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Cloud-Native Observability with OpenTelemetry

Cloud-Native Observability with OpenTelemetry

By : Boten
4.8 (8)
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Cloud-Native Observability with OpenTelemetry

Cloud-Native Observability with OpenTelemetry

4.8 (8)
By: Boten

Overview of this book

Cloud-Native Observability with OpenTelemetry is a guide to helping you look for answers to questions about your applications. This book teaches you how to produce telemetry from your applications using an open standard to retain control of data. OpenTelemetry provides the tools necessary for you to gain visibility into the performance of your services. It allows you to instrument your application code through vendor-neutral APIs, libraries and tools. By reading Cloud-Native Observability with OpenTelemetry, you’ll learn about the concepts and signals of OpenTelemetry - traces, metrics, and logs. You’ll practice producing telemetry for these signals by configuring and instrumenting a distributed cloud-native application using the OpenTelemetry API. The book also guides you through deploying the collector, as well as telemetry backends necessary to help you understand what to do with the data once it's emitted. You’ll look at various examples of how to identify application performance issues through telemetry. By analyzing telemetry, you’ll also be able to better understand how an observable application can improve the software development life cycle. By the end of this book, you’ll be well-versed with OpenTelemetry, be able to instrument services using the OpenTelemetry API to produce distributed traces, metrics and logs, and more.
Table of Contents (17 chapters)
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1
Section 1: The Basics
3
Chapter 2: OpenTelemetry Signals – Traces, Metrics, and Logs
5
Section 2: Instrumenting an Application
10
Section 3: Using Telemetry Data

The grocery store

It's time to go back to the example application from Chapter 4, Distributed Tracing –Tracing Code Execution, to get some practical experience of all the knowledge we've gained so far. Let's start by adding a method to retrieve a meter that will resemble configure_tracer from the previous chapter. This method will be named configure_meter and will contain the configuration code from an example earlier in this chapter. One main difference is the addition of a resource that uses LocalMachineResourceDetector, as we already defined in this module. Add the following code to the common.py module:

common.py

from opentelemetry._metrics import get_meter_provider, set_meter_provider
from opentelemetry.sdk._metrics import MeterProvider
from opentelemetry.sdk._metrics.export import (
    ConsoleMetricExporter,
    PeriodicExportingMetricReader,
)
def configure_meter(name, version):
    exporter...

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