co-log-json: Structured messages support in co-log ecosystem.

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The library implements of a very simple approach to structured logging, that ca be used with the co-log ecosystem or on it's own see cheops-logger.

It provides:

  • Colog.Json — API for adding structured context to the log messages

  • Colog.Json.Action — efficient function for dumping logs in the following format.

By default it emits logs in the following format (pretty-printed for convenience):

{ "namespace":"server.package" -- namespace for the component
, "severity": "DEBUG"          -- severity level
, "thread":19                  -- id of the thread that emitted the message
, "message":"some long text "  -- textual message itself
, "data":                      -- user data
{ "ip":"8.8.8.8"
, "http.request_id":"b362cd5db5c193c05312af4d3a399955"
, "http.method":"DELETE"
, "http.path":"/url/"
, "user_id":"123"
}
}

The most interesting thing here is the field data that can be used by the user to add additional structured info to the message.


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Versions [RSS] 0.0.1.0, 0.1.0.0
Change log CHANGELOG.md
Dependencies aeson (>=2.0 && <2.2), base (>=4.11 && <5), bytestring (>=0.10 && <0.12), co-log-core (>=0.2 && <0.4), containers (>=0.6 && <0.7), string-conv (>=0.1 && <0.3), text (>=1.2 && <2.1) [details]
Tested with ghc ==9.2.2 || ==9.0.2 || ==8.10.7
License MPL-2.0
Copyright (C) 2019-2023 Фонд Талант и Успех
Author Alexander Vershilov
Maintainer alexander.vershilov@sirius.online
Category System
Bug tracker https://github.com/cheopslab/cheops-logger/issues/new?labels=co-log-json
Uploaded by AlexanderVershilov at 2023-01-10T16:05:46Z
Distributions NixOS:0.1.0.0
Downloads 346 total (14 in the last 30 days)
Rating 1.5 (votes: 3) [estimated by Bayesian average]
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Status Docs available [build log]
Last success reported on 2023-01-10 [all 1 reports]

Readme for co-log-json-0.1.0.0

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Hackage MPL-2.0 license Haskell CI

co-log-json

co-log-json allows writing structured logs in your application.

The library allows adding additional machine-readable context to the log messages. I.e. each log message is a JSON object with a predefined structure where additional user context can be added. Such logs can be easily indexed by external logs systems such as Graylog or Elastic search. The message logging is done using a special context, that keeps the information about additional attributes. Such contexts form a nested scope, and all messages in the score inherit provided context:

   scope [ user = "Joe"] 
     |
     | ==>  {"message":"user arrived", "data": { "user": "Joe"}
     |
     +------ scope [ tag = "human" ]
              |
              | ==> {"message": "user entered the door", "data": { "user": "Joe", "tag": "human"}

In other words, this library takes two choices:

  1. We write full context with each message. This approach allows using external tools (like elastic-search) that can index message without any additional work and information. Any message can be lost without affecting the ability to decode other messages. An alternative approach could be emitting a list of events (possibly as a bytecode), such an approach is taken by the tracing libraries. It requires more works during reading and indexing logs, and in the case in some logs are logs may render later ones unusable or lose some info.

  2. We keep a state context so we don't need to attach context messages to each one. An alternative approach is the extraction of the structure information from the message itself. This approach is taken in some structured logging libraries, it can provide better error messages. However, it requires to think about the message context all the time (and developer user may not even know all interesting context where the message will be used).

Using a library

To to use a library you'll need to add co-log-json to the dependency list.

library.cabal

library
  build-depends:
    base,
    co-log-json ^>= 0.0

Setting the library

import Colog.Json                       -- Core API for structured logging
import Colog.Json.Action (logToHandle)  -- Actions to store the message
import System.IO (stderr)

main :: IO ()
main = do
  -- First, we need to set up log storing function:
  --   To emit logs we need to create a context.
  --    Context takes the action to store log and it's possible to
  --    attach additional information to it.

  let context = mkLogger (logToHandle stderr)
  --                          ^
  --                          |
  --                          +------  `LogAction IO Message` 
  --                                    (see discussion "Why IO below")
  --
  -- Once 'context' is created it can be passed to the other parts
  -- of the code or used to emit logs.

  logDebug context "Hi, there!"
  --         ^         ^
  --         |         |
  --         |         +----- `LogStr` type - is an efficient text builder.
  --         |                 
  --         |
  --         +-- log context

  -- Will output:
  --
  -- ```
  -- {"severity":"DEBUG", "thread": 1, "message": "Hi, there!"}
  -- ```
  --                ^               ^                ^
  --                |               |                +------------ Message itself
  --                |               +----------------------------- Id of the thread that emitted the message
  --                +----------------- Severity level: Debug, Info, Notice, Error, Critical, Alert, Emergency
  -- 
  -- to the stderr.

  -- There are other helper functions list `logInfo`, `logNotice`, etc.

Now let's discuss LogStr type. It exists to efficiently generate message without extra allocations that can be avoided. It's just a Text.Builder though internal representation may evolve in the future. LogStr allows message concatenation without allocating intermediate structures, so it allows efficient log building. For example line:

  logDebug context $ "a" <> "b" <> "c"

will write all text string "a", "b", "c" directly to the buffer, and can do more optimizations. So it's quite safe to use the library even with a large number of logs.

The 'LogStr' type implement IsString instance it means that you can just write string literals and they will be treated as 'LogStr'. To concatenate two 'LogStr' you can use <> operation.

In addition you can convert any string lines that has StringConv a T.Text, i.e. can be converted to LogStr using ls :: StringConv a T.Text => a -> LogStr. Efficiency and safety of this conversion depends on the concrete instance implementation and is out of control of the package.

   logDebug context $ "foo is " <> ls ("ы":: ByteString)

In case your data structure does not implement StringConv a it's possible to use not efficient but very general showLS :: Show a => a -> LogStr method that will work for any type that has Show instance.

Adding context.

But just writing JSON messages is not very interesting, we want to control the context of the message. In order to add user data to the context we can use addContext :: PushContext -> LoggerEnv -> LoggerEnv method.


   let context1 = addContext (sl "user_id" (1::Int)) context
   --    ^                    ^     ^         ^        ^
   --    |                    |     |         |        +--- old context
   --    |                    |     |         +------------ user data 
   --    |                    |     +---------------------- key for the user data
   --    |                    +---------------------------- function that generates an entry
   --    +------------------------------------------------- new context that has data attached

   logDebug context1 "Hi again!"

   -- Will emit to the stderr:
   --
   -- ```
   -- {"severity":"DEBUG", "thread": 1, "message": "Hi, there!", "data": {"user_id":1}}
   -- ```
   --                                                              ^           ^    ^
   --                                                              |           |    +-- value
   --                                                              |           +------- key
   --                                                              +--- all user data is kept under 'data' key

Sidenote: 'sl' function looks redundant, but it's needed in order to provide a future compatibility for a case when internal structure of user data is changing. Historically it came from katip library, there are more functions that allows context creation but

Function sl :: ToJSON a => T.Text -> a -> PushContext prepares update to the context. It encodes user data to JSON. This is why we had to add type annotation to 1 otherwise GHC had no means to infer the type).

It's important that the library does not perform any compaction of key-values, i.e.:

   logDebug (addContext (sl "user_id" 2) context1) "Who am I?"
   -- Will emit:
   -- ```
   -- {"severity":"DEBUG", "thread": 1, "message": "Hi, there!", "data": {"user_id":1, "user_id": 2}}
   -- ```

This is done for purpose, but may be a subject to change in the future major versions.

addContext is not the only function that allows to modify context, there is the other one addNamespace :: Text -> LoggerEnv -> LoggerEnv, this function adds an entry about the current namespace. Namespace is a nested list of strings that tells the logical part of the codebase the log belongs to. It's kept separate fom the data, and it's possible to use in library filtering (using cfilter) or filtering in external system.

The described functionality is enough to perform logging. However, it may worth discussing interoperability with the rest of co-log ecosystem and ergonomics.

co-log interoperability

The co-log ecosystem works with "LogAction m a" and in the package, we use "LogEnv" it means that we are losing most of the benefits of the library and can't use a lot of utility functions. To improve the situation it's possible to convert LogEnv into LogAction m (Severity,LogStr) using function unLogger. Then we will have log action that will emit a message with the current context, but the context will no longer be modifiable.

Ergonomics

The package provides no ergonomic tools by default and it's important that addContext is a pure function. On the one han,d it introduces a log of boilerplate code but on the other.

It allows to modify context even outside of the effectful computation for example with servant you may have:

-- | Catalogue of items 
data CatalogueApi route = CatalogueApi
  { _the_catalogue :: route :- Capture "catalogue_id" CatalogueId :> ToServantAPI Bar
  , ...
  } 

-- Item
data ItemApi route = ItemApi
  { _items :: route :- "items" :> Get '[JSON] (Vector Item)
  , ...
  }

handleCatalogue :: LoggerEnv -> ToServant CatalogueApi AsServer
handleCatalogue ctx' = CatalogueApi
  { _the_catalogue = \catalogue_id ->
     handleItem (addContext "catalogue_id" catalogue_id) ctx) catalogue_id
  , ...
  }
  where 
    ctx = addNamespace "catalogue" ctx'

handleItem :: LoggerEnv -> CatalogueId -> ToServant ItemApi AsServer
handleItem ctx' catalogue_id = ItemApi ...
  where ctx = addNamespace "item" ctx'

So we can build computation that we will execute later while modifying the context.

On the other hand, we can always wrap this pure function into an effect system of choice be it either handle pattern or readert or MTL or effect system. This library does not target any particular solution and want to introduce neither additional dependencies nor additional restrictions on the user.