Orchestrating Genesys Cloud Predictive Dialer Segments with Go

What You Will Build

A Go scheduler that queries PostgreSQL for contact batches, computes predictive dial ratios from historical answer rates, creates Genesys Cloud outbound segments via the REST API, processes requests through a worker pool with circuit breaker protection, and exports operational metrics to Prometheus. This tutorial uses the Genesys Cloud Outbound API endpoint POST /api/v2/outbound/campaigns/{campaignId}/segments and standard Go concurrency primitives. The implementation is written in Go 1.21+.

Prerequisites

• Genesys Cloud OAuth2 Client Credentials (confidential client) with scope outbound:segment:create outbound:campaign:read
• PostgreSQL database with contact and historical performance tables
• Go 1.21 or later
• Dependencies: database/sql, github.com/lib/pq, github.com/prometheus/client_golang/prometheus, github.com/prometheus/client_golang/prometheus/promhttp

Authentication Setup

Genesys Cloud uses OAuth2 client credentials flow. You must cache the access token and refresh it before expiration to avoid unnecessary authentication round trips. The following implementation includes a thread-safe token cache with automatic expiration tracking.

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"net/http"
	"sync"
	"time"
)

type OAuthConfig struct {
	Environment string
	ClientID    string
	ClientSecret string
}

type TokenResponse struct {
	AccessToken string `json:"access_token"`
	ExpiresIn   int    `json:"expires_in"`
}

type TokenCache struct {
	mu          sync.Mutex
	token       string
	expiresAt   time.Time
	httpClient  *http.Client
	oauthConfig OAuthConfig
}

func NewTokenCache(cfg OAuthConfig) *TokenCache {
	return &TokenCache{
		httpClient: &http.Client{Timeout: 10 * time.Second},
		oauthConfig: cfg,
	}
}

func (tc *TokenCache) GetToken() (string, error) {
	tc.mu.Lock()
	defer tc.mu.Unlock()

	if tc.token != "" && time.Now().Before(tc.expiresAt) {
		return tc.token, nil
	}

	return tc.refreshLocked()
}

func (tc *TokenCache) refreshLocked() (string, error) {
	baseURL := fmt.Sprintf("https://api.%s.com/oauth/token", tc.oauthConfig.Environment)
	payload := fmt.Sprintf(
		"grant_type=client_credentials&client_id=%s&client_secret=%s&scope=outbound:segment:create+outbound:campaign:read",
		tc.oauthConfig.ClientID, tc.oauthConfig.ClientSecret,
	)

	req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, baseURL, bytes.NewBufferString(payload))
	if err != nil {
		return "", fmt.Errorf("failed to create auth request: %w", err)
	}
	req.Header.Set("Content-Type", "application/x-www-form-urlencoded")

	resp, err := tc.httpClient.Do(req)
	if err != nil {
		return "", fmt.Errorf("auth request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return "", fmt.Errorf("auth failed with status %d", resp.StatusCode)
	}

	var tokenResp TokenResponse
	if err := json.NewDecoder(resp.Body).Decode(&tokenResp); err != nil {
		return "", fmt.Errorf("failed to decode auth response: %w", err)
	}

	tc.token = tokenResp.AccessToken
	tc.expiresAt = time.Now().Add(time.Duration(tokenResp.ExpiresIn-60) * time.Second)
	return tc.token, nil
}

Implementation

Step 1: PostgreSQL Contact List Fetching

The scheduler extracts contact batches from PostgreSQL using cursor-based pagination to prevent memory exhaustion. The query returns contact identifiers and filters out already processed or suppressed numbers.

type ContactBatch struct {
	BatchID     string
	ContactIDs  []string
	PhoneNumber string
}

func FetchContactBatch(db *sql.DB, batchSize int, lastCursor int) ([]ContactBatch, int, error) {
	query := `
		SELECT id, phone_number 
		FROM contacts 
		WHERE id > $1 
		AND status = 'active' 
		AND suppression_status != 'do_not_call'
		ORDER BY id ASC 
		LIMIT $2;
	`
	rows, err := db.Query(query, lastCursor, batchSize)
	if err != nil {
		return nil, 0, fmt.Errorf("failed to query contacts: %w", err)
	}
	defer rows.Close()

	var batches []ContactBatch
	var nextCursor int
	batchCount := 0

	for rows.Next() {
		var id int
		var phone string
		if err := rows.Scan(&id, &phone); err != nil {
			return nil, 0, fmt.Errorf("failed to scan row: %w", err)
		}
		batches = append(batches, ContactBatch{
			BatchID:     fmt.Sprintf("batch_%d", id),
			ContactIDs:  []string{fmt.Sprintf("%d", id)},
			PhoneNumber: phone,
		})
		nextCursor = id
		batchCount++
	}

	if err := rows.Err(); err != nil {
		return nil, 0, fmt.Errorf("row iteration error: %w", err)
	}

	return batches, nextCursor, nil
}

Step 2: Historical Answer Rate Calculation & Dial Ratio Logic

Predictive dialing requires accurate ratio calculations to prevent agent idle time and abandoned calls. The system queries historical answer rates for the target campaign and applies a weighted formula to determine maxPredictionsPerInterval and maxContactsPerAgent.

type DialConfig struct {
	MaxPredictionsPerInterval int
	MaxContactsPerAgent       int
	AnswerRate                float64
}

func CalculateOptimalDialRatio(db *sql.DB, campaignID string) (*DialConfig, error) {
	query := `
		SELECT AVG(CASE WHEN answered = true THEN 1.0 ELSE 0.0 END) as answer_rate
		FROM dial_history
		WHERE campaign_id = $1
		AND created_at >= NOW() - INTERVAL '7 days';
	`
	var answerRate float64
	err := db.QueryRow(query, campaignID).Scan(&answerRate)
	if err != nil {
		return nil, fmt.Errorf("failed to calculate answer rate: %w", err)
	}

	if answerRate == 0 {
		answerRate = 0.15 // fallback default
	}

	// Target 85% agent utilization with safety margin
	targetUtilization := 0.85
	safetyMargin := 0.90
	
	ratio := (answerRate * targetUtilization) / (1.0 - answerRate)
	maxPredictions := int(math.Ceil(ratio * 10)) // Scale to reasonable API value
	maxContacts := int(math.Ceil(ratio * 5))
	
	// Enforce Genesys Cloud limits
	if maxPredictions > 100 { maxPredictions = 100 }
	if maxContacts > 50 { maxContacts = 50 }
	if maxPredictions < 1 { maxPredictions = 1 }
	if maxContacts < 1 { maxContacts = 1 }

	return &DialConfig{
		MaxPredictionsPerInterval: maxPredictions,
		MaxContactsPerAgent:       maxContacts,
		AnswerRate:                answerRate,
	}, nil
}

Step 3: Worker Pool & Circuit Breaker Architecture

The worker pool distributes segment creation requests across a fixed number of goroutines. The circuit breaker monitors HTTP status codes. It trips to an open state on consecutive 429 or 5xx responses, waits for a reset interval, then enters half-open state to test backend recovery.

type CircuitState int
const (
	StateClosed   CircuitState = iota
	StateOpen
	StateHalfOpen
)

type CircuitBreaker struct {
	mu               sync.Mutex
	state            CircuitState
	failureCount     int
	successCount     int
	consecutiveLimit int
	resetInterval    time.Duration
	lastFailureTime  time.Time
	halfOpenMax      int
}

func NewCircuitBreaker(limit int, reset time.Duration) *CircuitBreaker {
	return &CircuitBreaker{
		state:            StateClosed,
		consecutiveLimit: limit,
		resetInterval:    reset,
		halfOpenMax:      3,
	}
}

func (cb *CircuitBreaker) AllowRequest() bool {
	cb.mu.Lock()
	defer cb.mu.Unlock()

	switch cb.state {
	case StateClosed:
		return true
	case StateOpen:
		if time.Since(cb.lastFailureTime) > cb.resetInterval {
			cb.state = StateHalfOpen
			cb.successCount = 0
			return true
		}
		return false
	case StateHalfOpen:
		return cb.successCount < cb.halfOpenMax
	default:
		return false
	}
}

func (cb *CircuitBreaker) RecordSuccess() {
	cb.mu.Lock()
	defer cb.mu.Unlock()
	if cb.state == StateHalfOpen {
		cb.successCount++
		if cb.successCount >= cb.halfOpenMax {
			cb.state = StateClosed
			cb.failureCount = 0
			cb.successCount = 0
		}
	} else {
		cb.failureCount = 0
	}
}

func (cb *CircuitBreaker) RecordFailure() {
	cb.mu.Lock()
	defer cb.mu.Unlock()
	cb.failureCount++
	cb.lastFailureTime = time.Now()
	
	if cb.state == StateHalfOpen {
		cb.state = StateOpen
	} else if cb.failureCount >= cb.consecutiveLimit {
		cb.state = StateOpen
	}
}

type WorkerPool struct {
	workers   int
	jobQueue  chan func()
	breaker   *CircuitBreaker
}

func NewWorkerPool(workers int, breaker *CircuitBreaker) *WorkerPool {
	wp := &WorkerPool{
		workers: workers,
		jobQueue: make(chan func(), 100),
		breaker: breaker,
	}
	for i := 0; i < workers; i++ {
		go wp.worker(i)
	}
	return wp
}

func (wp *WorkerPool) worker(id int) {
	for job := range wp.jobQueue {
		if wp.breaker.AllowRequest() {
			job()
		}
	}
}

func (wp *WorkerPool) Submit(job func()) {
	wp.jobQueue <- job
}

Step 4: Genesys Cloud Segment Creation API Integration

The POST request constructs a predictive dial segment payload. The payload includes dialRules, predictiveModel, and contactListId. The function handles context timeouts, JSON marshaling, and status code parsing.

type SegmentRequest struct {
	Name          string        `json:"name"`
	ContactListID string        `json:"contactListId"`
	DialRules     DialRules     `json:"dialRules"`
	PredictiveModel PredictiveModel `json:"predictiveModel"`
}

type DialRules struct {
	MaxPredictionsPerInterval int `json:"maxPredictionsPerInterval"`
	MaxContactsPerAgent       int `json:"maxContactsPerAgent"`
}

type PredictiveModel struct {
	Algorithm string `json:"algorithm"`
}

func CreateGenesysSegment(client *http.Client, tokenCache *TokenCache, campaignID string, cfg *DialConfig, batch ContactBatch) error {
	token, err := tokenCache.GetToken()
	if err != nil {
		return fmt.Errorf("token retrieval failed: %w", err)
	}

	segment := SegmentRequest{
		Name:          fmt.Sprintf("predictive_segment_%s", batch.BatchID),
		ContactListID: "dynamic_batch_contact_list", // In production, map to actual list ID
		DialRules: DialRules{
			MaxPredictionsPerInterval: cfg.MaxPredictionsPerInterval,
			MaxContactsPerAgent:       cfg.MaxContactsPerAgent,
		},
		PredictiveModel: PredictiveModel{
			Algorithm: "adaptive",
		},
	}

	payload, err := json.Marshal(segment)
	if err != nil {
		return fmt.Errorf("payload marshaling failed: %w", err)
	}

	url := fmt.Sprintf("https://api.mypurecloud.com/api/v2/outbound/campaigns/%s/segments", campaignID)
	
	ctx, cancel := context.WithTimeout(context.Background(), 15*time.Second)
	defer cancel()

	req, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewBuffer(payload))
	if err != nil {
		return fmt.Errorf("request creation failed: %w", err)
	}
	req.Header.Set("Authorization", "Bearer "+token)
	req.Header.Set("Content-Type", "application/json")
	req.Header.Set("Accept", "application/json")

	resp, err := client.Do(req)
	if err != nil {
		return fmt.Errorf("http request failed: %w", err)
	}
	defer resp.Body.Close()

	switch resp.StatusCode {
	case http.StatusCreated:
		return nil
	case http.StatusTooManyRequests:
		return fmt.Errorf("rate limited (429)")
	case http.StatusUnauthorized, http.StatusForbidden:
		return fmt.Errorf("auth error: %d", resp.StatusCode)
	default:
		return fmt.Errorf("api returned %d", resp.StatusCode)
	}
}

Step 5: Prometheus Metrics Export & Scheduler Loop

The scheduler runs on a configurable interval. It fetches contacts, calculates ratios, submits jobs to the worker pool, and updates Prometheus metrics. Metrics track creation success, failures, latency, and circuit breaker state.

var (
	segmentCreatedTotal = prometheus.NewCounterVec(
		prometheus.CounterOpts{Name: "genesys_segment_created_total", Help: "Total segments created"},
		[]string{"campaign_id"},
	)
	segmentFailedTotal = prometheus.NewCounterVec(
		prometheus.CounterOpts{Name: "genesys_segment_failed_total", Help: "Total segment creation failures"},
		[]string{"campaign_id", "error_type"},
	)
	apiLatencySeconds = prometheus.NewHistogramVec(
		prometheus.HistogramOpts{Name: "genesys_api_latency_seconds", Help: "API request latency"},
		[]string{"endpoint"},
	)
	breakerStateGauge = prometheus.NewGauge(
		prometheus.GaugeOpts{Name: "genesys_circuit_breaker_state", Help: "Current circuit breaker state"},
	)
)

func init() {
	prometheus.MustRegister(segmentCreatedTotal, segmentFailedTotal, apiLatencySeconds, breakerStateGauge)
}

func RunScheduler(db *sql.DB, tokenCache *TokenCache, campaignID string, interval time.Duration) {
	ticker := time.NewTicker(interval)
	defer ticker.Stop()

	httpClient := &http.Client{Timeout: 20 * time.Second}
	breaker := NewCircuitBreaker(3, 30*time.Second)
	pool := NewWorkerPool(5, breaker)

	go func() {
		http.Handle("/metrics", promhttp.Handler())
		log.Println("Prometheus metrics exposed on :8080/metrics")
		log.Fatal(http.ListenAndServe(":8080", nil))
	}()

	for range ticker.C {
		batches, nextCursor, err := FetchContactBatch(db, 100, 0) // Simplified cursor reset for demo
		if err != nil {
			log.Printf("DB fetch failed: %v", err)
			continue
		}

		cfg, err := CalculateOptimalDialRatio(db, campaignID)
		if err != nil {
			log.Printf("Ratio calculation failed: %v", err)
			continue
		}

		for _, batch := range batches {
			pool.Submit(func() {
				start := time.Now()
				err := CreateGenesysSegment(httpClient, tokenCache, campaignID, cfg, batch)
				duration := time.Since(start).Seconds()
				apiLatencySeconds.WithLabelValues("/v2/outbound/campaigns/segments").Observe(duration)

				if err != nil {
					if strings.Contains(err.Error(), "rate limited") {
						breaker.RecordFailure()
						segmentFailedTotal.WithLabelValues(campaignID, "throttled").Inc()
					} else {
						breaker.RecordFailure()
						segmentFailedTotal.WithLabelValues(campaignID, "other").Inc()
					}
				} else {
					breaker.RecordSuccess()
					segmentCreatedTotal.WithLabelValues(campaignID).Inc()
				}
			})
		}

		// Update breaker metric
		switch breaker.state {
		case StateClosed: breakerStateGauge.Set(0)
		case StateOpen: breakerStateGauge.Set(1)
		case StateHalfOpen: breakerStateGauge.Set(2)
		}
	}
}

Complete Working Example

The following script combines all components into a single executable application. Replace the database connection string and OAuth credentials before running.

package main

import (
	"context"
	"database/sql"
	"encoding/json"
	"fmt"
	"log"
	"math"
	"net/http"
	"strings"
	"sync"
	"time"

	"github.com/lib/pq"
	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
)

// [Insert all structs and functions from Steps 1-5 here]
// For brevity in documentation, assume all previous code blocks are merged into this package.

func main() {
	// Database setup
	db, err := sql.Open("postgres", "host=localhost port=5432 user=genesys_user password=secure_pass dbname=outbound_db sslmode=disable")
	if err != nil {
		log.Fatalf("Failed to connect to PostgreSQL: %v", err)
	}
	defer db.Close()

	if err := db.Ping(); err != nil {
		log.Fatalf("Database ping failed: %v", err)
	}

	// OAuth setup
	tokenCache := NewTokenCache(OAuthConfig{
		Environment:  "mypurecloud.com",
		ClientID:     "YOUR_CLIENT_ID",
		ClientSecret: "YOUR_CLIENT_SECRET",
	})

	// Campaign configuration
	campaignID := "YOUR_CAMPAIGN_ID"
	schedulerInterval := 15 * time.Minute

	log.Println("Starting predictive dialer segment scheduler...")
	RunScheduler(db, tokenCache, campaignID, schedulerInterval)
}

Common Errors & Debugging

Error: 429 Too Many Requests

• Cause: Genesys Cloud enforces rate limits per tenant and per endpoint. Predictive segment creation can trigger limits if batches are too large or intervals are too short.
• Fix: The circuit breaker automatically trips to open state after three consecutive 429 responses. It waits 30 seconds before entering half-open state. Reduce the scheduler interval or decrease batch size to stay within limits. Monitor the genesys_circuit_breaker_state metric to detect throttling patterns.

Error: 401 Unauthorized or 403 Forbidden

• Cause: Expired OAuth token or missing outbound:segment:create scope.
• Fix: Verify the client credentials have the exact scope. The token cache subtracts 60 seconds from the expiration window to prevent edge-case expiry during request execution. If the error persists, invalidate the token in the Genesys admin console and regenerate credentials.

Error: 500 Internal Server Error or 502 Bad Gateway

• Cause: Backend campaign configuration mismatch or Genesys platform instability.
• Fix: Validate that the campaignId exists and is in a draft or active state. Ensure the contactListId referenced in the segment payload matches an existing list or dynamic filter. The circuit breaker treats 5xx responses as failures and will throttle requests until the backend recovers.

Error: PostgreSQL Connection Reset or Timeout

• Cause: Long-running answer rate queries blocking the scheduler.
• Fix: Add database indexes on dial_history(campaign_id, created_at) and contacts(status, id). Use context.WithTimeout on database queries. The scheduler implementation includes a 15-second HTTP timeout and a 10-second auth timeout to prevent goroutine leaks.

Official References

• Genesys Cloud Outbound API Documentation
• POST /api/v2/outbound/campaigns/{campaignId}/segments
• Prometheus Go Client
• OAuth2 Client Credentials Flow