In the first two blog posts of the blog series Building an E-Commerce Marketplace Middleware in Clojure, we learnt how to bootstrap a Clojure project using Mount & Aero and how to configure database connection pooling & database migration along with reloaded workflow. We are going to continue setting up the infrastructure, and in this blog post, we are going to take up logging using Timbre.

Timbre is a Clojure/Script logging library that enables to configure logging using a simple Clojure map. If you ever had a hard time dealing with complex (XML based) configuration setup for logging, you will feel a breath of fresh air while using Timbre. Let’s dive in!

This blog post is a part 3 of the blog series Building an E-Commerce Marketplace Middleware in Clojure.

Timbre 101

To get started, let’s add the dependency in the project.clj and restart the REPL to download and include the dependency in our project.

(defproject wheel "0.1.0-SNAPSHOT" ; ... :dependencies [; ... [com.taoensso/timbre "4.10.0"]] ; ... )

Then create a new file log.clj and refer the timbre library.

> touch src/wheel/infra/log.clj

(ns wheel.infra.log (:require [taoensso.timbre :as timbre]))

To play with the functionality provided by Timbre, send the above snippet to the REPL and then use any of the info , warn , debug or error macro to perform the logging. By default, Timbre uses println to write the logs in the console.

wheel.infra.log=> (timbre/info "Hello Timbre!") 19-09-29 04:59:03 UnknownHost INFO [wheel.infra.log:1] - Hello Timbre! nil

These macros also accept Clojure maps.

wheel.infra.log=> (timbre/info {:Hello "Timbre!"}) 19-09-29 05:02:44 UnknownHost INFO [wheel.infra.log:1] - {:Hello "Timbre!"} nil

Customizing the Output Log Format

The default output format is naive and not friendly for reading by an external tool like logstash. We can modify the behaviour and use JSON as our output format by following the below steps.

Let’s add the Chesire library to take care of JSON serialization in the project.clj file and restart the REPL.

(defproject wheel "0.1.0-SNAPSHOT" ; ... :dependencies [; ... [chesire "5.9.0"]] ; ... )

Timbre provides a hook output-fn , a function with the signature (fn [data]) -> string , to customize the output format. The data is a map that contains the actual message, log level, timestamp, hostname and much more.

; src/wheel/infra/log.clj ; ... (defn- json-output [{:keys [level msg_ instant]}] ;<1> (let [event (read-string (force msg_))] ;<2> (json/generate-string {:timestamp instant ;<3> :level level :event event})))

1 It destructures the interested keys from the data map.

2 Timbre use delay for the logging message. So, here we are retrieving the value using the force function and then uses read-string to convert the string to its corresponding Clojure data structure.

3 It generates the stringified JSON representation of the log entry containing the log level, timestamp and the actual message.

To wire this function with Timbre, we are going to make use of its merge-config! function.

; src/wheel/infra/log.clj ; ... (defn init [] (timbre/merge-config! {:output-fn json-output}))

As the name indicates, the init function acts as the entry point for initialization the logging, and here we are modifying the Timbre’s config to use our json-output function as its output-fn function.

Now if we log after calling this init function, we will get the output as below.

wheel.infra.log=> (init) {:level :debug, :ns-whitelist [], :ns-blacklist [] ...}

wheel.infra.log=> (timbre/info {:name :an-event/succeeded}) {"timestamp":"2019-09-29T05:30:42Z", "level":"info","event":{"name":"an-event/succeeded"}} nil

Let’s invoke this init function from the application’s start-app function to set up this configuration during application bootstrap.

(ns wheel.infra.core (:require [mount.core :as mount] + [wheel.infra.log :as log] [wheel.infra.config :as config] [wheel.infra.database :as db])) (defn start-app [] + (log/init) (mount/start)) ...

Logs as the Single Source of Truth

The middleware that we built acts as a liaison between our client’s order management system(OMS) and the e-commerce marketplaces.

Logging all the business (domain) event occurred in or processed by the middleware is one of the critical requirement. We incorporated it by defining functions that either returns an event (a Clojure map) or a list of events.

At the boundaries of the system, we consume these data and write it to a log. In the logging configuration, we had a database appender which projects the log entries (events) to a table. We’ll learn more about it in the upcoming blog posts.

In this blog post, we are going to focus on modelling the event.

Modelling Event using clojure.spec

An event in the wild is a Clojure map with a bunch of key-value pairs. But treating the event like this will be hard to develop and maintain. So, we need a specification of what constitutes an event. We are going to make use of clojure.spec to define it.

Let’s get started by creating a new file event.clj and add the spec for the individual keys.

> mkdir src/wheel/middleware > touch src/wheel/middleware/event.clj

(ns wheel.middleware.event (:require [clojure.spec.alpha :as s])) (s/def ::id uuid?) (s/def ::parent-id ::id) ; <1> (s/def ::name qualified-keyword?) ; <2> (s/def ::level #{:info :warn :debug :error :fatal})

1 As the name indicates, the parent-id represents the id of an event which resulted in the event in question.

2 An event name is a namespaced keyword. We’ll discuss it more in the upcoming blog posts.

To model the timestamp of the event, we are going to take advantage of the fact our Client works on IST(+05:30) timezone and all their transactions are on IST.

Let’s add the ist-timestamp spec in a new file offset-date-time.clj . We will be using ISO 8061 combined date-time representation with a time zone designator.

> touch src/wheel/offset-date-time.clj

(ns wheel.offset-date-time (:require [clojure.spec.alpha :as s]) (:import [java.time.format DateTimeFormatter DateTimeParseException] [java.time OffsetDateTime])) (defn iso-8061-format? [x] (try (.parse DateTimeFormatter/ISO_OFFSET_DATE_TIME x) true (catch DateTimeParseException e false))) (defn ist? [x] (if (iso-8061-format? x) (= (.. (OffsetDateTime/parse x) getOffset toString) "+05:30") false)) (s/def ::iso-8061-format (s/and string? iso-8061-format?)) (s/def ::ist-timestamp (s/and ::iso-8061-format ist?))

We can verify it in the REPL as below.

wheel.offset-date-time=> (s/valid? ::ist-timestamp "2007-04-05T12:30-02:00") false wheel.offset-date-time=> (s/valid? ::ist-timestamp "2019-10-01T06:56+05:30") true

Then in event.clj , use this ist-timestamp spec to define the timestamp spec.

; src/wheel/middleware/event.clj (ns wheel.middleware.event (:require ; ... [wheel.offset-date-time :as offset-date-time])) ; ... (s/def ::timestamp ::offset-date-time/ist-timestamp)

There are two types of events in the middleware, system and domain events.

The system events represent the events associated with the technical implementation of the application like db.migration/failed , ibm-mq.connection/failed , and so on.

As you correctly guessed, the domain events represent business-specific events in the middleware.

; src/wheel/middleware/event.clj ; ... (s/def ::type #{:domain :system})

All the domain events should have a channel-id and channel-name . The term channel represents the e-commerce marketplace (Amazon, Flipkart or Tata CliQ) through which our client sells their products.

To define the spec for the channel-id (a non-empty string identifier from OMS), channel-name (an enumeration of markplaces), create a new file channel.clj .

> mkdir src/wheel/marketplace > touch src/wheel/marketplace/channel.clj

(ns wheel.marketplace.channel (:require [clojure.spec.alpha :as s])) (s/def ::id (complement clojure.string/blank?)) (s/def ::name #{:tata-cliq :amazon :flipkart})

Then we can use this spec in the event spec.

; src/wheel/middleware/event.clj (ns wheel.middleware.event (:require ; ... [wheel.marketplace.channel :as channel])) ; ... (s/def ::channel-id ::channel/id) (s/def ::channel-name ::channel/name)

Now we have all the individual attributes of an event, and we can define the spec of the event itself using Clojure’s multi-spec

; src/wheel/middleware/event.clj ; ... (defmulti event-type :type) ; <1> (defmethod event-type :system [_] ; <2> (s/keys :req-un [::id ::name ::type ::level ::timestamp] :opt-un [::parent-id])) (defmethod event-type :domain [_] ; <3> (s/keys :req-un [::id ::name ::type ::level ::timestamp ::channel-id ::channel-name] :opt-un [::parent-id])) (defmethod event-type :default [_] ; <4> (s/keys :req-un [::type])) (s/def ::event (s/multi-spec event-type :type))

1 It defines multi-method dispatch based of the :type key.

2 It defines the :system event spec.

3 It defines the :domain event spec.

4 It defines the default event spec which requires an event map with a :type key and conforms to the ::type spec.

Let’s verify the spec in the REPL

wheel.middleware.event=> (s/valid? ::event {:name :ranging/succeeded :type :domain :channel-id "UA" :level :info :timestamp "2019-10-01T12:30+05:30" :id (java.util.UUID/randomUUID) :channel-name :tata-cliq}) true

wheel.middleware.event=> (s/valid? ::event {:name :db.migration/failed :type :system :level :fatal :timestamp "2019-10-01T12:30+05:30" :id (java.util.UUID/randomUUID)}) true

We will revisiting this event spec, when we are implementing the business requirements.

Asserting & Logging Event

We are going to add a function write! in the log.clj file that takes an event and writes it to the log using Timbre. The application boundaries will use this function to perform the logging.

; src/wheel/infra/log.clj (ns wheel.infra.log (:require ; ... [clojure.spec.alpha :as s] [wheel.middleware.event :as event])) ; ... (defn write! [{:keys [level] :as event}] ; <1> {:pre [(s/assert ::event/event event)]} ; <2> (case level ; <3> :info (timbre/info event) :debug (timbre/debug event) :warn (timbre/warn event) :error (timbre/error event) :fatal (timbre/fatal event)))

1It destructures the level from the event and also keeps the event

2It uses the Clojure’s function pre-condition to assert the incoming parameter against the event spec.

3It invokes the appropriate log macros of the Timbre library based on the event’s level .

When we evaluate this write! function with a random map, we’ll get the following output.

wheel.infra.log=> (write! {:level :info :name :foo}) {"timestamp":"2019-10-01T15:46:22Z","level":"info","event":{"level":"info","name":"foo"}} nil

If you are wondering the pre-condition didn’t get executed, it’s because Clojure spec’s asserts as disabled by default, we need to enable them.

wheel.infra.log=> (s/check-asserts true) true wheel.infra.log=> (write! {:level :info :name :foo}) Execution error - invalid arguments to wheel.infra.log/write! at (log.clj:17). {:level :info, :name :foo} - failed: (contains? % :type) at: [nil] class clojure.lang.ExceptionInfo # ... Stack traces ignored for brevity

After enabling the asserts checking it is now working as expected.

In our application, we are going to turn on the check-asserts by setting it up during application startup.

; src/wheel/infra/core.clj (ns wheel.infra.core (:require ; ... [clojure.spec.alpha :as s])) (defn start-app ([] (start-app true)) ([check-asserts] (log/init) (s/check-asserts check-asserts) (mount/start))) ; ...

The rewritten version of start-app is a multi-arity function that optionally accepts a parameter to set the check-asserts flag. Typically in the production environment, we can turn off this flag.

To log multiple events, let’s add the write-all! function, which invokes the write! function for each provided events.

; src/wheel/infra/log.clj ; ... (defn write-all! [events] (run! write! events))

As a final step, rewrite the json-output function to log the event itself as it already contains the timestamp and level.

; src/wheel/infra/log.clj ; ... (defn- json-output [{:keys [msg_]}] (let [event (read-string (force msg_))] (json/generate-string event)))

Summary

In this blog post, we learned how to configure Timbre with JSON output and also created abstractions write! & write-all! to do the logging. In the upcoming blog posts, we are going to add database and Slack appenders. Stay tuned!

The source code associated with this part is available on this GitHub repository.