Table of Contents

Webhooks fix the timing problem: when something meaningful happens, the source system immediately sends an HTTPS POST with structured JSON to an endpoint you control. That’s the same pattern used by Stripe webhooks, which push events the moment they occur instead of making you poll for updates. This aligns with event-driven integration principles: “tell me when it changes,” not “ask me every few minutes.”

Integrate.io turns that approach into configuration instead of code. You stand up a managed HTTPS endpoint, map fields visually, and deliver IBM i–sourced changes to downstream systems (CRM, ecommerce, warehouses, analytics) in near real time. Where you need historical context or full backfills, you add scheduled/API pulls in the same platform. The result is fast, reliable, and observable pipelines—without hand-rolling listener services, retry/backoff logic, queues, and monitors. 

Key Takeaways

  • Webhook-first + scheduled pulls: Blend push-style events for fresh changes with scheduled/API pulls for history and backfill. This keeps systems current while minimizing unnecessary calls.

  • Managed HTTPS endpoint: Integrate.io provides a listener with optional HMAC/signature verification, IP allowlisting, and durable queuing—no custom microservice to build or maintain. 

  • Visual transformation at scale: Use 200+ low-code transformations to normalize IBM i data (packed/zoned decimals, EBCDIC, date formats) without writing custom parsers. 

  • CDC and micro-batch orchestration: Pair change detection/CDC with short-interval micro-batches (often ~minute-level depending on configuration and plan) so downstream apps reflect what just happened, not what happened last night. Learn about CDC.

  • Enterprise security: Encryption in transit and at rest, role-based access control, audit logging, and documented SOC 2 Type II controls in Integrate.io’s security posture.

  • Reliability patterns built-in: Durable queues, idempotency, and exponential-backoff retries help prevent silent data loss and duplicate writes.

  • End-to-end visibility: Throughput, latency, error rates, schema drift, and anomaly alerts via Data Observability.

What Is a Webhook (and Why It Helps on IBM i)

A webhook is a simple contract: when a defined event occurs, the source immediately sends an HTTPS POST to your endpoint with a structured payload (usually JSON). That’s different from polling, where a consumer asks every few minutes if anything changed. In a webhook model, events drive the integration, which dramatically reduces latency and wasted calls. This is the same “tell me when it changes” pattern used by modern platforms (for example, see Stripe webhooks for a canonical implementation).

On IBM i, you can emulate native webhooks by detecting database changes (via journal/CDC where available, or by querying last_update_ts/sequence fields) and then pushing those changes out immediately. With Integrate.io, that looks like:

  1. Detect: Identify inserts/updates in Db2 for i tables you care about (orders, inventory, customers, invoices).

  2. Package: Map the key fields and related context you need into a compact JSON payload.

  3. Deliver: Send the payload to a managed HTTPS endpoint or directly into a destination API (CRM, marketing, analytics).

  4. Acknowledge & retry: The receiver returns 2xx on success; transient failures trigger retries with backoff and land in a DLQ if needed.

Because it’s event-driven, downstream systems react as changes occur, not hours later.

Webhook vs API (and Why You Usually Need Both)

Push (webhook-style)

  • Sends only when something changed → low latency, low noise.

  • Ideal for: hot operational signals (new order, order approved, inventory change, status transitions), audience/segment updates, and real-time notifications.

Pull (API / scheduled extracts)

  • Consumer asks for data → great for history and reconciliation.

  • Ideal for: backfills (“all orders from last quarter”), slowly changing reference data (catalogs), audits, investigations.

The winning pattern: use push for fresh, high-value events and pull for history and reconciliation. Integrate.io supports both in a single UI, so Marketing Ops, RevOps, and Data teams don’t need separate stacks.

Getting IBM i Ready (Connectivity, Security, and Naming)

Before you stream events, align on connectivity and controls:

  • Platform naming: Use “IBM i (formerly AS/400)” at first mention, then “IBM i” going forward. This is accurate and SEO-friendly for readers who still search “AS/400.”

  • Connectivity & ports: Work with admins to confirm service entries. Common defaults you’ll see in practice are:

  • TLS & cipher policy: Enforce modern TLS (1.2+) end-to-end for webhook traffic. For reference guidance, see NIST SP 800-52r2 (TLS 1.2+ recommendations).

  • Authentication & authorization: Use shared secrets or HMAC-style signature verification on inbound calls, IP allowlisting for the listener, and role-based access controls for pipeline changes.

  • PII/regulated data: Apply field-level masking/hashing and align retention with policy. Integrate.io documents encryption at rest/in transit and SOC 2 Type II in its security.

Step-by-Step: IBM i Change → Webhook → Destination in Integrate.io

1) Generate a Managed HTTPS Endpoint

Create a listener in Integrate.io’s webhook integration. You can require a secret/signature header and restrict inbound IPs. This removes the need to host or patch a public web service just to receive incoming events.

2) Point Your IBM i–Sourced Changes at That Endpoint

Configure a pipeline that detects changes in Db2 for i (journal/CDC where supported, or incremental queries keyed on timestamp/sequence). When a change is captured, the pipeline immediately emits a JSON payload to the managed HTTPS endpoint or directly to a downstream API (for example, Salesforce).

Tip: Start with the smallest set of fields that unambiguously identifies the record and the change (IDs, type, status/timestamps), then enrich as needed. Keeping the payload lean avoids downstream bottlenecks.

3) Map & Transform (No Custom Parsers Required)

In the visual mapper, connect inbound fields to destination schema—Salesforce, Shopify, Zendesk, or a warehouse. With ETL transformations you can:

  • Convert packed/zoned decimals to standard numerics (IBM Docs: DECIMAL/NUMERIC data type and Zoned decimal data type).

  • Normalize dates (for example, CYYMMDD → ISO 8601).

  • Handle EBCDIC → UTF-8 conversion for text fields.

  • Flatten nested structures and arrays.

  • Add calculated fields (line totals, currency conversions, segments).

  • Maintain a raw_payload column for audit/debug while writing clean, modeled fields to destinations.

4) Deliver & Monitor

Choose delivery mode based on impact and cost:

  • Event-by-event for critical workflows (order approvals, cancellations).

  • Micro-batch every 30–60 seconds (often a practical default depending on configuration and plan) to improve API efficiency while keeping latency low.

  • Scheduled hourly/daily for slower-moving data or reconciliation.

Reliability patterns—durable queues, idempotency (see Stripe’s idempotent request pattern), and exponential-backoff retries per AWS prescriptive guidance—are baked in. You get a central view of throughput, latency, errors, and drift with Data Observability, including alerting to Slack/email/PagerDuty.

Common IBM i Webhook Use Cases

Order-to-Fulfillment Automation

Signal: Sales order created/approved.
Action: Push an event to logistics and customer-facing systems (shipments, order tracking, invoices).
Why it matters: Customers see status changes immediately; warehouse/3PL workflows start on time.

Inventory Synchronization Across Channels

Signal: On-hand quantity changes in IBM i.
Action: Update ecommerce/POS quickly; trigger back-in-stock notifications.
Why it matters: Prevent overselling and reduce customer service escalations.

Customer 360 for Marketing & Success

Signal: Account tier/contract status/renewal date updated.
Action: Enrich CRM/marketing profiles, start nurture or renewal plays, adjust entitlements in downstream apps.
Why it matters: Sales, CS, and Marketing operate on the same truth, not last week’s export.

Finance Visibility & Close Acceleration

Signal: Transaction posted or paid.
Action: Stream to a warehouse (Snowflake/BigQuery) for live dashboards; reconcile via scheduled pulls.
Why it matters: FP&A and RevOps don’t wait for quarter-end to see revenue reality.

Advanced Configuration

High-Volume Streams

As volumes climb, keep pipelines responsive and cost-efficient:

  • Intelligent batching to avoid API storms (aggregate many small changes into compact payloads).

  • Adaptive throttling when you approach a destination’s rate limits; prioritize revenue-critical events first.

  • Priority queues so purchases, cancellations, and SLA-sensitive changes outrank low-signal events.

  • Parallelism across independent flows (inventory vs. support updates) without sacrificing ordering within a single stream.

Security & Compliance

Integrate.io implements enterprise-grade controls documented in its security:

  • Encryption in transit (TLS 1.2+) and at rest.

  • Role-based access control and fine-grained permissions.

  • Audit logging for change history and access trails.

  • Support for customer compliance programs (for example, GDPR/CCPA; HIPAA support may require a BAA—discuss your needs with the team).

When handling sensitive fields, apply field-level protection (masking, hashing) at transform time so downstream targets only receive what policy allows.

Reliability Patterns (So You Don’t Lose Data)

  • Exponential-backoff retries for transient failures (avoid hammering an unhealthy endpoint).

  • Idempotency to prevent double-writes when a sender retries the same event.

  • Dead-letter queues to hold and inspect events that exceeded retry limits—then replay after you fix the root cause.

Performance Tips for IBM i Sources

  • Use indexed access paths and incremental windows (timestamps/sequence numbers) for change detection.

  • Keep payloads minimal; fetch heavier context on the receiving side if needed.

  • Cache slow-changing reference data (product catalog, region maps) in the pipeline to reduce repeated lookups.

  • If you use a warehouse as a hub, write both raw and modeled layers; the raw layer helps audit and replay.

Destination Patterns (Examples)

  • CRM (Salesforce)
    Push account/contact/order changes so Sales sees live status. Pair with pulls for historical backfill.
    – Learn how Integrate.io connects to Salesforce: Salesforce integration

  • Ecommerce (Shopify)
    Stream inventory updates and order confirmations; sync fulfillment and returns back to IBM i.
    – Explore Shopify flows: Shopify integration

  • Support (Zendesk)
    Emit entitlement/tier changes so support agents see accurate SLAs.
    – See Zendesk options: Zendesk integration

  • Analytics (Snowflake/BigQuery)
    Land events in your warehouse for live dashboards and modeling; reconcile with scheduled pulls.
    – Snowflake: Snowflake integration
    – BigQuery: BigQuery integration

  • Team Notifications (Slack)
    Send high-priority status changes (for example, order holds, low stock) to channels for rapid response.
    – Slack: Slack integration

Observability & Troubleshooting

What to Watch

Use Data Observability to track:

  • Throughput (events/min, by pipeline).

  • Latency (event time → destination write time).

  • Success/retry/DLQ ratios (alerts when success dips or retries spike).

  • Schema drift (new/renamed fields from IBM i or a downstream app).

  • Backlog depth (how many events are queued right now).

Route alerts to Slack, email, or PagerDuty so engineering and ops teams get early warnings—before downstream dashboards go stale or audiences drift.

Common Issues & Fast Fixes

  • Expired credentials / changed permissions → refresh secrets and re-test connections; enable alerts on auth failures.

  • Schema mismatches (for example, field type changed on IBM i) → adjust mappings; keep a raw payload column to minimize breakage.

  • Duplicate emissions (sender retried) → verify idempotency keys (primary key + change sequence or timestamp) and de-dupe step.

  • Destination rate limiting → turn on adaptive throttling; shift to micro-batches; prioritize critical events.

  • Intermittent network issues → rely on backoff + DLQ; replay after root cause is resolved.

Frequently Asked Questions

Do IBM i systems emit webhooks natively?

Not usually. You simulate a webhook by detecting changes (CDC or incremental queries) and pushing a JSON payload to a managed endpoint. Integrate.io supplies the listener, mapping, delivery, retries, and monitoring—so you don’t have to host or secure your own public service.

Which ports should we open for secure database access from IBM i?

Environments vary, but common TLS ports are 9471 (secure database host server) and 448 (secure DRDA). Non-TLS counterparts are 8471 and 446. IBM lists these ports in its docs here under “Ports in the list.”

How do we avoid duplicate updates when senders retry?

Use idempotency—combine a stable primary key with a change sequence or timestamp. The pipeline drops repeats and writes only the first valid occurrence. You can also hash a composite key (for example, table:id:updated_at) to detect duplicates across sources.

Can we stay “real time” without exploding API costs?

Yes. Push hot signals and micro-batch them every 30–60 seconds where acceptable, and use scheduled pulls for history. This blend keeps latency low, respects API limits, and reduces per-call overhead.

What about security and compliance?

All traffic runs over HTTPS (TLS 1.2+ recommended), data is encrypted at rest, and access is governed by RBAC and audit logs. Integrate.io documents SOC 2 Type II and supports customer compliance programs; discuss BAA needs for HIPAA workloads. You can further restrict access with IP allowlisting and per-environment credentials.

What happens if a destination goes down mid-campaign?

Events queue durably and retries use exponential backoff; after a threshold they move to a DLQ for inspection/replay. When the destination recovers, delivery resumes in order without data loss. Alerting notifies your team so you can remediate quickly while the queue buffers traffic.