skills.vishalvoidskills/vishalvoid
Technical & DevelopmentIntermediate

azure-ai-anomalydetector-java

Anomaly detection applications

Developer Setup

Setup & Installation

bash
npx skills add https://github.com/microsoft/skills --skill azure-ai-anomalydetector-java

Overview

What This Skill Does

Azure AI Anomaly Detector SDK for Java lets you detect anomalies in time-series data using univariate or multivariate analysis. It supports batch detection, real-time streaming detection, and change point detection across single or correlated signals.

Application

When to use this Skill

Documentation

Show Skills.md file

Azure AI Anomaly Detector SDK for Java

Build anomaly detection applications using the Azure AI Anomaly Detector SDK for Java.

Installation

<dependency>
  <groupId>com.azure</groupId>
  <artifactId>azure-ai-anomalydetector</artifactId>
  <version>3.0.0-beta.6</version>
</dependency>

Client Creation

Sync and Async Clients

import com.azure.ai.anomalydetector.AnomalyDetectorClientBuilder;
import com.azure.ai.anomalydetector.MultivariateClient;
import com.azure.ai.anomalydetector.UnivariateClient;
import com.azure.core.credential.AzureKeyCredential;

String endpoint = System.getenv("AZURE_ANOMALY_DETECTOR_ENDPOINT");
String key = System.getenv("AZURE_ANOMALY_DETECTOR_API_KEY");

// Multivariate client for multiple correlated signals
MultivariateClient multivariateClient = new AnomalyDetectorClientBuilder()
    .credential(new AzureKeyCredential(key))
    .endpoint(endpoint)
    .buildMultivariateClient();

// Univariate client for single variable analysis
UnivariateClient univariateClient = new AnomalyDetectorClientBuilder()
    .credential(new AzureKeyCredential(key))
    .endpoint(endpoint)
    .buildUnivariateClient();
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