Instrumenting Apps with OTel SDKs
Get an overview of OpenTelemetry SDKs for various programming languages. Understand how they are used to generate logs, metrics, and traces.
Instrumenting Apps with OTel SDKs is a free System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
What are OTel SDKs?
OpenTelemetry SDKs are language-specific libraries that enable your applications to generate and export observability data. Think of them as the toolkit for making your code observable.
They provide the necessary APIs (Application Programming Interfaces) to capture logs, metrics, and traces directly from your application's runtime.
Role of OpenTelemetry SDKs
SDKs are crucial because they bridge the gap between your application code and the OpenTelemetry standard. They handle the complex work of:
- Collecting Data: Gathering raw observability signals like method calls or variable values.
- Processing Data: Enriching, filtering, and batching this data.
- Exporting Data: Sending the processed data to an observability backend (like Jaeger, Prometheus, or an ELK stack).
Key OTel SDK Components
An OpenTelemetry SDK typically includes several core components that work together:
- Providers: Such as
TracerProvider,MeterProvider, andLoggerProvider, which manage the creation of Tracers, Meters, and Loggers. - Processors/Readers: These define how collected data (spans, metrics, log records) is processed before being sent to an exporter.
- Exporters: Components that send the processed data to an external system, like a console or a remote endpoint.
Tracing with OTel SDKs
When you want to trace requests through your system, OpenTelemetry SDKs provide tools to create and manage spans. A span represents a single operation within a trace.
The SDK gives you a Tracer object, which you use to start new spans, set attributes on them, and link them to parent spans, effectively building a complete trace of a request's journey.
OTel Tracing Code Example
Here's a simple Python example showing how to initialize OpenTelemetry and create a basic trace with nested spans. We use a ConsoleSpanExporter to print spans to the console.
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
# 1. Configure the TracerProvider
provider = TracerProvider()
processor = SimpleSpanProcessor(ConsoleSpanExporter())
provider.add_span_processor(processor)
trace.set_tracer_provider(provider)
# 2. Get a Tracer
tracer = trace.get_tracer(__name__)
# 3. Create a Span
with tracer.start_as_current_span("my-first-span"):
print("Inside the span!")
with tracer.start_as_current_span("child-span"):
print("Inside the child span!")
print("Tracing example finished.")Metrics with OTel SDKs
OpenTelemetry SDKs allow you to define and record various types of metrics. Metrics are numerical measurements captured over time, useful for aggregated views of system health and performance.
You obtain a Meter object from the SDK, which you then use to create different types of instruments, such as Counters (for incrementing values) or Gauges (for current values).
OTel Metrics Code Example
This Python example demonstrates how to set up OpenTelemetry for metrics and use a Meter to create and update a Counter. The ConsoleMetricExporter prints the collected metrics.
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import ConsoleMetricExporter, PeriodicExportingMetricReader
# 1. Configure the MeterProvider
reader = PeriodicExportingMetricReader(ConsoleMetricExporter())
provider = MeterProvider(metric_readers=[reader])
metrics.set_meter_provider(provider)
# 2. Get a Meter
meter = metrics.get_meter(__name__)
# 3. Create a Counter instrument
counter = meter.create_counter(
"my_example_counter",
description="Counts how many times something happens"
)
# 4. Record a measurement
counter.add(1, {"key": "value"})
counter.add(2, {"another_key": "another_value"})
print("Metrics example finished. May take a moment to export.")Logging with OTel SDKs
OpenTelemetry SDKs also provide a way to capture and enrich logs. While traditional logging often focuses on plain text, OTel logs can be structured and correlated with traces and metrics.
The SDK offers a Logger (or integrates with existing logging frameworks) to create Log Records. These records can then be processed and exported alongside your traces and metrics, providing a unified view.
OTel Logging Code Example
This Python example shows how to integrate OpenTelemetry with the standard Python logging library. Logs emitted through the standard logger are then processed and exported by OTel.
import logging
from opentelemetry._logs import set_logger_provider
from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
from opentelemetry.sdk._logs.export import ConsoleLogExporter, SimpleLogRecordProcessor
# 1. Configure the LoggerProvider
provider = LoggerProvider()
processor = SimpleLogRecordProcessor(ConsoleLogExporter())
provider.add_log_record_processor(processor)
set_logger_provider(provider)
# 2. Get a Python standard logger
# and attach the OTel handler
handler = LoggingHandler(logger_provider=provider)
logging.getLogger().addHandler(handler)
logging.getLogger().setLevel(logging.INFO)
# 3. Emit a log record
logging.info("This is an info log from OTel SDK!")
logging.warning("A warning occurred.")
print("Logging example finished.")OTel SDKs Quick Check
OpenTelemetry SDKs are essential for instrumenting applications. Which of the following is NOT a core component or function provided by an OpenTelemetry SDK?
Recap: OTel SDKs
You've learned that OpenTelemetry SDKs are the foundational tools for instrumenting your applications across different programming languages.
- They provide the APIs to generate traces, metrics, and logs.
- They handle the processing and exporting of this data to your chosen observability backend.
- By using SDKs, you ensure your application's observability data adheres to the OpenTelemetry standard, making it portable and vendor-agnostic.
Next, you'll dive deeper into how to effectively instrument your applications.
Frequently asked questions
Is the “Instrumenting Apps with OTel SDKs” lesson free?
Yes — the full text of “Instrumenting Apps with OTel SDKs” is free to read here on the web, and the System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) course, upgrade to CoddyKit PRO.
What will I learn in “Instrumenting Apps with OTel SDKs”?
Get an overview of OpenTelemetry SDKs for various programming languages. Understand how they are used to generate logs, metrics, and traces. You practise System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry)?
No prior experience is required. System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Instrumenting Apps with OTel SDKs” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) lesson?
Yes. Every System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- The OpenTelemetry Standard
- OTel Collectors and Exporters
- Instrumenting Apps with OTel SDKs
- Signals and Semantic Conventions