Dica
Este procedimento faz parte do curso que ensina como criar um início rápido. Se ainda não o fez, confira a introdução do curso.
Cada procedimento neste curso é baseado no anterior, portanto, certifique-se de ter concluído o último procedimento, envie um evento do seu produto antes de prosseguir com este.
log são gerados pelo aplicativo. Eles são registros de texto baseados em tempo que ajudam seu usuário a ver o que está acontecendo em seu sistema.
New Relic oferece uma variedade de maneiras de instrumentar seu aplicativo para enviar log para nossa Logs API.
Nesta lição, você aprenderá a enviar log do seu produto usando nosso kit de desenvolvimento de software de telemetria (SDK).
import osimport randomimport datetimefrom sys import getsizeof
from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetricfrom 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()
Use nosso SDK
Oferecemos um SDK de telemetria de código aberto em diversas das linguagens de programação mais populares. Eles enviam dados para nossa de ingestão de API dados, incluindo nossa Log API. Desses SDKs de linguagem, Python e Java funcionam com a Log API.
Nesta lição, você aprende como instalar e usar o SDK de telemetria Python para enviar logs para o New Relic.
Mude para o diretório send-logs/flashDB
do repositório do curso.
$cd ../../send-events/flashDB
Se ainda não o fez, instale o pacote newrelic-telemetry-sdk
.
$pip install newrelic-telemetry-sdk
Abra o arquivo db.py
no IDE de sua preferência e configure o LogClient
.
import osimport randomimport datetimefrom sys import getsizeof
from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetricfrom newrelic_telemetry_sdk import EventClient, Eventfrom newrelic_telemetry_sdk import LogClient
metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])log_client = LogClient(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()
Importante
Este exemplo espera uma variável de ambiente chamada $NEW_RELIC_LICENSE_KEY
.
Instrumento seu aplicativo para enviar logs para New Relic.
import osimport randomimport datetimefrom sys import getsizeofimport psutil
from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetricfrom newrelic_telemetry_sdk import EventClient, Eventfrom newrelic_telemetry_sdk import LogClient, Log
metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])log_client = LogClient(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 send_logs():
print("sending log...")
process = psutil.Process(os.getpid()) memory_usage = process.memory_percent()
log = Log("FlashDB is using " + str(round(memory_usage * 100, 2)) + "% memory")
response = log_client.send(log) response.raise_for_status() print("Log 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()
Aqui você instrumenta sua plataforma para enviar memory_usage
como log para New Relic.
Altere o módulo try_send
para enviar o log a cada 2 segundos.
import osimport randomimport datetimefrom sys import getsizeofimport psutil
from newrelic_telemetry_sdk import MetricClient, GaugeMetric, CountMetric, SummaryMetricfrom newrelic_telemetry_sdk import EventClient, Eventfrom newrelic_telemetry_sdk import LogClient, Log
metric_client = MetricClient(os.environ["NEW_RELIC_LICENSE_KEY"])event_client = EventClient(os.environ["NEW_RELIC_LICENSE_KEY"])log_client = LogClient(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_) send_logs()
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 send_logs():
print("sending log...")
process = psutil.Process(os.getpid()) memory_usage = process.memory_percent()
log = Log("FlashDB is using " + str(round(memory_usage * 100, 2)) + "% memory")
response = log_client.send(log) response.raise_for_status() print("Log 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()
Sua plataforma agora reportará o logs configurados a cada 2 segundos.
Navegue até a raiz do seu aplicativo em build-a-quickstart-lab/send-logs/flashDB
.
Execute seus serviços para verificar se ele está relatando logs.
$python simulator.pyWriting...try_sendReading...try_sendReading...try_sendWriting...try_sendWriting...try_sendReading...sending metrics...Sent metrics successfully!sending event...Event sent successfully!sending log...Log sent successfully!
Opções alternativas
Se o SDK da linguagem não atender às suas necessidades, experimente uma de nossas outras opções:
- New Relic oferece uma variedade de soluções de encaminhamento de logs que permitem coletar log do sistema operacional, plataforma de nuvem incluindo Amazon AWS, [Google Cloud Platform], Microsoft Azure e Heroku, Kubernetes, Docker e APM.
- Implementação Manual: Se as opções anteriores não atenderem aos seus requisitos, você sempre pode instrumentar manualmente sua própria biblioteca para fazer uma solicitação POST para a New Relic Log API.
Neste procedimento, você instrumentou seu serviço para enviar log para New Relic. Em seguida, instrumento-o para enviar o rastreamento.
Dica
Este procedimento faz parte do curso que ensina como criar um início rápido. Continue na próxima lição, envie o rastreamento do seu produto.