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OpenTelemetry.
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Beginner 4
01

What is OpenTelemetry and what are the three pillars of observability it addresses?

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OpenTelemetry (OTel) is an open-source observability framework that provides a unified approach to collecting, processing, and exporting telemetry data. It addresses the three pillars of observability:

  • Traces: Track requests as they flow through distributed systems, showing the path and timing of operations
  • Metrics: Numerical measurements collected over time intervals (counters, gauges, histograms)
  • Logs: Discrete event records with timestamps and contextual information

OpenTelemetry provides APIs, SDKs, and tools to instrument applications and infrastructure, making it easier to understand system behavior and performance.

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02

Explain the difference between OpenTelemetry and OpenTracing/OpenCensus.

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OpenTelemetry is the successor and merger of two previous projects:

  • OpenTracing: Focused primarily on distributed tracing with vendor-neutral APIs
  • OpenCensus: Provided both tracing and metrics collection capabilities

Key differences:

  • OpenTelemetry combines both projects' capabilities into a single, comprehensive framework
  • Provides unified APIs for traces, metrics, and logs (the three pillars)
  • Better standardization and broader vendor support
  • More mature ecosystem with extensive instrumentation libraries
  • Backward compatibility with both OpenTracing and OpenCensus

OpenTracing and OpenCensus are now in maintenance mode, with new development focused on OpenTelemetry.

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03

What are the main components of the OpenTelemetry ecosystem?

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The OpenTelemetry ecosystem consists of several key components:

  • APIs: Language-specific interfaces for creating telemetry data
  • SDKs: Implementations of the APIs with configuration capabilities
  • Instrumentation Libraries: Pre-built integrations for popular frameworks and libraries
  • Collector: Vendor-agnostic service for receiving, processing, and exporting telemetry data
  • Exporters: Components that send data to various backends (Jaeger, Prometheus, etc.)
  • Resources: Metadata describing the entity producing telemetry (service name, version, etc.)
  • Semantic Conventions: Standard attribute names and meanings for consistent data representation
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04

How do you configure a basic OpenTelemetry Collector pipeline?

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Intermediate 9
05

Describe the OpenTelemetry Collector architecture and its main components.

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06

What is the OTLP protocol and why is it important?

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07

Explain the concept of Resources in OpenTelemetry.

Part of Pro
08

What are the different deployment patterns for OpenTelemetry Collector?

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09

How do you secure OpenTelemetry Collector communications?

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10

How do you monitor the health and performance of OpenTelemetry Collector itself?

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11

How do you troubleshoot common OpenTelemetry Collector issues?

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12

What are the key performance metrics to monitor for OpenTelemetry Collector?

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13

What are the security best practices for OpenTelemetry deployments?

Part of Pro
Expert 12
14

How do you handle backpressure and reliability in OpenTelemetry Collector?

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15

Explain sampling strategies in OpenTelemetry and when to use each.

Part of Pro
16

How do you handle data loss prevention in OpenTelemetry deployments?

Part of Pro
17

How do you optimize OpenTelemetry Collector performance for high-throughput environments?

Part of Pro
18

What are the considerations for deploying OpenTelemetry Collector in Kubernetes at scale?

Part of Pro
19

How do you implement data governance and compliance in OpenTelemetry?

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20

How do you implement custom processors in OpenTelemetry Collector?

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21

Explain auto-instrumentation strategies and their trade-offs.

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22

How do you handle multi-tenancy in OpenTelemetry deployments?

Part of Pro
23

How do you implement distributed tracing correlation across service boundaries?

Part of Pro
24

How would you implement blue-green deployments with OpenTelemetry observability?

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25

How do you handle OpenTelemetry in serverless environments like AWS Lambda?

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