> | ||
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| Examples: | ||
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| >> POST /metric/total_sales_in_euro-sum-30?value=351 | ||
| << HTTP/1.1 201 CREATED | ||
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| FnordMetric Enterprise | ||
| ---------------------- | ||
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| FnordMetric Enterprise is a JVM-based timeseries database. It's a key-value store | ||
| (much like redis or memcached) where each key holds a "measurement". There are | ||
| different measurement methods like sum, mean, min/max, 90th percentile, etc. You | ||
| continuously add data to these keys/measurements which is aggregated and periodically | ||
| persisted. | ||
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| FnordMetric Enterprise features disk persistence, a HTTP, TCP and UDP API, native | ||
| WebSockets support, CSV/JSON Export and a turnkey-ready HTML5 visualization solution | ||
| (FnordMetric UI). FnordMetric Enterprise can be used as a drop-in replacement for | ||
| StatsD+Graphite (it is a lot faster, see Benchmarks). | ||
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| ### Semantics | ||
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| There are three basic operations: `add_sample`, `value_at` and `values_in` that | ||
| add a sample to an ongoing measurement, retrieve the measurement value at a | ||
| specified time, or retrieve all aggregated measurement values in a specified time | ||
| interval. | ||
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| The measurement method and flush_interval are implicitly specified by the key; | ||
| all keys have to be postfixed with "$method-$flush_timeout". For example if | ||
| you want a key "response_time" to operate in average/mean mode and flush every 60 | ||
| seconds, use the key `response_time-mean-60`, for a key "total_clicks" that | ||
| aggregates/sums a value and flushes every hour, you could use "total_clicks.sum-3600" | ||
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| ### In-memory vs. disk storage | ||
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| FnordMetric Enterprise stores the values as 64bit double precision floats. | ||
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| With an example flush timeout of 10 seconds, one metric uses 0.065 MB of | ||
| memory per day or 0.4 MB per week. The default ring buffer size is x,. | ||
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| That means with only 4GB of ram, you could access the last month of data of | ||
| 2500 counters/measurements with 10 second granularity all from the in-memory | ||
| ringbuffers (without ever hitting a HDD). | ||
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| Requests that can not be served from memory require one sequential disk read. | ||
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| ### FnordMetric Enterprise vs. StatsD | ||
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| + allows for flush intervals as low as one second | ||
| + rendered in the browser, interactive | ||
| + much much more scalable | ||
| + highly customizable with css | ||
| + requires only a single deployment | ||
| + i18n (proper timezones in graphs due to in browser rendering etc) |
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