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Aliaksandr Tsviatkou
Aliaksandr Tsviatkou

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CAP Advanced Patterns — Drafts, i18n, Audit Logging & Production Readiness

#sap #sapcap #java #bestpractices

Lesson 3.4 — CAP Advanced Patterns & Production Readiness

Table of Contents

Summary: Production CAP Java applications require mastering draft handling for Fiori UIs, localization/i18n, temporal data, deployment topologies (MTA vs Helm), and performance optimization. This lesson covers these advanced patterns with practical examples and configuration.

1. Draft Handling

What is Draft?

Draft enables Fiori's "edit session" pattern: a user opens an entity for editing, makes changes over multiple requests, then saves or discards. Changes are stored in a draft table until explicitly activated.

User clicks "Edit"     User modifies fields     User clicks "Save"
       │                      │                        │
       ▼                      ▼                        ▼
┌──────────────┐    ┌──────────────┐    ┌──────────────────────┐
│ DRAFT_NEW    │    │ Draft table  │    │ Copy draft → active  │
│ creates draft│───→│ updated      │───→│ Delete draft          │
│ copy         │    │ (multiple    │    │ Return active entity  │
│              │    │  requests)   │    │                       │
└──────────────┘    └──────────────┘    └──────────────────────┘
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CDS Annotation 

service AdminService {
    @odata.draft.enabled
    entity Books as projection on db.Books;
}
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This auto-generates:

  • DRAFT_Books table for storing in-progress edits
  • Draft-specific OData actions: draftEdit, draftActivate, draftPrepare

Draft Handler in Java 

@Component
@ServiceName(AdminService_.CDS_NAME)
public class AdminServiceHandler implements EventHandler {

    // Runs when user clicks "Save" (draft → active)
    @Before(event = DraftService.EVENT_DRAFT_SAVE, entity = Books_.CDS_NAME)
    public void validateOnSave(DraftSaveEventContext context) {
        CqnSelect draftQuery = Select.from(Books_.class)
            .where(b -> b.IsActiveEntity().eq(false)  // draft version
                .and(b.ID().eq(context.getCqn().entries().get(0).get("ID"))));

        Books draft = db.run(draftQuery).single(Books.class);

        if (draft.getTitle() == null || draft.getTitle().isBlank()) {
            throw new ServiceException(ErrorStatuses.BAD_REQUEST,
                "Title is required before saving");
        }
        if (draft.getPrice() == null || draft.getPrice().compareTo(BigDecimal.ZERO) <= 0) {
            throw new ServiceException(ErrorStatuses.BAD_REQUEST,
                "Price must be positive");
        }
    }

    // Runs during draft preparation (field validation while editing)
    @Before(event = DraftService.EVENT_DRAFT_PREPARE, entity = Books_.CDS_NAME)
    public void prepareWarnings(DraftPrepareEventContext context) {
        // Side-effect free validation — add warnings but don't reject
        Messages messages = context.getMessages();
        // Add warnings that show in Fiori UI but don't block save
    }
}
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Draft Timeout 

cds:
  drafts:
    cancellation-timeout: 15d  # Auto-delete drafts after 15 days
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2. Localization (i18n)

CDS Text Bundles 

// db/schema.cds
entity Books {
    key ID : UUID;
    title  : localized String(200);  // enables translations
    descr  : localized String(2000);
}
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The localized keyword generates a Books.texts table:

-- Auto-generated
CREATE TABLE my_bookshop_Books_texts (
    locale VARCHAR(14),
    ID UUID,
    title VARCHAR(200),
    descr VARCHAR(2000),
    PRIMARY KEY (locale, ID)
);
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i18n Properties Files 

# srv/src/main/resources/i18n/messages.properties (default/English)
book_not_found=Book with ID {0} not found
order_submitted=Order {0} submitted successfully
insufficient_stock=Not enough stock for book {0}. Available: {1}

# srv/src/main/resources/i18n/messages_de.properties (German)
book_not_found=Buch mit ID {0} nicht gefunden
order_submitted=Bestellung {0} erfolgreich eingereicht
insufficient_stock=Nicht genug Bestand für Buch {0}. Verfügbar: {1}
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Using Localized Messages in Handlers 

@On(event = "submitOrder")
public void onSubmitOrder(SubmitOrderContext context) {
    Books book = db.run(Select.from(Books_.class).byId(context.getBook()))
        .first(Books.class)
        .orElseThrow(() -> new ServiceException(ErrorStatuses.NOT_FOUND,
            MessageKeys.BOOK_NOT_FOUND, context.getBook()));

    if (book.getStock() < context.getQuantity()) {
        throw new ServiceException(ErrorStatuses.CONFLICT,
            MessageKeys.INSUFFICIENT_STOCK, book.getTitle(), book.getStock());
    }
    // ... process order
}
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3. Temporal Data & Audit Logging

Managed Aspects (Auto-filled Fields) 

using { managed, cuid } from '@sap/cds/common';

entity Orders : cuid, managed {
    // cuid provides: key ID : UUID;
    // managed provides: createdAt, createdBy, modifiedAt, modifiedBy
    orderNo    : String(20);
    totalAmount: Decimal(15,2);
    status     : String(20);
}
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CAP automatically fills these fields:

  • createdAt / modifiedAt — server timestamp
  • createdBy / modifiedBy — from JWT user ID

Audit Logging with @changelog 

@changelog: [title, price, stock]
entity Books : managed {
    key ID : UUID;
    title  : String(200);
    price  : Decimal(10,2);
    stock  : Integer;
}
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CAP generates change log entries for annotated fields, recording old value, new value, user, and timestamp.

Soft Delete Pattern 

entity Orders : managed {
    key ID      : UUID;
    // ... fields ...
    deletedAt   : Timestamp;
    deletedBy   : String(255);
}

// Service shows only non-deleted
service OrderService {
    entity Orders as projection on db.Orders
        where deletedAt is null;
}
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@On(event = CqnService.EVENT_DELETE, entity = Orders_.CDS_NAME)
public void softDelete(CdsDeleteEventContext context) {
    // Instead of physical delete, set deleted fields
    String orderId = extractId(context);
    CqnUpdate update = Update.entity(Orders_.class)
        .data("deletedAt", Instant.now())
        .data("deletedBy", context.getUserInfo().getName())
        .byId(orderId);
    db.run(update);
    context.setResult(List.of(Map.of("ID", orderId)));
    context.setCompleted(); // prevent generic delete handler
}
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4. Deployment Topologies

MTA (Cloud Foundry) 

# mta.yaml
_schema-version: "3.1"
ID: my-cap-app
version: 1.0.0

modules:
  - name: my-cap-srv
    type: java
    path: srv
    parameters:
      memory: 1024M
      buildpack: sap_java_buildpack_jakarta
    properties:
      SPRING_PROFILES_ACTIVE: cloud
      JBP_CONFIG_COMPONENTS: '{jres: ["com.sap.xs.java.buildpack.jre.SAPMachineJRE"]}'
    requires:
      - name: my-xsuaa
      - name: my-hana
      - name: my-destination

  - name: my-cap-db-deployer
    type: hdb
    path: gen/db
    requires:
      - name: my-hana

resources:
  - name: my-xsuaa
    type: org.cloudfoundry.managed-service
    parameters:
      service: xsuaa
      service-plan: application
      path: ./xs-security.json

  - name: my-hana
    type: com.sap.xs.hdi-container
    parameters:
      service: hana
      service-plan: hdi-shared

  - name: my-destination
    type: org.cloudfoundry.managed-service
    parameters:
      service: destination
      service-plan: lite
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Helm (Kyma) 

my-cap-helm/
├── Chart.yaml
├── values.yaml
├── templates/
│   ├── deployment-srv.yaml
│   ├── deployment-sidecar.yaml    # MTX sidecar (if multi-tenant)
│   ├── service.yaml
│   ├── apirule.yaml
│   ├── service-instance-xsuaa.yaml
│   ├── service-instance-hana.yaml
│   ├── service-binding-xsuaa.yaml
│   ├── service-binding-hana.yaml
│   └── job-db-deploy.yaml          # HDI deployer as K8s Job
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CF vs Kyma Deployment Comparison

Aspect Cloud Foundry (MTA) Kyma (Helm)
Packaging MTA archive (.mtar) Docker image + Helm chart
DB deployment hdb module (auto) K8s Job with HDI deployer image
Service binding MTA requires BTP Operator CRDs
Scaling CF instances parameter K8s HPA
Routing CF routes + approuter APIRule + Istio
Sidecar (MTX) Separate CF app Separate K8s Deployment

5. Performance Optimization

Query Optimization 

// BAD: fetches all columns, all rows
CqnSelect bad = Select.from(Books_.class);

// GOOD: project only needed columns, filter, limit
CqnSelect good = Select.from(Books_.class)
    .columns(b -> b.ID(), b -> b.title(), b -> b.price())
    .where(b -> b.stock().gt(0))
    .orderBy(b -> b.title().asc())
    .limit(50);
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Batch Operations 

// BAD: N individual inserts
for (Map<String, Object> book : books) {
    db.run(Insert.into(Books_.class).entry(book));
}

// GOOD: single batch insert
db.run(Insert.into(Books_.class).entries(books));
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Connection Pool Tuning 

spring:
  datasource:
    hikari:
      maximum-pool-size: 10
      minimum-idle: 2
      connection-timeout: 30000
      idle-timeout: 600000
      max-lifetime: 1800000
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Caching with Spring Cache 

@Cacheable(value = "genres", key = "'all'")
public List<Genres> getAllGenres() {
    return db.run(Select.from(Genres_.class)).listOf(Genres.class);
}

@CacheEvict(value = "genres", allEntries = true)
public void onGenreChanged() {
    // Called when genres are modified
}
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Top 5 Pitfalls

  1. Not enabling draft for Fiori edit scenarios. Without @odata.draft.enabled, Fiori Elements uses "direct edit" mode which doesn't support multi-step editing or concurrent user detection.
  2. Ignoring the localized keyword. Adding translations retroactively requires database migration. Plan for i18n from the start using localized on user-facing String fields.
  3. Deploying without a startup probe. CAP Java apps with CDS compilation at startup can take 30-60s. Without a startup probe, Kubernetes kills the pod before it's ready.
  4. Not batching database operations. Individual inserts/updates in a loop are orders of magnitude slower than batch operations. Always use .entries(list).
  5. MTA descriptor out of sync with actual services. Forgetting to add a new service to mta.yaml causes deployment failures. Keep the MTA descriptor as the definitive deployment manifest.

What to Learn Next

  • Lesson 3.5: CAP Fiori Elements — UI annotations for automatic UI generation
  • Lesson 1.4: Multi-Tenancy — MTX sidecar deployment patterns
  • Lesson 4.1: CI/CD — automating MTA builds and Helm deployments
  • Lesson 4.2: Observability — monitoring CAP applications in production

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