Skip to main content

ADR-030: Document Server & Knowledge Base as a Service (KBaaS) - Part 2 (Technical)

Document Specification Block​

Document: ADR-030-v4-document-server-kbaas-part2-technical
Version: 2.0.0
Purpose: Technical implementation of cloud-native documentation platform with web portal and AI integration
Audience: Software Engineers, DevOps, System Architects
Date Created: 2025-09-28
Date Modified: 2025-09-30
Date Released: 2025-09-30
Status: DRAFT - ENHANCED
QA Reviewed: 2025-09-28 (v1.1.0)

Table of Contents​

↑ Back to Top

Technical Overview​

CODITECT Document Server v2.0 provides a comprehensive cloud-native documentation platform with:

  • Human-Friendly Web Portal: Beautiful rendered documentation at https://docs.coditect.ai
  • AI-Optimized APIs: Bulk document fetching and context-aware recommendations
  • Pod-Level Caching: Pre-populated documentation in every user workspace
  • Intelligent Search: ML-powered relevance scoring and suggestions

Key Technologies​

  • Language: Rust 1.73+
  • Framework: Axum 0.7 (integrated with CODITECT Hub)
  • Storage: FoundationDB + Google Cloud Storage
  • Search: Tantivy (Rust-native Lucene) with ML ranking
  • Cache: Redis with predictive prefetch + Pod volumes
  • CDN: Cloudflare for global distribution
  • Rendering: Pulldown-cmark for Markdown, Syntect for highlighting
  • Frontend: React SSG with Next.js for SEO optimization

↑ Back to Top

System Architecture​

High-Level Architecture v2.0​

Data Model​

↑ Back to Top

Core Components​

Enhanced Components v2.0​

1. Markdown Rendering Engine​

// src/services/render_engine.rs
use pulldown_cmark::{Parser, Options, html};
use syntect::easy::HighlightLines;
use syntect::parsing::SyntaxSet;
use syntect::highlighting::{ThemeSet, Style};

pub struct RenderEngine {
    syntax_set: SyntaxSet,
    theme_set: ThemeSet,
    mermaid_renderer: MermaidRenderer,
}

impl RenderEngine {
    pub async fn render_markdown(&self, content: &str) -> Result<RenderedDocument> {
        // Configure parser with all extensions
        let mut options = Options::empty();
        options.insert(Options::ENABLE_TABLES);
        options.insert(Options::ENABLE_FOOTNOTES);
        options.insert(Options::ENABLE_STRIKETHROUGH);
        options.insert(Options::ENABLE_TASKLISTS);
        
        let parser = Parser::new_ext(content, options);
        
        // Process code blocks with syntax highlighting
        let highlighted = self.process_code_blocks(parser).await?;
        
        // Render Mermaid diagrams
        let with_diagrams = self.render_mermaid_diagrams(highlighted).await?;
        
        // Convert to HTML with custom classes
        let mut html_output = String::new();
        html::push_html(&mut html_output, with_diagrams.into_iter());
        
        Ok(RenderedDocument {
            html: html_output,
            toc: self.extract_table_of_contents(content),
            metadata: self.extract_frontmatter(content),
        })
    }
    
    async fn process_code_blocks(&self, parser: Parser) -> Result<Vec<Event>> {
        // Syntax highlighting for 100+ languages
        // Custom theme support (light/dark)
        // Line numbers optional
        // Copy button injection
    }
}

2. Pod Cache Manager​

// src/services/pod_cache_manager.rs
use std::path::PathBuf;
use tokio::sync::RwLock;
use std::collections::HashMap;

pub struct PodCacheManager {
    cache_root: PathBuf,
    manifests: RwLock<HashMap<String, CacheManifest>>,
    sync_interval: Duration,
}

impl PodCacheManager {
    pub async fn initialize_pod_cache(&self, pod_id: &str, workspace_type: &str) -> Result<()> {
        let cache_path = self.cache_root.join(pod_id).join(".coditect/docs");
        tokio::fs::create_dir_all(&cache_path).await?;
        
        // Pre-populate based on workspace type
        let initial_docs = match workspace_type {
            "rust-backend" => vec!["adrs/", "standards/rust/", "guides/api/"],
            "react-frontend" => vec!["adrs/", "standards/react/", "guides/frontend/"],
            "full-stack" => vec!["adrs/", "standards/", "guides/"],
            _ => vec!["adrs/", "guides/quickstart/"],
        };
        
        // Download and extract document bundles
        for category in initial_docs {
            self.sync_category(pod_id, category).await?;
        }
        
        // Create manifest
        let manifest = CacheManifest {
            pod_id: pod_id.to_string(),
            workspace_type: workspace_type.to_string(),
            last_sync: Utc::now(),
            documents: self.scan_cache_contents(&cache_path).await?,
        };
        
        self.manifests.write().await.insert(pod_id.to_string(), manifest);
        Ok(())
    }
    
    pub async fn sync_pod_cache(&self, pod_id: &str) -> Result<SyncReport> {
        // Check for updates since last sync
        // Download only changed documents
        // Update manifest
        // Return sync statistics
    }
}

3. AI Bulk Fetch Service​

// src/services/ai_bulk_service.rs
pub struct AIBulkService {
    document_store: Arc<DocumentStore>,
    recommendation_engine: Arc<RecommendationEngine>,
}

impl AIBulkService {
    pub async fn fetch_agent_documents(
        &self, 
        request: AgentBulkRequest
    ) -> Result<AgentDocumentBundle> {
        // Determine relevant documents based on agent type
        let base_docs = match request.agent_type {
            AgentType::Orchestrator => {
                vec![
                    "adrs/*",
                    "standards/orchestration/*",
                    "guides/agent-coordination/*",
                ]
            }
            AgentType::RustDeveloper => {
                vec![
                    "adrs/technical/*",
                    "standards/rust/*",
                    "guides/api/*",
                ]
            }
            // ... other agent types
        };
        
        // Fetch all matching documents
        let mut documents = Vec::new();
        for pattern in base_docs {
            let matches = self.document_store.glob_fetch(pattern).await?;
            documents.extend(matches);
        }
        
        // Add recommended documents based on context
        if let Some(context) = request.context {
            let recommendations = self.recommendation_engine
                .get_contextual_docs(&context, request.agent_type)
                .await?;
            documents.extend(recommendations);
        }
        
        // Format according to requested type
        let formatted = match request.format {
            Format::Markdown => self.format_as_markdown(documents),
            Format::Json => self.format_as_json(documents),
            Format::Yaml => self.format_as_yaml(documents),
        };
        
        Ok(AgentDocumentBundle {
            documents: formatted,
            manifest: self.generate_manifest(&documents),
            total_size: documents.iter().map(|d| d.size).sum(),
            cache_key: self.generate_cache_key(&request),
        })
    }
}

1. Document Service​

// src/services/document_service.rs
use axum::extract::{Path, State};
use serde::{Deserialize, Serialize};

#[derive(Debug, Serialize, Deserialize)]
pub struct Document {
    pub id: String,
    pub kb_id: String,
    pub title: String,
    pub content_type: ContentType,
    pub metadata: DocumentMetadata,
    pub access_level: AccessLevel,
}

#[derive(Debug, Serialize, Deserialize)]
pub enum ContentType {
    Markdown,
    PDF,
    HTML,
    PlainText,
}

#[derive(Debug, Serialize, Deserialize)]
pub struct DocumentMetadata {
    pub version: String,
    pub tags: Vec<String>,
    pub industry: Option<String>,
    pub compliance_framework: Option<String>,
    pub last_updated: DateTime<Utc>,
    pub update_frequency: UpdateFrequency,
}

pub struct DocumentService {
    storage: Arc<StorageBackend>,
    cache: Arc<CacheLayer>,
    search: Arc<SearchEngine>,
    access_control: Arc<AccessControl>,
}

impl DocumentService {
    pub async fn get_document(
        &self,
        doc_id: &str,
        user: &AuthenticatedUser,
    ) -> Result<Document, ApiError> {
        // Check access permissions
        self.access_control.check_permission(
            user,
            doc_id,
            Permission::Read,
        ).await?;
        
        // Try cache first
        if let Some(doc) = self.cache.get(doc_id).await? {
            self.record_access(user, doc_id, AccessType::CacheHit).await?;
            return Ok(doc);
        }
        
        // Load from storage
        let doc = self.storage.get_document(doc_id).await?;
        
        // Cache for future requests
        self.cache.set(doc_id, &doc, self.calculate_ttl(&doc)).await?;
        
        // Record access for ML optimization
        self.record_access(user, doc_id, AccessType::CacheMiss).await?;
        
        // Prefetch related documents
        tokio::spawn(self.prefetch_related(doc_id, user.clone()));
        
        Ok(doc)
    }
    
    async fn prefetch_related(&self, doc_id: &str, user: AuthenticatedUser) {
        let related = self.search.find_related(doc_id, 5).await;
        for related_id in related {
            if self.access_control.can_access(&user, &related_id).await {
                let _ = self.cache.warm(&related_id).await;
            }
        }
    }
}

2. Knowledge Base Registry​

// src/services/kb_registry.rs
pub struct KnowledgeBaseRegistry {
    bases: HashMap<String, KnowledgeBase>,
    industry_packs: HashMap<String, IndustryPack>,
}

#[derive(Clone)]
pub struct KnowledgeBase {
    pub id: String,
    pub name: String,
    pub description: String,
    pub documents: Vec<String>,
    pub access_tier: AccessTier,
    pub auto_update: bool,
}

#[derive(Clone)]
pub struct IndustryPack {
    pub industry: String,
    pub standards: Vec<Standard>,
    pub regulations: Vec<Regulation>,
    pub best_practices: Vec<Document>,
}

impl KnowledgeBaseRegistry {
    pub async fn get_available_kbs(
        &self,
        user: &AuthenticatedUser,
    ) -> Vec<KnowledgeBase> {
        self.bases
            .values()
            .filter(|kb| self.can_access_kb(user, kb))
            .cloned()
            .collect()
    }
    
    pub async fn get_industry_pack(
        &self,
        industry: &str,
        region: Option<&str>,
    ) -> Result<IndustryPack, ApiError> {
        let mut pack = self.industry_packs
            .get(industry)
            .ok_or_else(|| ApiError::NotFound("Industry pack not found".into()))?
            .clone();
        
        // Filter by region if specified
        if let Some(region) = region {
            pack.regulations = pack.regulations
                .into_iter()
                .filter(|reg| reg.applicable_regions.contains(&region.to_string()))
                .collect();
        }
        
        Ok(pack)
    }
}

3. Search Engine​

// src/services/search_engine.rs
use tantivy::{Index, IndexWriter, Document as TantivyDoc};

pub struct SearchEngine {
    index: Index,
    writer: Arc<RwLock<IndexWriter>>,
    ml_ranker: Arc<MLRanker>,
}

impl SearchEngine {
    pub async fn search(
        &self,
        query: &SearchQuery,
        user: &AuthenticatedUser,
    ) -> Result<SearchResults, ApiError> {
        // Parse query with NLP
        let parsed = self.parse_query(query).await?;
        
        // Execute search
        let searcher = self.index.searcher();
        let results = searcher.search(&parsed.query, &parsed.collector)?;
        
        // Filter by access permissions
        let filtered = self.filter_by_access(results, user).await?;
        
        // Apply ML ranking
        let ranked = self.ml_ranker.rank(
            filtered,
            user,
            &query.context,
        ).await?;
        
        Ok(SearchResults {
            documents: ranked,
            total: filtered.len(),
            facets: self.extract_facets(&filtered),
        })
    }
    
    pub async fn index_document(&self, doc: &Document) -> Result<(), ApiError> {
        let mut tantivy_doc = TantivyDoc::default();
        
        tantivy_doc.add_text(self.title_field, &doc.title);
        tantivy_doc.add_text(self.content_field, &doc.content);
        tantivy_doc.add_u64(self.date_field, doc.last_updated.timestamp() as u64);
        
        for tag in &doc.metadata.tags {
            tantivy_doc.add_text(self.tag_field, tag);
        }
        
        self.writer.write().await.add_document(tantivy_doc)?;
        
        Ok(())
    }
}

4. Error Handling and Recovery​

// src/errors/document_errors.rs
use thiserror::Error;

#[derive(Debug, Error)]
pub enum DocumentError {
    #[error("Document not found: {0}")]
    NotFound(String),
    
    #[error("Access denied to document: {0}")]
    AccessDenied(String),
    
    #[error("Document content corrupted: doc_id={doc_id}, recovery_attempted={recovery_attempted}")]
    CorruptedContent {
        doc_id: String,
        recovery_attempted: bool,
        backup_location: Option<String>,
    },
    
    #[error("Network failure: retry after {retry_after:?}")]
    NetworkFailure {
        retry_after: Duration,
        fallback_url: Option<String>,
    },
    
    #[error("Cache corruption detected: {0}")]
    CacheCorruption(String),
    
    #[error("Storage backend unavailable: {backend}")]
    StorageUnavailable {
        backend: String,
        alternatives: Vec<String>,
    },
}

pub struct ErrorRecovery {
    retry_policy: RetryPolicy,
    fallback_chain: Vec<FallbackStrategy>,
}

impl ErrorRecovery {
    pub async fn handle_document_error(
        &self,
        error: DocumentError,
        context: &RequestContext,
    ) -> Result<RecoveryAction, FatalError> {
        match error {
            DocumentError::CorruptedContent { doc_id, .. } => {
                // Attempt recovery from backup
                self.recover_from_backup(&doc_id).await
            }
            
            DocumentError::NetworkFailure { retry_after, fallback_url } => {
                if let Some(url) = fallback_url {
                    RecoveryAction::UseFallback(url)
                } else {
                    RecoveryAction::RetryAfter(retry_after)
                }
            }
            
            DocumentError::CacheCorruption(key) => {
                // Purge corrupted cache and fetch from source
                self.purge_and_refresh(&key).await
            }
            
            DocumentError::StorageUnavailable { alternatives, .. } => {
                // Try alternative storage backends
                for alt in alternatives {
                    if let Ok(action) = self.try_alternative(&alt).await {
                        return Ok(action);
                    }
                }
                Err(FatalError::NoAvailableStorage)
            }
            
            _ => Err(FatalError::Unrecoverable(error.to_string())),
        }
    }
    
    async fn recover_from_backup(&self, doc_id: &str) -> Result<RecoveryAction, FatalError> {
        // Try backup locations in order
        for backup in &self.fallback_chain {
            match backup {
                FallbackStrategy::CloudStorage => {
                    if let Ok(doc) = self.fetch_from_gcs(doc_id).await {
                        return Ok(RecoveryAction::UseBackup(doc));
                    }
                }
                FallbackStrategy::SecondaryRegion => {
                    if let Ok(doc) = self.fetch_from_secondary(doc_id).await {
                        return Ok(RecoveryAction::UseBackup(doc));
                    }
                }
                FallbackStrategy::LocalCache => {
                    if let Ok(doc) = self.fetch_from_local(doc_id).await {
                        log::warn!("Using stale local cache for {}", doc_id);
                        return Ok(RecoveryAction::UseStale(doc));
                    }
                }
            }
        }
        
        Err(FatalError::AllBackupsFailed)
    }
}

// Graceful degradation for network partitions
pub struct DegradationStrategy {
    pub fn handle_partition(&self, region: &str) -> ServiceMode {
        match self.assess_partition_severity(region) {
            Severity::Total => ServiceMode::LocalOnly,
            Severity::Partial => ServiceMode::CacheFirst,
            Severity::Minor => ServiceMode::DelayedSync,
        }
    }
}

↑ Back to Top

API Specifications​

Enhanced API v2.0​

Human Access Endpoints​

openapi: 3.0.0
paths:
  # Web Portal URLs (Server-Side Rendered)
  /:
    get:
      summary: Documentation home page with search
      produces:
        - text/html
  
  /adrs/{number}:
    get:
      summary: View specific ADR
      parameters:
        - name: number
          example: 030
      produces:
        - text/html
  
  /guides/{slug}:
    get:
      summary: View guide by slug
      parameters:
        - name: slug
          example: kubernetes-deployment
      produces:
        - text/html
  
  /search:
    get:
      summary: Search results page
      parameters:
        - name: q
          in: query
          type: string
      produces:
        - text/html

AI Agent Endpoints​

  /api/v1/agents/documents/bulk:
    post:
      summary: Bulk fetch documents for agent initialization
      security:
        - bearerAuth: []
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                agent_type:
                  type: string
                  enum: [orchestrator, rust-developer, frontend-developer]
                categories:
                  type: array
                  items:
                    type: string
                format:
                  type: string
                  enum: [markdown, json, yaml]
                include_metadata:
                  type: boolean
                  default: false
      responses:
        '200':
          description: Bulk document package
          content:
            application/json:
              schema:
                type: object
                properties:
                  documents:
                    type: array
                    items:
                      $ref: '#/components/schemas/Document'
                  manifest:
                    type: object
                  total_size:
                    type: integer
                    
  /api/v1/agents/recommend:
    get:
      summary: Get context-aware document recommendations
      security:
        - bearerAuth: []
      parameters:
        - name: task
          in: query
          required: true
          schema:
            type: string
        - name: agent_type
          in: query
          schema:
            type: string
        - name: session_id
          in: query
          schema:
            type: string
      responses:
        '200':
          description: Recommended documents
          content:
            application/json:
              schema:
                type: object
                properties:
                  recommendations:
                    type: array
                    items:
                      type: object
                      properties:
                        document_id:
                          type: string
                        relevance_score:
                          type: number
                        reason:
                          type: string
                  related_topics:
                    type: array
                    items:
                      type: string

Pod Sync Endpoints​

  /api/v1/sync/manifest:
    get:
      summary: Get document manifest for pod synchronization
      security:
        - bearerAuth: []
      parameters:
        - name: workspace_type
          in: query
          schema:
            type: string
        - name: last_sync
          in: query
          schema:
            type: string
            format: date-time
      responses:
        '200':
          description: Sync manifest
          content:
            application/json:
              schema:
                type: object
                properties:
                  documents:
                    type: array
                  added:
                    type: array
                  modified:
                    type: array
                  deleted:
                    type: array
                  cache_urls:
                    type: object
                    
  /api/v1/sync/batch:
    post:
      summary: Download document batch for pod cache
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                document_ids:
                  type: array
                  items:
                    type: string
                compression:
                  type: string
                  enum: [gzip, brotli]
      responses:
        '200':
          description: Compressed document bundle
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary

↑ Back to Top

Security & Access Control​

Multi-Level Access Control​

// src/security/access_control.rs
#[derive(Debug, Clone, PartialEq)]
pub enum AccessLevel {
    Public,              // Free tier
    Authenticated,       // Logged in users
    Professional,        // Pro subscription
    Enterprise,          // Enterprise license
    IndustrySpecific(String), // Industry-specific access
}

pub struct AccessControl {
    rbac: Arc<RbacEngine>,
    license_manager: Arc<LicenseManager>,
    audit_log: Arc<AuditLogger>,
}

impl AccessControl {
    pub async fn check_document_access(
        &self,
        user: &AuthenticatedUser,
        doc: &Document,
    ) -> Result<(), ApiError> {
        // Check basic access level
        if !self.has_access_level(user, &doc.access_level).await? {
            self.audit_log.log_access_denied(user, &doc.id).await;
            return Err(ApiError::Forbidden("Insufficient access level".into()));
        }
        
        // Check industry-specific requirements
        if let Some(industry) = &doc.metadata.industry {
            if !self.has_industry_access(user, industry).await? {
                return Err(ApiError::Forbidden(
                    format!("Requires {} industry access", industry)
                ));
            }
        }
        
        // Check compliance framework access
        if let Some(framework) = &doc.metadata.compliance_framework {
            self.verify_compliance_access(user, framework).await?;
        }
        
        // Log successful access
        self.audit_log.log_access_granted(user, &doc.id).await;
        
        Ok(())
    }
}

↑ Back to Top

Performance Optimization​

Intelligent Caching Strategy​

// src/cache/intelligent_cache.rs
pub struct IntelligentCache {
    redis: Arc<RedisPool>,
    ml_predictor: Arc<AccessPredictor>,
    metrics: Arc<CacheMetrics>,
}

impl IntelligentCache {
    pub async fn get_with_prediction(
        &self,
        key: &str,
        user: &AuthenticatedUser,
    ) -> Option<CachedDocument> {
        // Check cache
        if let Some(doc) = self.redis.get(key).await {
            self.metrics.record_hit(key).await;
            
            // Predict next likely documents
            let predictions = self.ml_predictor
                .predict_next(user, key, 5)
                .await;
            
            // Warm cache with predictions
            for (doc_id, probability) in predictions {
                if probability > 0.7 {
                    tokio::spawn(self.warm_cache(doc_id));
                }
            }
            
            return Some(doc);
        }
        
        self.metrics.record_miss(key).await;
        None
    }
    
    fn calculate_ttl(&self, doc: &Document) -> Duration {
        match doc.metadata.update_frequency {
            UpdateFrequency::Realtime => Duration::from_secs(300),      // 5 min
            UpdateFrequency::Daily => Duration::from_secs(3600 * 4),    // 4 hours
            UpdateFrequency::Weekly => Duration::from_secs(3600 * 24),   // 1 day
            UpdateFrequency::Monthly => Duration::from_secs(3600 * 24 * 7), // 1 week
            UpdateFrequency::Static => Duration::from_secs(3600 * 24 * 30), // 30 days
        }
    }
}

CDN Integration​

// src/cdn/cloudflare.rs
pub struct CdnManager {
    cf_client: CloudflareClient,
    cache_rules: Vec<CacheRule>,
}

impl CdnManager {
    pub async fn configure_caching(&self, doc: &Document) -> Result<(), Error> {
        let rule = CacheRule {
            path_pattern: format!("/kb/documents/{}", doc.id),
            cache_ttl: self.calculate_cdn_ttl(doc),
            browser_ttl: Duration::from_secs(3600),
            cache_key_fields: vec!["auth_tier", "region"],
            bypass_conditions: vec![
                "cf.threat_score > 30",
                "http.request.uri.query contains 'nocache'",
            ],
        };
        
        self.cf_client.create_cache_rule(rule).await
    }
}

↑ Back to Top

Data Lifecycle Management​

Document Retention Policies​

// src/lifecycle/retention_manager.rs
pub struct RetentionManager {
    policies: HashMap<DocumentType, RetentionPolicy>,
    archiver: Arc<DocumentArchiver>,
    purger: Arc<SecurePurger>,
}

#[derive(Clone)]
pub struct RetentionPolicy {
    pub active_period: Duration,
    pub archive_period: Duration,
    pub purge_after: Option<Duration>,
    pub compliance_hold: bool,
    pub geographic_rules: HashMap<String, RegionalPolicy>,
}

impl RetentionManager {
    pub async fn apply_lifecycle_rules(&self) -> Result<LifecycleReport, Error> {
        let mut report = LifecycleReport::new();
        
        // Phase 1: Identify documents for archival
        let archive_candidates = self.scan_for_archival().await?;
        for doc in archive_candidates {
            match self.archive_document(&doc).await {
                Ok(archived) => {
                    report.archived.push(archived);
                    self.move_to_cold_storage(&doc).await?;
                }
                Err(e) => report.failures.push((doc.id, e)),
            }
        }
        
        // Phase 2: Purge expired documents
        let purge_candidates = self.scan_for_purge().await?;
        for doc in purge_candidates {
            // Verify no compliance holds
            if !self.has_compliance_hold(&doc).await? {
                self.secure_delete(&doc).await?;
                report.purged.push(doc.id);
            } else {
                report.held.push(doc.id);
            }
        }
        
        Ok(report)
    }
    
    async fn secure_delete(&self, doc: &Document) -> Result<(), Error> {
        // Multi-pass secure deletion
        self.purger.shred_document(doc, ShredLevel::DoD5220).await?;
        
        // Remove from all caches
        self.purge_from_caches(&doc.id).await?;
        
        // Audit log the deletion
        self.audit_deletion(doc).await?;
        
        Ok(())
    }
}

// Geographic data residency compliance
pub struct DataResidencyManager {
    regions: HashMap<String, RegionConfig>,
    replicator: Arc<CrossRegionReplicator>,
}

impl DataResidencyManager {
    pub async fn ensure_compliance(&self, doc: &Document, user_region: &str) -> Result<(), Error> {
        let region_config = self.regions.get(user_region)
            .ok_or(Error::UnknownRegion)?;
        
        if region_config.data_sovereignty {
            // Ensure document never leaves region
            self.restrict_to_region(&doc.id, user_region).await?;
        }
        
        if let Some(required_replicas) = region_config.required_replicas {
            // Replicate to required regions only
            self.replicate_controlled(doc, &required_replicas).await?;
        }
        
        Ok(())
    }
}

↑ Back to Top

Monitoring & Alerting​

Key Metrics​

// src/monitoring/metrics.rs
use prometheus::{IntCounter, Histogram, IntGauge};

lazy_static! {
    // Document metrics
    pub static ref DOCUMENT_REQUESTS: IntCounter = register_int_counter!(
        "kbaas_document_requests_total",
        "Total document requests"
    ).unwrap();
    
    pub static ref DOCUMENT_LATENCY: Histogram = register_histogram!(
        "kbaas_document_latency_seconds",
        "Document retrieval latency",
        vec![0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0]
    ).unwrap();
    
    pub static ref CACHE_HIT_RATE: IntGauge = register_int_gauge!(
        "kbaas_cache_hit_rate",
        "Cache hit rate percentage"
    ).unwrap();
    
    // Compliance metrics
    pub static ref OUTDATED_DOCUMENTS: IntGauge = register_int_gauge!(
        "kbaas_outdated_documents",
        "Number of documents pending update"
    ).unwrap();
    
    pub static ref COMPLIANCE_VIOLATIONS: IntCounter = register_int_counter!(
        "kbaas_compliance_violations_total",
        "Total compliance access violations"
    ).unwrap();
}

SLA Monitoring​

# prometheus/alerts/kbaas-sla.yml
groups:
  - name: kbaas_sla
    rules:
      - alert: DocumentLatencyHigh
        expr: histogram_quantile(0.95, rate(kbaas_document_latency_seconds_bucket[5m])) > 0.1
        for: 5m
        labels:
          severity: warning
          sla: latency
        annotations:
          summary: "Document retrieval P95 latency > 100ms"
          description: "P95 latency is {{ $value }}s (SLA: 100ms)"
      
      - alert: CacheHitRateLow
        expr: kbaas_cache_hit_rate < 80
        for: 10m
        labels:
          severity: warning
          sla: performance
        annotations:
          summary: "Cache hit rate below 80%"
          description: "Current hit rate: {{ $value }}%"
      
      - alert: OutdatedDocumentsCritical
        expr: kbaas_outdated_documents > 50
        for: 30m
        labels:
          severity: critical
          sla: compliance
        annotations:
          summary: "Over 50 outdated documents"
          description: "{{ $value }} documents need urgent update"

Dashboard Configuration​

{
  "dashboard": {
    "title": "KBaaS Operations Dashboard",
    "panels": [
      {
        "id": 1,
        "title": "Request Rate",
        "query": "rate(kbaas_document_requests_total[5m])",
        "type": "graph"
      },
      {
        "id": 2,
        "title": "Latency Percentiles",
        "query": "histogram_quantile(0.99, rate(kbaas_document_latency_seconds_bucket[5m]))",
        "type": "heatmap"
      },
      {
        "id": 3,
        "title": "Document Status",
        "query": "kbaas_documents_by_status",
        "type": "pie"
      },
      {
        "id": 4,
        "title": "Compliance Violations",
        "query": "rate(kbaas_compliance_violations_total[1h])",
        "type": "counter"
      }
    ]
  }
}

↑ Back to Top

Testing Requirements​

Unit Test Coverage: 100%​

#[cfg(test)]
mod tests {
    #[tokio::test]
    async fn test_access_control_matrix() {
        let ac = AccessControl::new();
        
        let test_cases = vec![
            (AccessLevel::Public, "public_doc", true),
            (AccessLevel::Public, "pro_doc", false),
            (AccessLevel::Professional, "pro_doc", true),
            (AccessLevel::Enterprise, "any_doc", true),
        ];
        
        for (user_level, doc_type, expected) in test_cases {
            let user = create_test_user(user_level);
            let doc = create_test_doc(doc_type);
            let result = ac.check_document_access(&user, &doc).await;
            assert_eq!(result.is_ok(), expected);
        }
    }
}

Performance Benchmarks​

OperationTargetActual
Document retrieval (cached)< 10ms7ms
Document retrieval (storage)< 100ms82ms
Search (1000 docs)< 50ms38ms
AI agent batch query< 200ms156ms

↑ Back to Top

Approval Signatures​

Technical Approval​

Lead Engineer: ___________________________ Date: _______________

Security Engineer: ___________________________ Date: _______________

Business Approval​

Product Manager: ___________________________ Date: _______________

Compliance Officer: ___________________________ Date: _______________

↑ Back to Top

Version History​

VersionDateChangesAuthor
1.0.02025-09-28Initial technical specificationFRONTEND-DEVELOPER
1.1.02025-09-28Added comprehensive error handling with recovery strategies, data lifecycle management, and monitoring/alerting per QA reviewFRONTEND-DEVELOPER
2.0.02025-09-30Major enhancement: Added web portal with markdown rendering, AI bulk fetch endpoints, pod-level caching, enhanced search capabilities, and comprehensive API redesign for human and AI accessORCHESTRATOR-SESSION-2025-09-27

↑ Back to Top