core-telemetry-0.1.6.0: lib/Core/Telemetry/Observability.hs
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE GeneralisedNewtypeDeriving #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE QuasiQuotes #-}
{-# LANGUAGE RankNTypes #-}
{- |
To use this capability, first you need to initialize the telemetry subsystem
with an appropriate exporter.
@
import "Core.Program"
import "Core.Telemetry"
main :: 'IO' ()
main = do
context <- 'Core.Program.Execute.configure' \"1.0\" 'Core.Program.Execute.None' ('simpleConfig' [])
context' <- 'initializeTelemetry' ['Core.Telemetry.Console.consoleExporter', 'Core.Telemetry.Console.structuredExporter', 'Core.Telemetry.Console.honeycombExporter'] context
'Core.Program.Execute.executeWith' context' program
@
/Traces and Spans/
For spans to be connected together by an observability tool they need to be
part of a /trace/.
At the top of your program or request loop you need to start a new trace (with
'beginTrace') or continue one inherited from another service (with
'usingTrace'):
@
program :: 'Core.Program.Execute.Program' 'Core.Program.Execute.None' ()
program = do
'beginTrace' $ do
'encloseSpan' \"Service Request\" $ do
-- do stuff!
...
-- add appropriate telemetry values to the span
'telemetry'
[ 'metric' \"colour\" currentSkyObservation
, 'metric' \"temperature" currentAirTemperature
]
@
will result in @colour=\"Blue\"@ and @temperature=26.1@ or whatever being sent
by the telemetry system to the observability service that's been activated.
The real magic here is that spans /nest/. As you go into each subcomponent on
your request path you can again call 'encloseSpan' creating a new span. Any
metrics added before entering the new span will be inherited by the subspan
and sent when it finishes so you don't have to keep re-attaching data if it's
common across all the spans in your trace.
/Events/
In other circumstances you will just want to send metrics:
@
-- not again!
'sendEvent' \"Cat meowed\"
[ 'metric' \"room\" (\"living room\" :: 'Rope')
, 'metric' "volume\" (127.44 :: 'Float') -- decibels
, 'metric' \"apparently_hungry\" 'True'
]
@
will result in @room=\"living room\"@, @volume=127.44@, and
@apparently_hungry=true@ being sent as you'd expect. Ordinarily when you call
'metric' you are passing in a variable that already has a type, but when
hardcoding literals like in this example (less common but not unheard of)
you'll need to add a type annotation.
You /do not/ have to call 'sendEvent' from within a span, but if you do
appropriate metadata will be added to help the observability system link the
event to the context of the span it occured during.
Either way, explicitly sending an event, or upon exiting a span, the telemetry
will be gathered up and sent via the chosen exporter and forwarded to the
observability or monitoring service you have chosen.
-}
module Core.Telemetry.Observability (
-- * Initializing
Exporter,
initializeTelemetry,
-- * Traces
Trace (..),
Span (..),
beginTrace,
usingTrace,
setServiceName,
-- * Spans
Label,
encloseSpan,
setStartTime,
-- * Creating telemetry
MetricValue,
Telemetry (metric),
telemetry,
-- * Events
sendEvent,
) where
import Control.Concurrent.MVar (modifyMVar_, newMVar, readMVar)
import Control.Concurrent.STM (atomically)
import Control.Concurrent.STM.TQueue (writeTQueue)
import Core.Data.Structures (Map, insertKeyValue)
import Core.Encoding.Json
import Core.Program.Arguments
import Core.Program.Context
import Core.Program.Logging
import Core.System.Base (liftIO)
import Core.System.External (TimeStamp (unTimeStamp), getCurrentTimeNanoseconds)
import Core.Text.Rope
import Core.Text.Utilities (oxford, quote)
import qualified Data.ByteString as B (ByteString)
import qualified Data.ByteString.Lazy as L (ByteString)
import Data.Char (chr)
import Data.Int (Int32, Int64)
import qualified Data.List as List (foldl')
import Data.Scientific (Scientific)
import qualified Data.Text as T (Text)
import qualified Data.Text.Lazy as U (Text)
import System.Random (newStdGen, randomRs)
{- |
A telemetry value that can be sent over the wire. This is a wrapper around
JSON values of type string, number, or boolean. You create these using the
'metric' method provided by a 'Telemetry' instance and passing them to the
'telemetry' function in a span or 'sendEvent' if noting an event.
-}
-- a bit specific to Honeycomb's very limited data model, but what else is
-- there?
data MetricValue
= MetricValue JsonKey JsonValue
deriving (Show)
{- |
Record the name of the service that this span and its children are a part of.
A reasonable default is the name of the binary that's running, but frequently
you'll want to put something a bit more nuanced or specific to your
application. This is the overall name of the independent service, component,
or program complimenting the @label@ set when calling 'encloseSpan', which by
contrast descibes the name of the current phase, step, or even function name
within the overall scope of the \"service\".
This will end up as the @service_name@ parameter when exported.
-}
-- This field name appears to be very Honeycomb specific, but looking around
-- Open Telemmtry it was just a property floating around and regardless of
-- what it gets called it needs to get sent.
setServiceName :: Rope -> Program τ ()
setServiceName service = do
context <- getContext
let v = currentDatumFrom context
liftIO $ do
modifyMVar_
v
( \datum -> do
let datum' =
datum
{ serviceNameFrom = Just service
}
pure datum'
)
class Telemetry σ where
metric :: Rope -> σ -> MetricValue
instance Telemetry Int where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromIntegral v))
instance Telemetry Int32 where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromIntegral v))
instance Telemetry Int64 where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromIntegral v))
instance Telemetry Integer where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromInteger v))
-- HELP is this the efficient way to get to a Scientific?
instance Telemetry Float where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromRational (toRational v)))
-- HELP is this the efficient way to get to a Scientific?
instance Telemetry Double where
metric k v = MetricValue (JsonKey k) (JsonNumber (fromRational (toRational v)))
instance Telemetry Scientific where
metric k v = MetricValue (JsonKey k) (JsonNumber v)
instance Telemetry Rope where
metric k v = MetricValue (JsonKey k) (JsonString v)
instance Telemetry String where
metric k v = MetricValue (JsonKey k) (JsonString (intoRope v))
{- |
The usual warning about assuming the @ByteString@ is ASCII or UTF-8 applies
here. Don't use this to send binary mush.
-}
instance Telemetry B.ByteString where
metric k v = MetricValue (JsonKey k) (JsonString (intoRope v))
{- |
The usual warning about assuming the @ByteString@ is ASCII or UTF-8 applies
here. Don't use this to send binary mush.
-}
instance Telemetry L.ByteString where
metric k v = MetricValue (JsonKey k) (JsonString (intoRope v))
instance Telemetry T.Text where
metric k v = MetricValue (JsonKey k) (JsonString (intoRope v))
instance Telemetry U.Text where
metric k v = MetricValue (JsonKey k) (JsonString (intoRope v))
instance Telemetry Bool where
metric k v = MetricValue (JsonKey k) (JsonBool v)
instance Telemetry JsonValue where
metric k v = MetricValue (JsonKey k) v
{- |
Activate the telemetry subsystem for use within the
'Core.Program.Execute.Program' monad.
Each exporter specified here will add setup and configuration to the context,
including command-line options and environment variables needed as
approrpiate:
@
context' <- 'initializeTelemetry' ['Core.Telemetry.Console.consoleExporter'] context
@
This will allow you to then select the appropriate backend at runtime:
@
$ burger-service --telemetry=console
@
which will result in it spitting out metrics as it goes,
@
calories = 667.0
flavour = true
meal_name = "hamburger"
precise = 45.0
@
and so on.
-}
initializeTelemetry :: [Exporter] -> Context τ -> IO (Context τ)
initializeTelemetry exporters1 context =
let exporters0 = initialExportersFrom context
exporters2 = exporters0 ++ exporters1
codenames =
fmap (\name -> singletonRope '"' <> name <> singletonRope '"')
. fmap codenameFrom
$ exporters2
config0 = initialConfigFrom context
config1 =
appendOption
( Option
"telemetry"
Nothing
(Value "EXPORTER")
( [quote|
Turn on telemetry. Tracing data and metrics from events
will be forwarded via the specified exporter. Valid values
are
|]
<> oxford codenames
)
)
config0
config2 = List.foldl' f config1 exporters2
in pure
( context
{ initialConfigFrom = config2
, initialExportersFrom = exporters2
}
)
where
-- This doesn't actually setup the telemetry processor; that's done in
-- executeAction. Here we're setting up each of the exporters so they
-- show up in --help. When we process command-line arguments we'll find
-- out which exporter was activated, if any.
f :: Config -> Exporter -> Config
f config exporter =
let setup = setupConfigFrom exporter
in setup config
type Label = Rope
{- |
Begin a span.
You need to call this from within the context of a trace, which is established
either by calling `beginTrace` or `usingTrace` somewhere above this point in
the program.
You can nest spans as you make your way through your program, which means each
span has a parent (except for the first one, which is the root span) In the
context of a trace, allows an observability tool to reconstruct the sequence
of events and to display them as a nested tree correspoding to your program
flow.
The current time will be noted when entering the 'Program' this span encloses,
and its duration recorded when the sub @Program@ exits. Start time, duration,
the unique identifier of the span (generated for you), the identifier of the
parent, and the unique identifier of the overall trace will be appended as
metadata points and then sent to the telemetry channel.
-}
encloseSpan :: Label -> Program z a -> Program z a
encloseSpan label action = do
context <- getContext
unique <- liftIO randomIdentifier
debug "span" unique
liftIO $ do
-- prepare new span
start <- getCurrentTimeNanoseconds
-- slightly tricky: create a new Context with a new MVar with an
-- forked copy of the current Datum, creating the nested span.
let v = currentDatumFrom context
datum <- readMVar v
let datum' =
datum
{ spanIdentifierFrom = Just (Span unique)
, spanNameFrom = label
, spanTimeFrom = start
, parentIdentifierFrom = spanIdentifierFrom datum
}
v2 <- newMVar datum'
let context2 =
context
{ currentDatumFrom = v2
}
-- execute nested program
result <- subProgram context2 action
-- extract the Datum as it stands after running the action, finalize
-- with its duration, and send it
finish <- getCurrentTimeNanoseconds
datum2 <- readMVar v2
let datum2' =
datum2
{ durationFrom = Just (unTimeStamp finish - unTimeStamp start)
}
let tel = telemetryChannelFrom context
atomically $ do
writeTQueue tel (Just datum2')
-- now back to your regularly scheduled Haskell program
pure result
represent :: Int -> Char
represent x
| x < 10 = chr (48 + x)
| x < 36 = chr (65 + x - 10)
| x < 62 = chr (97 + x - 36)
| otherwise = '@'
-- TODO replace this with something that gets a UUID
randomIdentifier :: IO Rope
randomIdentifier = do
gen <- newStdGen
let result = packRope . fmap represent . take 16 . randomRs (0, 61) $ gen
pure result
{- |
Start a new trace. A random identifier will be generated.
You /must/ have a single \"root span\" immediately below starting a new trace.
@
program :: 'Core.Program.Execute.Program' 'Core.Program.Execute.None' ()
program = do
'beginTrace' $ do
'encloseSpan' \"Service Request\" $ do
...
@
-}
beginTrace :: Program τ α -> Program τ α
beginTrace action = do
trace <- liftIO randomIdentifier
usingTrace (Trace trace) Nothing action
{- |
Begin a new trace, but using a trace identifier provided externally. This is
the most common case. Internal services that are play a part of a larger
request will inherit a job identifier, sequence number, or other externally
supplied unique code. Even an internet facing web service might have a
correlation ID provided by the outside load balancers.
If you are continuting an existing trace within the execution path of another,
larger, enclosing service then you need to specify what the parent span's
identifier is in the second argument.
@
program :: 'Core.Program.Execute.Program' 'Core.Program.Execute.None' ()
program = do
-- do something that gets the trace ID
trace <- ...
-- and somethign to get the parent span ID
parent <- ...
'usingTrace' ('Trace' trace) ('Just' ('Span' span)) $ do
'encloseSpan' \"Internal processing\" $ do
...
@
-}
usingTrace :: Trace -> Maybe Span -> Program τ α -> Program τ α
usingTrace trace possibleParent action = do
context <- getContext
case possibleParent of
Nothing -> do
debug "trace" (unTrace trace)
Just parent -> do
debug "trace" (unTrace trace)
debug "parent" (unSpan parent)
liftIO $ do
-- prepare new span
let v = currentDatumFrom context
datum <- readMVar v
let datum2 =
datum
{ traceIdentifierFrom = Just trace
, parentIdentifierFrom = possibleParent
}
-- fork the Context
v2 <- newMVar datum2
let context2 =
context
{ currentDatumFrom = v2
}
-- execute nested program
subProgram context2 action
{- |
Add measurements to the current span.
@
telemetry
[ metric "calories" (667 :: Int)
, metric "precise" measurement
, metric "meal_name" ("hamburger" :: Rope)
, metric "flavour" True
]
@
The 'metric' function is a method provided by instances of the 'Telemtetry'
typeclass which is mostly a wrapper around constructing key/value pairs
suitable to be sent as measurements up to an observability service.
-}
telemetry :: [MetricValue] -> Program τ ()
telemetry values = do
context <- getContext
liftIO $ do
-- get the map out
let v = currentDatumFrom context
modifyMVar_
v
( \datum -> do
let meta = attachedMetadataFrom datum
-- update the map
let meta' = List.foldl' f meta values
-- replace the map back into the Datum (and thereby back into the
-- Context), updating it
let datum' =
datum
{ attachedMetadataFrom = meta'
}
pure datum'
)
where
f :: Map JsonKey JsonValue -> MetricValue -> Map JsonKey JsonValue
f acc (MetricValue k v) = insertKeyValue k v acc
{- |
Record telemetry about an event. Specify a label for the event and then
whichever metrics you wish to record.
The emphasis of this package is to create traces and spans. There are,
however, times when you just want to send telemetry about an event. You can
use 'sendEvent' to accomplush this.
If you call 'sendEvent' within an enclosing span created with 'encloseSpan'
(the usual and expected use case) then this event will be \"linked\" to this
span so that the observability tool can deisplay it attached to the span in
the in which it occured.
Not every situation is in the context of traces and spans and so you can use
this to send arbitrary telemetry.
-}
sendEvent :: Label -> [MetricValue] -> Program τ ()
sendEvent label values = do
context <- getContext
liftIO $ do
now <- getCurrentTimeNanoseconds
-- get the map out
let v = currentDatumFrom context
datum <- readMVar v
let meta = attachedMetadataFrom datum
-- update the map
let meta' = List.foldl' f meta values
-- replace the map back into the Datum and queue for sending
let datum' =
datum
{ spanNameFrom = label
, spanIdentifierFrom = Nothing
, parentIdentifierFrom = spanIdentifierFrom datum
, spanTimeFrom = now
, attachedMetadataFrom = meta'
}
let tel = telemetryChannelFrom context
atomically $ do
writeTQueue tel (Just datum')
where
f :: Map JsonKey JsonValue -> MetricValue -> Map JsonKey JsonValue
f acc (MetricValue k v) = insertKeyValue k v acc
-- get current time after digging out datum and override spanTimeFrom before
-- sending Datum
{- |
Override the start time of the current span.
Under normal circumstances this shouldn't be necessary. The start and end of a
span are recorded automatically when calling 'encloseSpan'. Observabilty tools
are designed to be used live; traces and spans should be created in real time
in your code.
-}
setStartTime :: TimeStamp -> Program τ ()
setStartTime time = do
context <- getContext
liftIO $ do
-- get the map out
let v = currentDatumFrom context
modifyMVar_
v
(\datum -> pure datum{spanTimeFrom = time})