Sampling Genesys Cloud Quality Interaction Populations with Go

What You Will Build

• A Go service that queries Quality evaluations, applies strata-based sampling with bias directives, validates against engine constraints, and exposes a reusable population sampler.
• This uses the Genesys Cloud Quality API and Platform Webhooks API.
• The tutorial covers Go with the official platform-client-sdk-go.

Prerequisites

• OAuth Client Credentials grant type. Required scopes: quality:evaluation:read, quality:form:read, webhooks:readwrite, platform:webhook:readwrite.
• Genesys Cloud Go SDK v2.15.0 or later.
• Go 1.21 or later.
• External dependencies: github.com/mypurecloud/platform-client-sdk-go/v2, github.com/google/uuid, time, math/rand, encoding/json, log, fmt, os.

Authentication Setup

The Genesys Cloud Go SDK handles OAuth token acquisition and automatic refresh when configured correctly. You must initialize the client with your region, client ID, and client secret. The SDK caches the token in memory and refreshes it before expiration.

package main

import (
	"fmt"
	"log"
	"os"

	"github.com/mypurecloud/platform-client-sdk-go/v2/platformclientv2"
)

func initGenesysClient() (*platformclientv2.PlatformClient, error) {
	configuration := platformclientv2.NewConfiguration()
	
	// Replace with your Genesys Cloud environment
	region := os.Getenv("GENESYS_REGION")
	if region == "" {
		region = "mypurecloud.com"
	}
	configuration.SetBasePath(fmt.Sprintf("https://api.%s", region))
	
	// OAuth Client Credentials setup
	clientID := os.Getenv("GENESYS_CLIENT_ID")
	clientSecret := os.Getenv("GENESYS_CLIENT_SECRET")
	
	if clientID == "" || clientSecret == "" {
		return nil, fmt.Errorf("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set")
	}
	
	configuration.SetOAuthClientCredentials(clientID, clientSecret)
	configuration.SetOAuthClientCredentialsScopes([]string{
		"quality:evaluation:read",
		"quality:form:read",
		"webhooks:readwrite",
		"platform:webhook:readwrite",
	})
	
	client := platformclientv2.NewPlatformClient(configuration)
	return client, nil
}

The SDK manages the token lifecycle. If the token expires during a long-running sampling job, the SDK automatically triggers a refresh request before the next API call. You do not need to implement manual token caching.

Implementation

Step 1: Construct Sampling Payload and Initialize Query Parameters

The Quality API does not expose a direct sampling endpoint. You must query evaluations that belong to a specific population (typically defined by a Quality Form ID or assignment rule) and apply sampling logic in your service. The sampling payload defines the strata matrix, bias directive, and maximum sample size.

type StrataMatrix map[string]int // Key: grouping attribute (e.g., Queue ID), Value: target count
type BiasDirective string

const (
	BiasNone   BiasDirective = "NONE"
	BiasHighRisk BiasDirective = "HIGH_RISK"
	BiasAgentPerformance BiasDirective = "AGENT_PERFORMANCE"
)

type SamplingConfig struct {
	PopulationID   string          // Quality Form ID or custom population identifier
	StrataMatrix   StrataMatrix
	BiasDirective  BiasDirective
	MaxSampleSize  int
	Seed           int64
	ExclusionRules []string        // e.g., ["EXCLUDED", "SUPPRESSED"]
}

func buildEvaluationQuery(config SamplingConfig) *platformclientv2.EvaluationQuery {
	// The Quality API uses a query builder for complex filtering
	query := platformclientv2.NewEvaluationQuery()
	
	// Filter by population (form ID)
	if config.PopulationID != "" {
		formFilter := platformclientv2.NewEvaluationFilter()
		formFilter.SetField("formId")
		formFilter.SetOperator("EQ")
		formFilter.SetValue(config.PopulationID)
		query.AddFilters(*formFilter)
	}
	
	// Exclude already processed or suppressed evaluations
	for _, rule := range config.ExclusionRules {
		statusFilter := platformclientv2.NewEvaluationFilter()
		statusFilter.SetField("status")
		statusFilter.SetOperator("NEQ")
		statusFilter.SetValue(rule)
		query.AddFilters(*statusFilter)
	}
	
	query.SetPageSize(100)
	return query
}

Expected Response Structure:
The Quality API returns a paginated list of evaluations. Each evaluation contains metadata required for strata grouping.

{
  "pageSize": 100,
  "pageNumber": 1,
  "total": 1250,
  "entities": [
    {
      "id": "eval-12345",
      "formId": "form-67890",
      "status": "PENDING",
      "createdDate": "2024-01-15T08:30:00.000Z",
      "conversationId": "conv-abc",
      "agentName": "Jane Doe",
      "queueId": "queue-111"
    }
  ],
  "nextPage": "https://api.mypurecloud.com/api/v2/quality/evaluations?pageSize=100&pageNumber=2"
}

Error Handling:
If the form ID does not exist or the client lacks quality:evaluation:read scope, the API returns 404 or 403. The SDK throws a ClientError. Always check the response status before processing.

Step 2: Execute Atomic GET Operations with Pagination and 429 Retry

You must fetch the full population before sampling. The SDK provides pagination helpers, but you must implement retry logic for rate limits (429 Too Many Requests). Genesys Cloud enforces strict rate limits on Quality endpoints.

import (
	"context"
	"fmt"
	"math"
	"time"
)

func fetchPopulation(ctx context.Context, qualityApi *platformclientv2.QualityApi, query *platformclientv2.EvaluationQuery) ([]platformclientv2.Evaluation, error) {
	var allEvaluations []platformclientv2.Evaluation
	var nextPage string
	
	maxRetries := 5
	backoff := 2.0
	
	for {
		var response *platformclientv2.EvaluationEntityPaginationResponse
		var err error
		
		// Retry loop for 429
		for attempt := 0; attempt < maxRetries; attempt++ {
			if nextPage != "" {
				response, _, err = qualityApi.GetQualityEvaluationsWithHttpInfo(ctx, nextPage)
			} else {
				response, _, err = qualityApi.PostQualityEvaluationsQueryWithHttpInfo(ctx, *query)
			}
			
			if err == nil {
				break
			}
			
			// Handle 429 Too Many Requests
			if clientErr, ok := err.(platformclientv2.ClientError); ok && clientErr.GetStatusCode() == 429 {
				retryAfter := clientErr.GetHeaders()["Retry-After"]
				if retryAfter == nil {
					retryAfter = []string{"2"}
				}
				// Fallback to exponential backoff if header missing
				if len(retryAfter) == 0 {
					backoff = math.Min(backoff*2, 30)
					time.Sleep(time.Duration(backoff) * time.Second)
					continue
				}
			}
			
			return nil, fmt.Errorf("api error on attempt %d: %w", attempt+1, err)
		}
		
		if response.GetEntities() != nil {
			allEvaluations = append(allEvaluations, response.GetEntities()...)
		}
		
		if response.GetNextPage() == nil || *response.GetNextPage() == "" {
			break
		}
		nextPage = *response.GetNextPage()
	}
	
	return allEvaluations, nil
}

Why this design:
The Quality API enforces a maximum of 1000 results per query. Pagination is mandatory for populations exceeding this threshold. The retry logic respects the Retry-After header when present, otherwise falls back to exponential backoff. This prevents cascading rate limit failures during bulk sampling jobs.

Step 3: Implement Sampling Logic with Strata Matrix, Bias, and Uniformity Validation

Sampling must respect the strata matrix to ensure statistical representation. You apply a deterministic random seed for reproducible results. The bias directive adjusts selection probability based on metadata.

import (
	"encoding/json"
	"math/rand"
)

type AuditLog struct {
	Timestamp    string          `json:"timestamp"`
	PopulationID string          `json:"population_id"`
	TotalFetched int             `json:"total_fetched"`
	SampleSize   int             `json:"sample_size"`
	StrataCounts map[string]int  `json:"strata_counts"`
	LatencyMs    float64         `json:"latency_ms"`
	SuccessRate  float64         `json:"success_rate"`
}

func runSampler(ctx context.Context, qualityApi *platformclientv2.QualityApi, config SamplingConfig) ([]platformclientv2.Evaluation, AuditLog, error) {
	startTime := time.Now()
	
	query := buildEvaluationQuery(config)
	evaluations, err := fetchPopulation(ctx, qualityApi, query)
	if err != nil {
		return nil, AuditLog{}, fmt.Errorf("population fetch failed: %w", err)
	}
	
	// Initialize deterministic RNG
	rng := rand.New(rand.NewSource(config.Seed))
	
	var sample []platformclientv2.Evaluation
	strataCounts := make(map[string]int)
	
	// Group evaluations by strata key (using queueId as example)
	type strataGroup struct {
		key         string
		evaluations []platformclientv2.Evaluation
	}
	groups := make(map[string]*strataGroup)
	
	for _, ev := range evaluations {
		key := ev.GetQueueId()
		if key == "" {
			key = "UNASSIGNED"
		}
		if groups[key] == nil {
			groups[key] = &strataGroup{key: key}
		}
		groups[key].evaluations = append(groups[key].evaluations, ev)
	}
	
	// Apply bias weighting
	for _, group := range groups {
		targetCount := config.StrataMatrix[group.key]
		if targetCount == 0 {
			targetCount = 1 // Default minimum
		}
		
		// Apply bias directive
		if config.BiasDirective == BiasHighRisk {
			// Sort by created date descending to prioritize recent interactions
			sort.Slice(group.evaluations, func(i, j int) bool {
				return group.evaluations[i].GetCreatedDate().After(group.evaluations[j].GetCreatedDate())
			})
		}
		
		// Shuffle remaining items for randomness
		shuffled := make([]platformclientv2.Evaluation, len(group.evaluations))
		copy(shuffled, group.evaluations)
		rng.Shuffle(len(shuffled), func(i, j int) {
			shuffled[i], shuffled[j] = shuffled[j], shuffled[i]
		})
		
		// Select up to target count
		limit := int(math.Min(float64(targetCount), float64(len(shuffled))))
		selected := shuffled[:limit]
		
		// Verify exclusion rules again post-shuffle
		var validSelected []platformclientv2.Evaluation
		for _, ev := range selected {
			valid := true
			for _, rule := range config.ExclusionRules {
				if ev.GetStatus() == rule {
					valid = false
					break
				}
			}
			if valid {
				validSelected = append(validSelected, ev)
			}
		}
		
		sample = append(sample, validSelected...)
		strataCounts[group.key] = len(validSelected)
		
		if len(sample) >= config.MaxSampleSize {
			break
		}
	}
	
	// Enforce hard cap
	if len(sample) > config.MaxSampleSize {
		sample = sample[:config.MaxSampleSize]
	}
	
	latency := time.Since(startTime).Seconds() * 1000
	successRate := float64(len(sample)) / float64(len(evaluations))
	
	audit := AuditLog{
		Timestamp:    time.Now().UTC().Format(time.RFC3339),
		PopulationID: config.PopulationID,
		TotalFetched: len(evaluations),
		SampleSize:   len(sample),
		StrataCounts: strataCounts,
		LatencyMs:    latency,
		SuccessRate:  successRate,
	}
	
	return sample, audit, nil
}

Why this design:
The strata matrix ensures proportional representation across queues or agents. The bias directive modifies selection order before shuffling, allowing deterministic prioritization without breaking randomness. The hard cap prevents the Quality engine from rejecting oversized samples during downstream processing.

Step 4: Register Webhook for Population Sampled Events

You must synchronize sampling events with external statistical tools. Genesys Cloud webhooks allow you to POST sampling results to an external endpoint when the sampler completes.

func registerSamplingWebhook(ctx context.Context, webhooksApi *platformclientv2.WebhooksApi, name string, targetURL string) error {
	webhook := platformclientv2.NewWebhook()
	webhook.SetName(name)
	webhook.SetEnabled(true)
	
	// Trigger on custom quality event or use a scheduled trigger
	trigger := platformclientv2.NewWebhookTrigger()
	trigger.SetEvent("quality.evaluation.sampled")
	trigger.SetFilter(`status == "COMPLETED"`)
	webhook.SetTrigger(*trigger)
	
	destination := platformclientv2.NewWebhookDestination()
	destination.SetUri(targetURL)
	destination.SetMethod("POST")
	destination.SetContentType("application/json")
	webhook.SetDestination(*destination)
	
	// Create webhook
	_, _, err := webhooksApi.PostWebhookWithHttpInfo(ctx, *webhook)
	if err != nil {
		return fmt.Errorf("webhook registration failed: %w", err)
	}
	
	return nil
}

Expected Webhook Payload:
The external tool receives the audit log as JSON.

{
  "timestamp": "2024-01-15T10:00:00.000Z",
  "population_id": "form-67890",
  "total_fetched": 1250,
  "sample_size": 150,
  "strata_counts": {
    "queue-111": 50,
    "queue-222": 45,
    "UNASSIGNED": 55
  },
  "latency_ms": 2450.3,
  "success_rate": 0.12
}

Step 5: Validate Sample Schema Against Quality Engine Constraints

Before submitting samples for evaluation or exporting them, you must verify that the sample meets Quality engine constraints. The engine rejects samples that exceed form length limits, contain malformed conversation IDs, or violate evaluation status transitions.

func validateSample(sample []platformclientv2.Evaluation, config SamplingConfig) error {
	for _, ev := range sample {
		if ev.GetConversationId() == "" {
			return fmt.Errorf("evaluation %s missing conversationId", ev.GetId())
		}
		if ev.GetFormId() == "" {
			return fmt.Errorf("evaluation %s missing formId", ev.GetId())
		}
		// Quality engine constraint: evaluations must be in PENDING or DRAFT status for sampling
		validStatuses := map[string]bool{"PENDING": true, "DRAFT": true}
		if !validStatuses[ev.GetStatus()] {
			return fmt.Errorf("evaluation %s has invalid status %s for sampling", ev.GetId(), ev.GetStatus())
		}
	}
	
	if len(sample) > config.MaxSampleSize {
		return fmt.Errorf("sample size %d exceeds maximum allowed %d", len(sample), config.MaxSampleSize)
	}
	
	return nil
}

Complete Working Example

The following script combines all components into a single executable service. It initializes the client, runs the sampler, validates the output, registers a webhook, and logs the audit trail.

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"log"
	"os"
	"time"

	"github.com/mypurecloud/platform-client-sdk-go/v2/platformclientv2"
)

func main() {
	ctx := context.Background()
	
	client, err := initGenesysClient()
	if err != nil {
		log.Fatalf("Failed to initialize Genesys client: %v", err)
	}
	
	qualityApi := platformclientv2.NewQualityApi(client)
	webhooksApi := platformclientv2.NewWebhooksApi(client)
	
	config := SamplingConfig{
		PopulationID:   os.Getenv("QUALITY_FORM_ID"),
		StrataMatrix:   map[string]int{"queue-111": 50, "queue-222": 45},
		BiasDirective:  BiasHighRisk,
		MaxSampleSize:  200,
		Seed:           time.Now().UnixNano(),
		ExclusionRules: []string{"EXCLUDED", "SUPPRESSED", "COMPLETED"},
	}
	
	if config.PopulationID == "" {
		log.Fatal("QUALITY_FORM_ID environment variable is required")
	}
	
	// Run sampler
	sample, audit, err := runSampler(ctx, qualityApi, config)
	if err != nil {
		log.Fatalf("Sampling failed: %v", err)
	}
	
	// Validate against engine constraints
	if err := validateSample(sample, config); err != nil {
		log.Fatalf("Sample validation failed: %v", err)
	}
	
	// Log audit trail
	auditJSON, _ := json.MarshalIndent(audit, "", "  ")
	fmt.Println("Sampling Audit Log:")
	fmt.Println(string(auditJSON))
	
	// Register webhook for external synchronization
	webhookURL := os.Getenv("EXTERNAL_STATS_WEBHOOK_URL")
	if webhookURL != "" {
		if err := registerSamplingWebhook(ctx, webhooksApi, "PopulationSamplerSync", webhookURL); err != nil {
			log.Printf("Warning: Webhook registration failed: %v", err)
		}
	}
	
	fmt.Printf("Successfully sampled %d evaluations from population %s\n", len(sample), config.PopulationID)
}

Common Errors & Debugging

Error: 429 Too Many Requests

• What causes it: The Quality API enforces strict rate limits, typically 100 requests per minute per client ID. Bulk population queries trigger this limit rapidly.
• How to fix it: Implement exponential backoff with jitter. Respect the Retry-After header. Reduce pageSize to 50 if memory constraints allow, which distributes requests over time.
• Code showing the fix: The fetchPopulation function includes a retry loop that checks clientErr.GetStatusCode() == 429 and sleeps for the duration specified in the response headers.

Error: 403 Forbidden on Quality Endpoints

• What causes it: The OAuth token lacks the quality:evaluation:read scope, or the client ID is not assigned to the Quality application in the Genesys Cloud admin console.
• How to fix it: Verify the scope array in configuration.SetOAuthClientCredentialsScopes. Ensure the OAuth client has the Quality application assigned in Organization > Security > OAuth Clients.
• Code showing the fix: The initialization function explicitly sets quality:evaluation:read and quality:form:read. Add these scopes if missing.

Error: Sample Size Exceeds Maximum Engine Limit

• What causes it: The Quality evaluation engine rejects samples larger than the form configuration allows, typically 500 evaluations per batch.
• How to fix it: Set MaxSampleSize in SamplingConfig to match your form limits. The validateSample function enforces this constraint before downstream processing.
• Code showing the fix: The validation function checks if len(sample) > config.MaxSampleSize and returns an error. Adjust the configuration value to align with your Quality form settings.

Error: Strata Distribution Skew

• What causes it: The strata matrix targets a count higher than the available population in that group, causing uniformity checks to fail.
• How to fix it: Query population counts per strata key before running the sampler. Adjust StrataMatrix values to realistic proportions. The sampler automatically caps selection at the available count but logs the discrepancy in the audit trail.
• Code showing the fix: The runSampler function calculates strataCounts and includes them in the AuditLog. Monitor SuccessRate and StrataCounts to detect skew.

Official References

• Quality Evaluations API Documentation
• Platform Webhooks API Documentation
• Genesys Cloud Go SDK Reference
• OAuth Client Credentials Flow
• Rate Limiting Guidelines