Featurevisor

SDKs

Java SDK

Featurevisor's Java SDK is a library for evaluating feature flags, experiment variations, and variables in your Java applications.

Installation

In your Java application, update pom.xml to add the following:

Repository

For finding GitHub Package (public package):

<repositories>
    <repository>
        <id>github</id>
        <name>GitHub Packages</name>
        <url>https://maven.pkg.github.com/featurevisor/featurevisor-java</url>
    </repository>
</repositories>

Dependency

Add Featurevisor Java SDK as a dependency with your desired version:

<dependencies>
    <dependency>
        <groupId>com.featurevisor</groupId>
        <artifactId>featurevisor-java</artifactId>
        <version>0.0.6</version>
    </dependency>
</dependencies>

Find latest version here: https://github.com/featurevisor/featurevisor-java/packages

Authentication

To authenticate with GitHub Packages, in your ~/.m2/settings.xml file, add the following:

<?xml version="1.0" encoding="UTF-8"?>
<settings xmlns="http://maven.apache.org/SETTINGS/1.0.0"
          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
          xsi:schemaLocation="http://maven.apache.org/SETTINGS/1.0.0
                              http://maven.apache.org/xsd/settings-1.0.0.xsd">
  <servers>
    <server>
      <id>github</id>
      <username>YOUR_GITHUB_USERNAME</username>
      <password>YOUR_GITHUB_TOKEN</password>
    </server>
  </servers>
</settings>

You can generate a new GitHub token with read:packages scope here: https://github.com/settings/tokens

See example application here: https://github.com/featurevisor/featurevisor-example-java

Initialization

The SDK can be initialized by passing datafile content directly:

import com.featurevisor.sdk.Featurevisor;
// Load datafile content
String datafileUrl = "https://cdn.yoursite.com/datafile.json";
String datafileContent = "..." // load your datafile content
// Create SDK instance
Featurevisor f = Featurevisor.createInstance(datafileContent);

or by constructing a Featurevisor.Options object:

Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafileContent)
);

We will learn about several different options in the next sections.

Evaluation types

We can evaluate 3 types of values against a particular feature:

  • Flag (boolean): whether the feature is enabled or not
  • Variation (Object): the variation of the feature (if any)
  • Variables: variable values of the feature (if any)

These evaluations are run against the provided context.

Context

Contexts are attribute values that we pass to SDK for evaluating features against.

Think of the conditions that you define in your segments, which are used in your feature's rules.

They are plain maps:

Map<String, Object> context = new HashMap<>();
context.put("userId", "123");
context.put("country", "nl");
// ...other attributes

Context can be passed to SDK instance in various different ways, depending on your needs:

Setting initial context

You can set context at the time of initialization:

Map<String, Object> initialContext = new HashMap<>();
initialContext.put("deviceId", "123");
initialContext.put("country", "nl");
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafileContent)
    .context(initialContext));

This is useful for values that don't change too frequently and available at the time of application startup.

Setting after initialization

You can also set more context after the SDK has been initialized:

Map<String, Object> additionalContext = new HashMap<>();
additionalContext.put("userId", "123");
additionalContext.put("country", "nl");
f.setContext(additionalContext);

This will merge the new context with the existing one (if already set).

Replacing existing context

If you wish to fully replace the existing context, you can pass true in second argument:

Map<String, Object> newContext = new HashMap<>();
newContext.put("deviceId", "123");
newContext.put("userId", "234");
newContext.put("country", "nl");
newContext.put("browser", "chrome");
f.setContext(newContext, true); // replace existing context

Manually passing context

You can optionally pass additional context manually for each and every evaluation separately, without needing to set it to the SDK instance affecting all evaluations:

Map<String, Object> context = new HashMap<>();
context.put("userId", "123");
context.put("country", "nl");
boolean isEnabled = f.isEnabled("my_feature", context);
String variation = f.getVariation("my_feature", context);
String variableValue = f.getVariableString("my_feature", "my_variable", context);

When manually passing context, it will merge with existing context set to the SDK instance before evaluating the specific value.

Further details for each evaluation types are described below.

Check if enabled

Once the SDK is initialized, you can check if a feature is enabled or not:

String featureKey = "my_feature";
boolean isEnabled = f.isEnabled(featureKey);
if (isEnabled) {
    // do something
}

You can also pass additional context per evaluation:

Map<String, Object> additionalContext = new HashMap<>();
// ...additional context
boolean isEnabled = f.isEnabled(featureKey, additionalContext);

Getting variation

If your feature has any variations defined, you can evaluate them as follows:

String featureKey = "my_feature";
String variation = f.getVariation(featureKey);
if ("treatment".equals(variation)) {
    // do something for treatment variation
} else {
    // handle default/control variation
}

Additional context per evaluation can also be passed:

String variation = f.getVariation(featureKey, additionalContext);

Getting variables

Your features may also include variables, which can be evaluated as follows:

String variableKey = "bgColor";
String bgColorValue = f.getVariableString(featureKey, variableKey);

Additional context per evaluation can also be passed:

String bgColorValue = f.getVariableString(featureKey, variableKey, additionalContext);

Type specific methods

Next to generic getVariable() methods, there are also type specific methods available for convenience:

f.getVariableBoolean(featureKey, variableKey, context);
f.getVariableString(featureKey, variableKey, context);
f.getVariableInteger(featureKey, variableKey, context);
f.getVariableDouble(featureKey, variableKey, context);
f.getVariableArray(featureKey, variableKey, context);
f.<Map<String, Object>>getVariableObject(featureKey, variableKey, context);
f.<MyCustomClass>getVariableObject(featureKey, variableKey, context);
f.<Map<String, Object>>getVariableJSON(featureKey, variableKey, context);
f.<MyCustomClass>getVariableJSON(featureKey, variableKey, context);

Getting all evaluations

You can get evaluations of all features available in the SDK instance:

import com.featurevisor.types.EvaluatedFeatures;
import com.featurevisor.types.EvaluatedFeature;
EvaluatedFeatures allEvaluations = f.getAllEvaluations(context);
// Access the evaluations map
Map<String, EvaluatedFeature> evaluations = allEvaluations.getValue();
System.out.println(evaluations);
// {
//   "myFeature": {
//     "enabled": true,
//     "variation": "control",
//     "variables": {
//       "myVariableKey": "myVariableValue"
//     }
//   },
//
//   "anotherFeature": {
//     "enabled": true,
//     "variation": "treatment"
//   }
// }

This is handy especially when you want to pass all evaluations from a backend application to the frontend.

Sticky

For the lifecycle of the SDK instance in your application, you can set some features with sticky values, meaning that they will not be evaluated against the fetched datafile:

Initialize with sticky

Map<String, Object> stickyFeatures = new HashMap<>();
Map<String, Object> myFeatureSticky = new HashMap<>();
myFeatureSticky.put("enabled", true);
myFeatureSticky.put("variation", "treatment");
Map<String, Object> myVariables = new HashMap<>();
myVariables.put("myVariableKey", "myVariableValue");
myFeatureSticky.put("variables", myVariables);
stickyFeatures.put("myFeatureKey", myFeatureSticky);
Map<String, Object> anotherFeatureSticky = new HashMap<>();
anotherFeatureSticky.put("enabled", false);
stickyFeatures.put("anotherFeatureKey", anotherFeatureSticky);
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafile)
    .sticky(stickyFeatures));

Once initialized with sticky features, the SDK will look for values there first before evaluating the targeting conditions and going through the bucketing process.

Set sticky afterwards

You can also set sticky features after the SDK is initialized:

Map<String, Object> stickyFeatures = new HashMap<>();
// ... build sticky features map
f.setSticky(stickyFeatures, true); // replace existing sticky features

Setting datafile

You may also initialize the SDK without passing datafile, and set it later on:

f.setDatafile(datafileContent);

Updating datafile

You can set the datafile as many times as you want in your application, which will result in emitting a datafile_set event that you can listen and react to accordingly.

The triggers for setting the datafile again can be:

  • periodic updates based on an interval (like every 5 minutes), or
  • reacting to:
    • a specific event in your application (like a user action), or
    • an event served via websocket or server-sent events (SSE)

Interval-based update

Here's an example of using interval-based update:

// Using ScheduledExecutorService for periodic updates
ScheduledExecutorService scheduler = Executors.newScheduledThreadPool(1);
scheduler.scheduleAtFixedRate(() -> {
    // Fetch new datafile content
    String newDatafileContent = // ... fetch from your CDN
    DatafileContent newDatafile = DatafileContent.fromJson(newDatafileContent);
    // Update the SDK
    f.setDatafile(newDatafile);
}, 0, 5, TimeUnit.MINUTES);

Logging

By default, Featurevisor SDKs will print out logs to the console for info level and above.

Levels

These are all the available log levels:

  • error
  • warn
  • info
  • debug

Customizing levels

If you choose debug level to make the logs more verbose, you can set it at the time of SDK initialization.

Setting debug level will print out all logs, including info, warn, and error levels.

import com.featurevisor.sdk.Logger;
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafile)
    .logLevel(Logger.LogLevel.DEBUG));

You can also set log level from SDK instance afterwards:

f.setLogLevel(Logger.LogLevel.DEBUG);

Handler

You can also pass your own log handler, if you do not wish to print the logs to the console:

// Create a custom logger with a custom handler
Logger customLogger = Logger.createLogger(new Logger.CreateLoggerOptions()
    .level(Logger.LogLevel.INFO)
    .handler((level, message, details) -> {
        // do something with the log
        System.out.println("[" + level + "] " + message);
    }));
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafile)
    .logger(customLogger));

Alternatively, you can create a custom logger directly:

Logger customLogger = new Logger(Logger.LogLevel.INFO, (level, message, details) -> {
    // do something with the log
    System.out.println("[" + level + "] " + message);
});
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafile)
    .logger(customLogger));

Further log levels like info and debug will help you understand how the feature variations and variables are evaluated in the runtime against given context.

Events

Featurevisor SDK implements a simple event emitter that allows you to listen to events that happen in the runtime.

You can listen to these events that can occur at various stages in your application:

datafile_set

Runnable unsubscribe = f.on("datafile_set", (event) -> {
    String revision = (String) event.get("revision"); // new revision
    String previousRevision = (String) event.get("previousRevision");
    Boolean revisionChanged = (Boolean) event.get("revisionChanged"); // true if revision has changed
    // list of feature keys that have new updates,
    // and you should re-evaluate them
    @SuppressWarnings("unchecked")
    List<String> features = (List<String>) event.get("features");
    // handle here
});
// stop listening to the event
unsubscribe.run();

The features array will contain keys of features that have either been:

  • added, or
  • updated, or
  • removed

compared to the previous datafile content that existed in the SDK instance.

context_set

Runnable unsubscribe = f.on("context_set", (event) -> {
    Boolean replaced = (Boolean) event.get("replaced"); // true if context was replaced
    @SuppressWarnings("unchecked")
    Map<String, Object> context = (Map<String, Object>) event.get("context"); // the new context
    System.out.println("Context set");
});

sticky_set

Runnable unsubscribe = f.on("sticky_set", (event) -> {
    Boolean replaced = (Boolean) event.get("replaced"); // true if sticky features got replaced
    @SuppressWarnings("unchecked")
    List<String> features = (List<String>) event.get("features"); // list of all affected feature keys
    System.out.println("Sticky features set");
});

Evaluation details

Besides logging with debug level enabled, you can also get more details about how the feature variations and variables are evaluated in the runtime against given context:

// flag
Map<String, Object> evaluation = f.evaluateFlag(featureKey, context);
// variation
Map<String, Object> evaluation = f.evaluateVariation(featureKey, context);
// variable
Map<String, Object> evaluation = f.evaluateVariable(featureKey, variableKey, context);

The returned object will always contain the following properties:

  • featureKey: the feature key
  • reason: the reason how the value was evaluated

And optionally these properties depending on whether you are evaluating a feature variation or a variable:

  • bucketValue: the bucket value between 0 and 100,000
  • ruleKey: the rule key
  • error: the error object
  • enabled: if feature itself is enabled or not
  • variation: the variation object
  • variationValue: the variation value
  • variableKey: the variable key
  • variableValue: the variable value
  • variableSchema: the variable schema

Hooks

Hooks allow you to intercept the evaluation process and customize it further as per your needs.

Defining a hook

A hook is a simple object with a unique required name and optional functions:

Map<String, Object> myCustomHook = new HashMap<>();
myCustomHook.put("name", "my-custom-hook");
// before evaluation
myCustomHook.put("before", (options) -> {
    String type = (String) options.get("type"); // "feature" | "variation" | "variable"
    String featureKey = (String) options.get("featureKey");
    String variableKey = (String) options.get("variableKey"); // if type is "variable"
    @SuppressWarnings("unchecked")
    Map<String, Object> context = (Map<String, Object>) options.get("context");
    // update context before evaluation
    context.put("someAdditionalAttribute", "value");
    options.put("context", context);
    return options;
});
// after evaluation
myCustomHook.put("after", (evaluation, options) -> {
    String reason = (String) evaluation.get("reason"); // "error" | "feature_not_found" | "variable_not_found" | ...
    if ("error".equals(reason)) {
        // log error
        return;
    }
});
// configure bucket key
myCustomHook.put("bucketKey", (options) -> {
    String featureKey = (String) options.get("featureKey");
    @SuppressWarnings("unchecked")
    Map<String, Object> context = (Map<String, Object>) options.get("context");
    String bucketBy = (String) options.get("bucketBy");
    String bucketKey = (String) options.get("bucketKey"); // default bucket key
    // return custom bucket key
    return bucketKey;
});
// configure bucket value (between 0 and 100,000)
myCustomHook.put("bucketValue", (options) -> {
    String featureKey = (String) options.get("featureKey");
    @SuppressWarnings("unchecked")
    Map<String, Object> context = (Map<String, Object>) options.get("context");
    String bucketKey = (String) options.get("bucketKey");
    Integer bucketValue = (Integer) options.get("bucketValue"); // default bucket value
    // return custom bucket value
    return bucketValue;
});

Registering hooks

You can register hooks at the time of SDK initialization:

List<Map<String, Object>> hooks = new ArrayList<>();
hooks.add(myCustomHook);
Featurevisor f = Featurevisor.createInstance(new Featurevisor.Options()
    .datafile(datafile)
    .hooks(hooks));

Or after initialization:

Runnable removeHook = f.addHook(myCustomHook);
// removeHook.run();

Child instance

When dealing with purely client-side applications, it is understandable that there is only one user involved, like in browser or mobile applications.

But when using Featurevisor SDK in server-side applications, where a single server instance can handle multiple user requests simultaneously, it is important to isolate the context for each request.

That's where child instances come in handy:

Map<String, Object> childContext = new HashMap<>();
childContext.put("userId", "123");
ChildInstance childF = f.spawn(childContext);

Now you can pass the child instance where your individual request is being handled, and you can continue to evaluate features targeting that specific user alone:

boolean isEnabled = childF.isEnabled("my_feature");
String variation = childF.getVariation("my_feature");
String variableValue = childF.getVariableString("my_feature", "my_variable");

Similar to parent SDK, child instances also support several additional methods:

  • setContext
  • setSticky
  • isEnabled
  • getVariation
  • getVariable
  • getVariableBoolean
  • getVariableString
  • getVariableInteger
  • getVariableDouble
  • getVariableArray
  • getVariableObject
  • getVariableJSON
  • getAllEvaluations
  • on
  • close

Close

Both primary and child instances support a .close() method, that removes forgotten event listeners (via on method) and cleans up any potential memory leaks.

f.close();

CLI usage

This package also provides a CLI tool for running your Featurevisor project's test specs and benchmarking against this Java SDK:

Test

Learn more about testing here.

$ mvn exec:java -Dexec.mainClass="com.featurevisor.cli.CLI" -Dexec.args="test --projectDirectoryPath=/absolute/path/to/your/featurevisor/project"

Additional options that are available:

$ mvn exec:java -Dexec.mainClass="com.featurevisor.cli.CLI" -Dexec.args="test --projectDirectoryPath=/absolute/path/to/your/featurevisor/project --quiet --onlyFailures --keyPattern=myFeatureKey --assertionPattern=#1"

Benchmark

Learn more about benchmarking here.

$ mvn exec:java -Dexec.mainClass="com.featurevisor.cli.CLI" -Dexec.args="benchmark --projectDirectoryPath=/absolute/path/to/your/featurevisor/project --environment=production --feature=myFeatureKey --context='{\"country\": \"nl\"}' --n=1000"

Assess distribution

Learn more about assessing distribution here.

$ mvn exec:java -Dexec.mainClass="com.featurevisor.cli.CLI" -Dexec.args="assess-distribution --projectDirectoryPath=/absolute/path/to/your/featurevisor/project --environment=production --feature=foo --variation --context='{\"country\": \"nl\"}' --populateUuid=userId --populateUuid=deviceId --n=1000"
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