Python Agent Meter Reporter

To enable or disable this feature, you will need to set some environment variables.

Enabling the feature (default)

os.environ['SW_AGENT_METER_REPORTER_ACTIVE'] = 'True'

or

export SW_AGENT_METER_REPORTER_ACTIVE=True

Disable the feature

os.environ['SW_AGENT_METER_REPORTER_ACTIVE'] = 'False'

or

export SW_AGENT_METER_REPORTER_ACTIVE=False

Counter

  • Counter API represents a single monotonically increasing counter, automatic collect data and report to backend.
builder = Counter.Builder('c2', CounterMode.INCREMENT, (("k1", "v1"), ("k2", "v2")))
# or this way
# builder = Counter.Builder('c2', CounterMode.INCREMENT).tag('key1', 'value1').tag('key2', 'value2')
c = builder.build()
c.increment(2)

Syntactic sugars

builder = Counter.Builder('c2', CounterMode.INCREMENT)
c = builder.build()

# increase Counter c by the time the with-wrapped codes consumed
with c.create_timer():
    # some codes may consume a certain time

builder = Counter.Builder('c3', CounterMode.INCREMENT)
c = builder.build()

# increase Counter c by num once counter_decorator_test gets called
@Counter.increase(name='c3', num=2)
def counter_decorator_test():
    # some codes

builder = Counter.Builder('c4', CounterMode.INCREMENT)
c = builder.build()

# increase Counter c by the time counter_decorator_test consumed
@Counter.timer(name='c4')
def counter_decorator_test(s):
    # some codes may consume a certain time
  1. Counter.Builder(name, tags) Create a new counter builder with the meter name and optional tags.
  2. Counter.tag(key: str, value) Mark a tag key/value pair.
  3. Counter.mode(mode: CounterMode) Change the counter mode, RATE mode means reporting rate to the backend.
  4. Counter.increment(count) Increment count to the Counter, It could be a positive value.

Gauge

  • Gauge API represents a single numerical value.
# producer: iterable object
builder = Gauge.Builder('g1', producer, (("key", "value")))
g = Builder.build()
  1. Gauge.Builder(name, tags) Create a new gauge builder with the meter name and iterable object, this iterable object need to produce numeric value.
  2. Gauge.tag(key: str, value) Mark a tag key/value pair.
  3. Gauge.build() Build a new Gauge which is collected and reported to the backend.

Histogram

  • Histogram API represents a summary sample observations with customize buckets.
builder = Histogram.Builder('h2', [i / 10 for i in range(10)], ("key", "value"))
h = builder.build()

Syntactic sugars

builder = Histogram.Builder('h3', [i / 10 for i in range(10)])
h = builder.build()

# Histogram h will record the time the with-wrapped codes consumed
with h.create_timer():
    # some codes may consume a certain time

builder = Histogram.Builder('h2', [i / 10 for i in range(10)])
h = builder.build()

# Histogram h will record the time histogram_decorator_test consumed
@Histogram.timer(name='h2')
def histogram_decorator_test(s):
    time.sleep(s)
  1. Histogram.Builder(name, tags) Create a new histogram builder with the meter name and optional tags.
  2. Histogram.tag(key: str, value) Mark a tag key/value pair.
  3. Histogram.minValue(value) Set up the minimal value of this histogram, default is 0.
  4. Histogram.build() Build a new Histogram which is collected and reported to the backend.
  5. Histogram.addValue(value) Add value into the histogram, automatically analyze what bucket count needs to be increment. rule: count into [step1, step2).