---
title: Send events from your product
source: https://docs.newrelic.com/docs/new-relic-solutions/build-nr-ui/contribute-nr-io/send-events
---

> #### 💡 TIP
>
> This procedure is a part of course that teaches you how to build a quickstart. If you haven't already, checkout the [course introduction](https://docs.newrelic.com/docs/new-relic-solutions/build-nr-ui/contribute-nr-io/contribute-quickstart).
>
> Each procedure in this course builds on top of the last one, so make sure you've completed the last procedure, [send metrics from your product](https://docs.newrelic.com/docs/new-relic-solutions/build-nr-ui/contribute-nr-io/send-metrics) before proceeding with this one.

Events capture things that occur in your product. For example, if your platform automates application deployments, you might generate an event every time a job runs. If your application scans for security vulnerabilities, you might generate an event every time you detect one.

New Relic, provides you a variety of ways to instrument your application to send events to our [Event API](https://docs.newrelic.com/docs/data-apis/ingest-apis/event-api/introduction-event-api).

In this lesson, you send events from your product using our telemetry software development kit (SDK).

```python fileName=db.py
import os
import random
import datetime
from sys import getsizeof

from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetric

metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])

db = {}
stats = {
    "read_response_times": [],
    "read_errors": 0,
    "read_count": 0,
    "create_response_times": [],
    "create_errors": 0,
    "create_count": 0,
    "update_response_times": [],
    "update_errors": 0,
    "update_count": 0,
    "delete_response_times": [],
    "delete_errors": 0,
    "delete_count": 0,
    "cache_hit": 0,
}
last_push = {
    "read": datetime.datetime.now(),
    "create": datetime.datetime.now(),
    "update": datetime.datetime.now(),
    "delete": datetime.datetime.now(),
}

def read(key):
    print(f"Reading...")

    if random.randint(0, 30) > 10:
        stats["cache_hit"] += 1

    stats["read_response_times"].append(random.uniform(0.5, 1.0))
    if random.choice([True, False]):
        stats["read_errors"] += 1
    stats["read_count"] += 1
    try_send("read")

def create(key, value):
    print(f"Writing...")

    db[key] = value
    stats["create_response_times"].append(random.uniform(0.5, 1.0))
    if random.choice([True, False]):
        stats["create_errors"] += 1
    stats["create_count"] += 1
    try_send("create")

def update(key, value):
    print(f"Updating...")

    db[key] = value
    stats["update_response_times"].append(random.uniform(0.5, 1.0))
    if random.choice([True, False]):
        stats["update_errors"] += 1
    stats["update_count"] += 1
    try_send("update")

def delete(key):
    print(f"Deleting...")

    db.pop(key, None)
    stats["delete_response_times"].append(random.uniform(0.5, 1.0))
    if random.choice([True, False]):
        stats["delete_errors"] += 1
    stats["delete_count"] += 1
    try_send("delete")

def try_send(type_):
    print("try_send")

    now = datetime.datetime.now()
    interval_ms = (now - last_push[type_]).total_seconds() * 1000
    if interval_ms >= 2000:
        send_metrics(type_, interval_ms)

def send_metrics(type_, interval_ms):
    print("sending metrics...")

    keys = GaugeMetric("fdb_keys", len(db))
    db_size = GaugeMetric("fdb_size", getsizeof(db))

    errors = CountMetric(
        name=f"fdb_{type_}_errors",
        value=stats[f"{type_}_errors"],
        interval_ms=interval_ms
    )

    cache_hits = CountMetric(
        name=f"fdb_cache_hits",
        value=stats["cache_hit"],
        interval_ms=interval_ms
    )

    response_times = stats[f"{type_}_response_times"]
    response_time_summary = SummaryMetric(
        f"fdb_{type_}_responses",
        count=len(response_times),
        min=min(response_times),
        max=max(response_times),
        sum=sum(response_times),
        interval_ms=interval_ms,
    )

    batch = [keys, db_size, errors, cache_hits, response_time_summary]
    response = metric_client.send_batch(batch)
    response.raise_for_status()
    print("Sent metrics successfully!")
    clear(type_)

def clear(type_):
    stats[f"{type_}_response_times"] = []
    stats[f"{type_}_errors"] = 0
    stats["cache_hit"] = 0
    stats[f"{type_}_count"] = 0
    last_push[type_] = datetime.datetime.now()
```

## Use our SDK [#use-our-sdk]

We offer an open source [telemetry SDK](https://docs.newrelic.com/docs/data-apis/ingest-apis/telemetry-sdks-report-custom-telemetry-data) in several of the most popular programming languages. These send data to our data ingest APIs, including our Event API. Of these language SDKs, two work with the Event API: Python and Java.

Here, you use the [Python telemetry SDK](https://github.com/newrelic/newrelic-telemetry-sdk-python) to send events to New Relic.

1.  Change to the `send-events/flashDB` directory of the [course repository](https://github.com/newrelic-experimental/build-a-quickstart-lab).
    ````bash
    cd ../../send-events/flashDB
    ```

    ````
2.  If you haven't already, install the `newrelic-telemetry-sdk` package.
    ````bash
    pip install newrelic-telemetry-sdk
    ```

    ````
3.  Open `db.py` file in the IDE of your choice and configure the `EventClient`.
    ````python fileName=db.py
    import os
    import random
    import datetime
    from sys import getsizeof

    from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetric
    from newrelic_telemetry_sdk import EventClient

    metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])
    event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])

    db = {}
    stats = {
        "read_response_times": [],
        "read_errors": 0,
        "read_count": 0,
        "create_response_times": [],
        "create_errors": 0,
        "create_count": 0,
        "update_response_times": [],
        "update_errors": 0,
        "update_count": 0,
        "delete_response_times": [],
        "delete_errors": 0,
        "delete_count": 0,
        "cache_hit": 0,
    }
    last_push = {
        "read": datetime.datetime.now(),
        "create": datetime.datetime.now(),
        "update": datetime.datetime.now(),
        "delete": datetime.datetime.now(),
    }

    def read(key):
        print(f"Reading...")

        if random.randint(0, 30) > 10:
            stats["cache_hit"] += 1

        stats["read_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["read_errors"] += 1
        stats["read_count"] += 1
        try_send("read")

    def create(key, value):
        print(f"Writing...")

        db[key] = value
        stats["create_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["create_errors"] += 1
        stats["create_count"] += 1
        try_send("create")

    def update(key, value):
        print(f"Updating...")

        db[key] = value
        stats["update_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["update_errors"] += 1
        stats["update_count"] += 1
        try_send("update")

    def delete(key):
        print(f"Deleting...")

        db.pop(key, None)
        stats["delete_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["delete_errors"] += 1
        stats["delete_count"] += 1
        try_send("delete")

    def try_send(type_):
        print("try_send")

        now = datetime.datetime.now()
        interval_ms = (now - last_push[type_]).total_seconds() * 1000
        if interval_ms >= 2000:
            send_metrics(type_, interval_ms)

    def send_metrics(type_, interval_ms):
        print("sending metrics...")

        keys = GaugeMetric("fdb_keys", len(db))
        db_size = GaugeMetric("fdb_size", getsizeof(db))

        errors = CountMetric(
            name=f"fdb_{type_}_errors",
            value=stats[f"{type_}_errors"],
            interval_ms=interval_ms
        )

        cache_hits = CountMetric(
            name=f"fdb_cache_hits",
            value=stats["cache_hit"],
            interval_ms=interval_ms
        )

        response_times = stats[f"{type_}_response_times"]
        response_time_summary = SummaryMetric(
            f"fdb_{type_}_responses",
            count=len(response_times),
            min=min(response_times),
            max=max(response_times),
            sum=sum(response_times),
            interval_ms=interval_ms,
        )

        batch = [keys, db_size, errors, cache_hits, response_time_summary]
        response = metric_client.send_batch(batch)
        response.raise_for_status()
        print("Sent metrics successfully!")
        clear(type_)

    def clear(type_):
        stats[f"{type_}_response_times"] = []
        stats[f"{type_}_errors"] = 0
        stats["cache_hit"] = 0
        stats[f"{type_}_count"] = 0
        last_push[type_] = datetime.datetime.now()
    ```

    <Callout variant="important">
      This example expects an environment variable called `NEW_RELIC_LICENSE_KEY`.
    </Callout>

    ````
4.  Instrument your app to send an event to New Relic.
    ````python fileName=db.py
    import os
    import random
    import datetime
    from sys import getsizeof

    from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetric
    from newrelic_telemetry_sdk import EventClient, Event

    metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])
    event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])

    db = {}
    stats = {
        "read_response_times": [],
        "read_errors": 0,
        "read_count": 0,
        "create_response_times": [],
        "create_errors": 0,
        "create_count": 0,
        "update_response_times": [],
        "update_errors": 0,
        "update_count": 0,
        "delete_response_times": [],
        "delete_errors": 0,
        "delete_count": 0,
        "cache_hit": 0,
    }
    last_push = {
        "read": datetime.datetime.now(),
        "create": datetime.datetime.now(),
        "update": datetime.datetime.now(),
        "delete": datetime.datetime.now(),
    }

    def read(key):
        print(f"Reading...")

        if random.randint(0, 30) > 10:
            stats["cache_hit"] += 1

        stats["read_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["read_errors"] += 1
        stats["read_count"] += 1
        try_send("read")

    def create(key, value):
        print(f"Writing...")

        db[key] = value
        stats["create_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["create_errors"] += 1
        stats["create_count"] += 1
        try_send("create")

    def update(key, value):
        print(f"Updating...")

        db[key] = value
        stats["update_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["update_errors"] += 1
        stats["update_count"] += 1
        try_send("update")

    def delete(key):
        print(f"Deleting...")

        db.pop(key, None)
        stats["delete_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["delete_errors"] += 1
        stats["delete_count"] += 1
        try_send("delete")

    def try_send(type_):
        print("try_send")

        now = datetime.datetime.now()
        interval_ms = (now - last_push[type_]).total_seconds() * 1000
        if interval_ms >= 2000:
            send_metrics(type_, interval_ms)

    def send_metrics(type_, interval_ms):
        print("sending metrics...")

        keys = GaugeMetric("fdb_keys", len(db))
        db_size = GaugeMetric("fdb_size", getsizeof(db))

        errors = CountMetric(
            name=f"fdb_{type_}_errors",
            value=stats[f"{type_}_errors"],
            interval_ms=interval_ms
        )

        cache_hits = CountMetric(
            name=f"fdb_cache_hits",
            value=stats["cache_hit"],
            interval_ms=interval_ms
        )

        response_times = stats[f"{type_}_response_times"]
        response_time_summary = SummaryMetric(
            f"fdb_{type_}_responses",
            count=len(response_times),
            min=min(response_times),
            max=max(response_times),
            sum=sum(response_times),
            interval_ms=interval_ms,
        )

        batch = [keys, db_size, errors, cache_hits, response_time_summary]
        response = metric_client.send_batch(batch)
        response.raise_for_status()
        print("Sent metrics successfully!")
        clear(type_)

    def send_event(type_):
        print("sending event...")

        count = Event(
            "fdb_method", {"method": type_}
        )

        response = event_client.send_batch(count)
        response.raise_for_status()
        print("Event sent successfully!")

    def clear(type_):
        stats[f"{type_}_response_times"] = []
        stats[f"{type_}_errors"] = 0
        stats["cache_hit"] = 0
        stats[f"{type_}_count"] = 0
        last_push[type_] = datetime.datetime.now()
    ```

    Here, you instrument your platform to send a `count` event to New Relic.

    ````
5.  Amend the `try_send` module to send the event every 2 second.
    ````python fileName=db.py
    import os
    import random
    import datetime
    from sys import getsizeof

    from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetric
    from newrelic_telemetry_sdk import EventClient, Event

    metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])
    event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])

    db = {}
    stats = {
        "read_response_times": [],
        "read_errors": 0,
        "read_count": 0,
        "create_response_times": [],
        "create_errors": 0,
        "create_count": 0,
        "update_response_times": [],
        "update_errors": 0,
        "update_count": 0,
        "delete_response_times": [],
        "delete_errors": 0,
        "delete_count": 0,
        "cache_hit": 0,
    }
    last_push = {
        "read": datetime.datetime.now(),
        "create": datetime.datetime.now(),
        "update": datetime.datetime.now(),
        "delete": datetime.datetime.now(),
    }

    def read(key):
        print(f"Reading...")

        if random.randint(0, 30) > 10:
            stats["cache_hit"] += 1

        stats["read_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["read_errors"] += 1
        stats["read_count"] += 1
        try_send("read")

    def create(key, value):
        print(f"Writing...")

        db[key] = value
        stats["create_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["create_errors"] += 1
        stats["create_count"] += 1
        try_send("create")

    def update(key, value):
        print(f"Updating...")

        db[key] = value
        stats["update_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["update_errors"] += 1
        stats["update_count"] += 1
        try_send("update")

    def delete(key):
        print(f"Deleting...")

        db.pop(key, None)
        stats["delete_response_times"].append(random.uniform(0.5, 1.0))
        if random.choice([True, False]):
            stats["delete_errors"] += 1
        stats["delete_count"] += 1
        try_send("delete")

    def try_send(type_):
        print("try_send")

        now = datetime.datetime.now()
        interval_ms = (now - last_push[type_]).total_seconds() * 1000
        if interval_ms >= 2000:
            send_metrics(type_, interval_ms)
            send_event(type_)

    def send_metrics(type_, interval_ms):
        print("sending metrics...")

        keys = GaugeMetric("fdb_keys", len(db))
        db_size = GaugeMetric("fdb_size", getsizeof(db))

        errors = CountMetric(
            name=f"fdb_{type_}_errors",
            value=stats[f"{type_}_errors"],
            interval_ms=interval_ms
        )

        cache_hits = CountMetric(
            name=f"fdb_cache_hits",
            value=stats["cache_hit"],
            interval_ms=interval_ms
        )

        response_times = stats[f"{type_}_response_times"]
        response_time_summary = SummaryMetric(
            f"fdb_{type_}_responses",
            count=len(response_times),
            min=min(response_times),
            max=max(response_times),
            sum=sum(response_times),
            interval_ms=interval_ms,
        )

        batch = [keys, db_size, errors, cache_hits, response_time_summary]
        response = metric_client.send_batch(batch)
        response.raise_for_status()
        print("Sent metrics successfully!")
        clear(type_)

    def send_event(type_):
        print("sending event...")

        count = Event(
            "fdb_method", {"method": type_}
        )

        response = event_client.send_batch(count)
        response.raise_for_status()
        print("Event sent successfully!")

    def clear(type_):
        stats[f"{type_}_response_times"] = []
        stats[f"{type_}_errors"] = 0
        stats["cache_hit"] = 0
        stats[f"{type_}_count"] = 0
        last_push[type_] = datetime.datetime.now()
    ```

    Your platform will now report the configured event every 2 seconds.

    ````
6.  Navigate to the root of your application at `build-a-quickstart-lab/send-events/flashDB`.
7.  Run your services to verify that it is reporting events.
    ````bash animate
    python simulator.py
    [output] Writing...
    [output] try_send
    [output] Writing...
    [output] try_send
    [output] Reading...
    [output] try_send
    [output] Reading...
    [output] try_send
    [output] Writing...
    [output] try_send
    [output] Writing...
    [output] try_send
    [output] Reading...
    [output] sending metrics...
    [output] {green}Sent metrics successfully!
    [output] sending event...
    [output] {green}Event sent successfully!
    ```

    ````

## Alternative Options [#alternative-options]

If the language SDK doesn't fit your needs, try out one of our other options:

-   **Manual Implementation**: If our SDK in your preferred language doesn't support events, you can always manually instrument your own library to make a POST request to the [New Relic Event API](https://docs.newrelic.com/docs/data-apis/ingest-apis/event-api/introduction-event-api).

-   **Prometheus Data**: [Prometheus](https://docs.newrelic.com/docs/infrastructure/prometheus-integrations/get-started/send-prometheus-metric-data-new-relic) data can be sent to New Relic in two ways, [remote write](https://docs.newrelic.com/docs/infrastructure/prometheus-integrations/install-configure-remote-write/set-your-prometheus-remote-write-integration) and [OpenMetrics](https://docs.newrelic.com/docs/infrastructure/prometheus-integrations/install-configure-openmetrics/install-update-or-uninstall-your-prometheus-openmetrics-integration). At a very high level, you should use remote write if you manage your own Prometheus servers and OpenMetrics if you don't.

-   **Flex Agent**: Our serverless [Flex agent](https://github.com/newrelic/nri-flex/blob/master/docs/basic-tutorial.md#flex-step-by-step-tutorial) is a possibility, but might be a more complex integration to get started.

In this procedure, you instrumented your service to send events to New Relic. Next, instrument it to send logs.

> #### 💡 TIP
>
> This procedure is a part of course that teaches you how to build a quickstart. Continue to next lesson, [send logs from your product](https://docs.newrelic.com/docs/new-relic-solutions/build-nr-ui/contribute-nr-io/send-logs).