Custom Metrics (API)

Collect any business or platform signal as custom metrics and visualise it alongside your Host/Kubernetes/Service telemetry in Middleware.

You can send metrics in two ways:

1. HTTP (OTLP/JSON): Simple curl/scripted pushes to /v1/metrics
2. OpenTelemetry SDKs: Instrument your app and export to Middleware over OTLP

Option A: Send custom data with cURL (OTLP/JSON)

POST your payload to OTLP Metrics HTTP endpoint:

1curl -X POST "https://<MW_UID>.middleware.io:443/v1/metrics" \
2  -H "Accept: application/json" \
3  -H "Content-Type: application/json" \
4  -H "Authorization: <MW_API_KEY>" \
5  -d @- << 'EOF'
6{
7  "resource_metrics": [
8    {
9      "resource": {
10        "attributes": [
11          { "key": "mw.resource_type", "value": { "string_value": "custom" } },
12          { "key": "service.name", "value": { "string_value": "custom-metrics-pusher" } }
13        ]
14      },
15      "scope_metrics": [
16        {
17          "metrics": [
18            {
19              "name": "swap-usage",
20              "description": "SWAP usage",
21              "unit": "By",
22              "gauge": {
23                "data_points": [
24                  {
25                    "attributes": [
26                      { "key": "device", "value": { "string_value": "nvme0n1p4" } }
27                    ],
28                    "time_unix_nano": 1759743015000000000,
29                    "asInt": 4000500678
30                  }
31                ]
32              }
33            }
34          ]
35        }
36      ]
37    }
38  ]
39}
40EOF

Notes:

• Use asInt for integer values or asDouble for floating-point values.
• time_unix_nano is the event timestamp; if omitted, the backend may use its receive time.
• You can send multiple metrics in the same batch; add them to the metrics array.
• To attach the metric to an existing resource (host/pod/service/etc.), add the required resource attribute(s) (see tables below).

Option B: Send custom metrics via OpenTelemetry

If you want to send custom metrics via your codebase, you need to install the OpenTelemetry Python SDK:

1pip install opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp

You can use the template codebase given below to send custom metrics:

1import time
2from opentelemetry import metrics
3from opentelemetry.sdk.metrics import MeterProvider
4from opentelemetry.sdk.resources import Resource
5from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
6from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import OTLPMetricExporter
7
8# Configure OTLP exporter for Middleware
9exporter = OTLPMetricExporter(
10    endpoint="https://ruplp.middleware.io",  # no /v1/metrics for gRPC
11    headers={"authorization": "<MW_API_KEY>"},
12)
13
14# Attach resource attributes (choose one of the options shown in the tables below)
15resource = Resource.create({
16    "mw.resource_type": "custom",
17    "service.name": "custom-metrics-pusher"
18})
19
20metric_reader = PeriodicExportingMetricReader(exporter)
21provider = MeterProvider(resource=resource, metric_readers=[metric_reader])
22metrics.set_meter_provider(provider)
23
24meter = metrics.get_meter(__name__)
25
26counter = meter.create_counter(
27    name="custom_counter",
28    description="Counts something custom",
29    unit="1",
30)
31
32histogram = meter.create_histogram(
33    name="custom_histogram",
34    description="Records histogram data",
35    unit="ms",
36)
37
38while True:
39    counter.add(1, attributes={"environment": "production", "region": "us-east-1"})
40    histogram.record(100, attributes={"operation": "database_query"})
41    time.sleep(5)

For other languages (Node.js/Go/Java, etc.), configure the OTLP/gRPC or OTLP/HTTP exporter and set the same endpoint and authorization header.

Ingest into existing Middleware resource types

Attach the required resource attribute so the metric lands in the correct dataset:

Example (host):

Add to the resource.attributes:

1{ "key": "host.id", "value": { "string_value": "ip-10-0-0-12" } }

Ingest pure custom data (no existing type)

If your metric doesn’t belong to an existing resource, set:

1{ "key": "mw.resource_type", "value": { "string_value": "custom" } }

These metrics appear under the Custom Metrics dataset in the UI and can be charted, alerted, and filtered using any attributes you attach.

Verify Delivery

• Send a test data point.
• In the dashboard, open dashboard builder → Create a new or open an existing dashboard and add a metrics widget.
• Under the Look for menu, select Custom, and the data should start showing in the selected dashboard.

Troubleshooting (quick)

• 401/403: Check the Authorization header (no Bearer), that the key is active, and you’re hitting the correct region.
• 400/422: Validate OTLP structure — ensure resource_metrics[*].scope_metrics[*].metrics[*] contains one of gauge / sum / histogram with a data_points array.
• No data visible: Confirm mw.resource_type or the correct resource attribute (e.g., host.id) is set. Ensure timestamps are realistic nanoseconds.
• High cardinality: Reduce dynamic attribute values; prefer enums/buckets.
• gRPC exporters: Use endpoint without /v1/metrics and keep TLS enabled (port 443).