Best examples of SOAP API logging and monitoring examples in 2025

Real-world examples of SOAP API logging and monitoring examples

Instead of starting with definitions, let’s jump straight into how teams actually log and monitor SOAP in production. These examples of SOAP API logging and monitoring examples come from typical enterprise stacks in finance, healthcare, and government integrations.

You’ll see a pattern: the best examples combine three layers:

• Transport logging (HTTP/S)
• SOAP envelope logging (headers and bodies)
• Higher-level monitoring (latency, error rates, SLAs, security)

The details change by platform, but the principles stay consistent.

Java/Apache CXF example of SOAP request/response logging

A very common example of SOAP API logging and monitoring examples is an Apache CXF service that needs full request/response logging for troubleshooting, but with sensitive fields masked.

A typical CXF configuration in cxf-beans.xml might use the built-in logging interceptors:

<bean id="logIn" class="org.apache.cxf.ext.logging.LoggingInInterceptor">
    <property name="prettyLogging" value="true" />
    <property name="limit" value="65536" />
</bean>

<bean id="logOut" class="org.apache.cxf.ext.logging.LoggingOutInterceptor">
    <property name="prettyLogging" value="true" />
    <property name="limit" value="65536" />
</bean>

<jaxws:endpoint id="paymentService" implementor="#paymentServiceImpl"
                address="/payments">
    <jaxws:inInterceptors>
        <ref bean="logIn" />
    </jaxws:inInterceptors>
    <jaxws:outInterceptors>
        <ref bean="logOut" />
    </jaxws:outInterceptors>
</jaxws:endpoint>

Teams then extend LoggingInInterceptor to mask elements like <cardNumber> or <ssn> before logs are written. This gives you readable, pretty-printed XML in your centralized log platform (Splunk, ELK, Datadog) while still meeting PCI-DSS or HIPAA expectations.

Monitoring is layered on top using metrics from the servlet container or Spring Boot Actuator: response time histograms, 5xx rates, and SLA alerts for specific SOAP actions (for example, ProcessPayment). This is one of the best examples of SOAP API logging and monitoring examples because it shows how to combine low-level XML logging with higher-level operational metrics.

Spring Web Services interceptor example of SOAP logging

Another strong example of SOAP API logging and monitoring examples comes from Spring Web Services, where EndpointInterceptors provide hooks for logging and tracing.

A custom interceptor might:

• Extract a correlation ID from a SOAP header (or generate one)
• Log the correlation ID, operation name, and client IP
• Attach the correlation ID to MDC (Mapped Diagnostic Context) so every log line in that thread includes it

Sketch of the idea:

public class CorrelationLoggingInterceptor implements EndpointInterceptor {

    @Override
    public boolean handleRequest(MessageContext messageContext, Object endpoint) {
        SoapMessage soapMessage = (SoapMessage) messageContext.getRequest();
        String correlationId = extractOrCreateCorrelationId(soapMessage);
        MDC.put("correlationId", correlationId);
        logger.info("Incoming SOAP request: op={} corrId={}",
                    getOperationName(messageContext), correlationId);
        return true;
    }

    @Override
    public boolean handleResponse(MessageContext messageContext, Object endpoint) {
        logger.info("Outgoing SOAP response: op={} corrId={}",
                    getOperationName(messageContext), MDC.get("correlationId"));
        MDC.clear();
        return true;
    }
}

This example of logging gives you end-to-end traceability across microservices. When a SOAP call fans out into REST downstreams, you can propagate the same correlation ID via HTTP headers and stitch everything together in your APM tool.

.NET / WCF message inspector example

On the Microsoft side, a classic example of SOAP API logging and monitoring examples uses WCF message inspectors. You implement IDispatchMessageInspector to capture raw SOAP envelopes, then push summaries to Application Insights or another telemetry sink.

Key patterns teams use:

• Log the full SOAP envelope only for failed or timed-out requests
• For successful calls, log only metadata: operation name, duration, client, and a hashed user identifier
• Emit custom metrics per operation (for example, ClaimsService.SubmitClaim.LatencyMs)

A WCF behavior configuration attaches the inspector to all endpoints, making it easy to standardize logging across dozens of SOAP services.

Monitoring then focuses on Application Insights queries and dashboards:

• Percent of requests over 2 seconds by operation
• Top 10 client applications by error rate
• Trend of FaultException occurrences by fault code

This is one of the best examples because it shows how SOAP-era services can still plug into modern cloud monitoring without rewriting the whole stack.

API gateway and proxy-based logging examples

Many organizations now terminate SOAP at an API gateway or proxy, then forward to internal services. In these examples of SOAP API logging and monitoring examples, the gateway becomes the main observability layer.

Typical gateway behaviors:

• Log request/response sizes, status codes, and latency per route
• Parse SOAPAction headers to tag logs and metrics with operation names
• Enforce rate limits and log when clients are throttled
• Mask or drop sensitive XML elements at the edge

For instance, an NGINX or Kong gateway can log:

• soap_operation (from SOAPAction)
• client_id
• request_time_ms
• response_code

Those fields feed into dashboards that show which SOAP operations are slow, which partners are overusing the API, and where error spikes begin.

Because the gateway sits in front of multiple SOAP services, this pattern gives you cross-service visibility without modifying every backend. It’s a pragmatic example of SOAP API logging and monitoring examples that works well during long modernization programs.

Healthcare and regulated data: logging examples with redaction

Healthcare integrations are full of SOAP, especially around HL7v3 and older EHR interfaces. Here, logging and monitoring must respect privacy regulations. You can see this tension in real examples from hospital integration engines and payer systems.

Common techniques:

• Redact PHI fields like patient name, date of birth, and diagnosis codes
• Hash identifiers (MRN, member ID) so you can correlate events without storing raw IDs
• Log only message metadata for certain operations (for example, eligibility checks)

While the technical details vary, many teams align their logging policies with guidance from organizations like the U.S. Office for Civil Rights and research from academic centers such as NIH and Harvard. The point is not to copy health content from those sites, but to align with their privacy-aware mindset.

From an observability standpoint, the monitoring layer still tracks:

• Error codes from SOAP faults
• Latency percentiles by operation
• Volume trends by facility or partner

The best examples of SOAP API logging and monitoring examples in healthcare show that you can be highly observable without spraying PHI into your logs.

OpenTelemetry and distributed tracing for SOAP in 2024–2025

A newer wave of examples of SOAP API logging and monitoring examples involves OpenTelemetry. Even if your core service is a 10‑year‑old SOAP endpoint, you can still emit traces and metrics that play nicely with modern observability stacks.

Typical pattern in 2024–2025:

• Wrap the SOAP client or server with middleware that starts an OpenTelemetry span
• Add attributes like soap.operation, soap.action, soap.fault_code, soap.client_app
• Export traces to a backend like Jaeger, Tempo, or a commercial APM

For Java, OpenTelemetry instrumentation can hook into HTTP clients and servlet containers, so you get spans for inbound and outbound SOAP calls without rewriting the business logic. For .NET, similar instrumentation exists for HttpClient and WCF.

The payoff is big:

• You can see a SOAP request triggering downstream REST calls, database queries, and message-queue operations in a single trace
• You can correlate logs, metrics, and traces using the same trace ID

These real examples show that SOAP doesn’t have to be an observability dead end. It can live inside the same monitoring fabric as your Kubernetes workloads and serverless functions.

Security-focused examples: SOAP logging for threat detection

Security teams increasingly use SOAP logs as a data source for threat detection. In these examples of SOAP API logging and monitoring examples, the emphasis is on pattern analysis rather than just debugging.

Typical signals captured:

• Repeated failed authentication attempts from a single IP
• Unusual SOAPAction values or malformed XML that may indicate probing
• Sudden spikes in high-value operations (for example, fund transfers or policy changes)

Logs are shipped to a SIEM where detection rules look for anomalies. For example:

• More than 10 failed logins in 5 minutes from the same client
• Requests containing known exploit signatures in the SOAP body

Here, the monitoring layer includes:

• Security dashboards
• Alerting on suspicious traffic patterns
• Correlation with firewall and VPN logs

These are some of the best examples of SOAP API logging and monitoring examples because they show how operational logs double as security telemetry.

Performance tuning examples using SOAP metrics

Another practical example of SOAP API logging and monitoring examples is performance tuning. Teams instrument SOAP endpoints with metrics such as:

• Average and p95 latency per operation
• Request size and response size distributions
• Backend dependency timings (database, downstream services)

By correlating logs and metrics, engineers can answer questions like:

• Are large SOAP requests consistently slower?
• Did a database schema change increase latency for SubmitOrder?
• Are specific partners sending malformed or oversized payloads?

A common pattern:

• Log request size and operation name
• Emit metrics for latency and error rates
• Use your observability platform to build a heat map of size vs. latency

That heat map often reveals that a small percentage of very large SOAP messages dominate processing time. Teams then negotiate payload limits or pagination with partners, backed by hard data from their logging and monitoring setup.

Trends for SOAP logging and monitoring in 2024–2025

Looking at real examples across industries, a few trends stand out:

• Centralized log platforms are non-negotiable: Shipping SOAP logs to a central place (ELK, Splunk, Datadog, etc.) is now table stakes. Local log files on app servers are a liability.
• Privacy and minimization: Redaction and field-level masking are standard. Teams are aligning with privacy practices similar in spirit to those discussed by institutions like Mayo Clinic and WebMD when handling sensitive health-related data.
• Telemetry unification: SOAP services are being wired into the same tracing and metrics systems used for REST and event-driven workloads.
• Policy-as-code for logging: Instead of ad hoc decisions, teams define reusable logging policies (what to log, what to mask, retention windows) and enforce them via code or gateway configuration.

The best examples of SOAP API logging and monitoring examples today are less about fancy XML tricks and more about fitting SOAP into a disciplined, organization-wide observability strategy.

FAQ: examples of SOAP API logging and monitoring examples

Q1: What are some common examples of SOAP API logs you should always capture?
At minimum, capture timestamp, client identifier, operation name (via SOAPAction or WSDL operation), HTTP status, SOAP fault code (if any), latency, and a correlation ID. Many teams also log request and response sizes and a redacted snapshot of the SOAP envelope for failed requests.

Q2: Can you give an example of sensitive data that should never appear in SOAP logs?
Yes. Full credit card numbers, CVV codes, Social Security numbers, unmasked patient identifiers, and authentication secrets (passwords, tokens, API keys) should not be logged. The safer examples of SOAP API logging and monitoring examples either mask these values (for example, last 4 digits only) or drop the fields entirely.

Q3: How do you monitor SOAP APIs if you can’t log the full XML?
You focus on metadata and metrics: operation names, error codes, latency, size, and client IDs. Many real examples use structured logs (JSON) with these fields plus a correlation ID, combined with metrics in a time-series database. This gives you visibility without exposing sensitive payloads.

Q4: What is a good example of integrating SOAP logging with modern APM tools?
A common example is a Java SOAP service using Apache CXF, with logs sent to ELK and traces exported via OpenTelemetry to a backend like Jaeger or a commercial APM. Each SOAP request becomes a trace span with attributes for operation, client, and fault code, and the correlation ID ties that span to log entries.

Q5: Are there examples where SOAP logging hurt performance, and how was that fixed?
Yes. Teams that initially logged full pretty-printed XML for every request often saw CPU and I/O overhead spike. The fix in these examples of SOAP API logging and monitoring examples was to limit body size, log full envelopes only for failures or sampling (for example, 1% of successful calls), and turn off pretty-printing in high-throughput paths.

If you treat these examples of SOAP API logging and monitoring examples as building blocks rather than rigid recipes, you can adapt them to almost any legacy stack and still meet 2025 expectations for observability, security, and compliance.