### Description

This applies to the following APIs:
- [x] open anomaly detection
- [x] start datafeed
- [x] start data frame analytics job
- [x] start trained model deployment

Currently, if the operation takes longer than the configured `timeout`, the response status code is `500`.

With Kibana in mind, a `4xx` response would be more suitable as it will lead to showing more useful information to the user about why the request failed.

Looking at [RFC 9110](https://www.rfc-editor.org/rfc/rfc9110.html#name-408-request-timeout), it seems the most appropriate `4xx` code would be `408 Request Timeout`, even though the RFC describes a different situation. 

The alternative, `504 Gateway Timeout`, would be more appropriate for this situation but it wouldn't improve the user experience in Kibana.
x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/action/TransportStartDatafeedAction.java
ActionListener<Job.Builder> jobListener = ActionListener.wrap(jobBuilder -> {
            try {
                Job job = jobBuilder.build();
                validate(job, datafeedConfigHolder.get(), tasks, xContentRegistry);
                auditDeprecations(datafeedConfigHolder.get(), job, auditor, xContentRegistry);
                createDataExtractor.accept(job);
            } catch (Exception e) {
                listener.onFailure(e);
            }
        }, listener::onFailure);
        ActionListener<DatafeedConfig.Builder> datafeedListener = ActionListener.wrap(datafeedBuilder -> {
            try {
                DatafeedConfig datafeedConfig = datafeedBuilder.build();
                params.setDatafeedIndices(datafeedConfig.getIndices());
                params.setJobId(datafeedConfig.getJobId());
                params.setIndicesOptions(datafeedConfig.getIndicesOptions());
                datafeedConfigHolder.set(datafeedConfig);
                if (datafeedConfig.hasCompositeAgg(xContentRegistry)) {
                    if (state.nodes()
                        .mastersFirstStream()
                        .filter(MachineLearning::isMlNode)
                        .map(DiscoveryNode::getVersion)
                        .anyMatch(COMPOSITE_AGG_SUPPORT::after)) {
                        listener.onFailure(
                            ExceptionsHelper.badRequestException(
                                "cannot start datafeed [{}] as [{}] requires all machine learning nodes to be at least version [{}]",
                                datafeedConfig.getId(),
                                "composite aggs",
                                COMPOSITE_AGG_SUPPORT
                            )