Telemetry
Telemetry is automatically generated or collected operational data describing a system’s activity, state, behavior, or performance.
Effective Platform Engineering
Telemetry data consists of automatically emitted records such as metrics, logs, and traces that describe software-system behavior, performance, and state.
- How it is used
- Supports cross-service diagnosis and engineering and business decisions about system health, feature use, and platform value.
- How deep it goes
- Explains collection choices, alerts, tracing, aggregation, and access through operational scenarios; does not specify record schemas or emitter implementations.
- Examples
- Uses Kubernetes CPU activity, a platform-service adoption target, cross-service incidents, and spreadsheets broken by data-structure changes.
- What you can do after
- Diagnose/debug with it by querying shared telemetry across services and defining alerts for known unhealthy states.
Read how Effective Platform Engineering explains telemetry →
Secure APIs
Data and signals emitted by software about its execution, health, and behavior.
- How it is used
- Supports API reliability, security detection, incident investigation, and understanding how users interact with services.
- How deep it goes
- Defines logs, traces, metrics, and instrumentation with practical setup, but stops short of detailed telemetry-storage internals.
- Examples
- Uses API requests, errors, database-query logs, OpenTelemetry spans, endpoint metrics, and unusual user request rates.
- What you can do after
- Operate/configure OpenTelemetry instrumentation, correlate API activity, analyze trends, and design safer security telemetry.
Google Anthos in Action
Telemetry is automatically collected information about system or service behavior, including metrics, logs, and traces.
- How it is used
- Provides automatic visibility into microservice traffic for monitoring, troubleshooting, security, scaling, and operational analysis.
- How deep it goes
- Explains collection paths, observability tools, and operational uses, but stops short of detailed telemetry schemas or instrumentation code.
- Examples
- Uses Envoy sidecars, Kiali service graphs, Prometheus time series, Grafana dashboards, and Google Cloud Monitoring and Logging.
- What you can do after
- Diagnose/debug with it by tracing latency, inspecting traffic and dependencies, reviewing service health, and analyzing historical failures.
Cloud Observability in Action
Telemetry is the process of collecting signals from sources, processing them, and ingesting them into destinations for consumption.
- How it is used
- Collects and routes system signals so people and applications can consume them for understanding and influencing operations.
- How deep it goes
- Defines the source-agent-destination pipeline and discusses instrumentation, collection, processing, and signal costs without detailing individual signal implementations.
- Examples
- Uses Kubernetes microservices, application code, APIs, databases, metrics, traces, logs, dashboards, alerts, and long-term storage.
- What you can do after
- Operate telemetry by selecting signals, instrumenting owned sources, collecting them through agents, and sending them to central destinations.
Logs and Telemetry
Telemetry data is machine-generated information about software or infrastructure behavior, including logs, metrics, and traces.
- How it is used
- Uses machine-generated logs, metrics, and traces to support monitoring and observability across distributed systems.
- How deep it goes
- Defines telemetry forms and follows collection, transformation, encoding, transmission, and routing, without detailing individual payload schemas.
- Examples
- Illustrates application-generated logs, metrics, and traces flowing through Fluent Bit to compatible collectors or analysis tools.
- What you can do after
- Evaluate how telemetry moves from applications through collectors and exporters using OTLP-compatible transports.
Build an AI Agent (From Scratch)
Operational data and signals generated by a running system and transmitted for monitoring and analysis.
- How it is used
- Supports agent observability, debugging, evaluation, anomaly detection, and operational response.
- How deep it goes
- Defines telemetry, separates metrics, traces, and logs, and explains instrumentation and export without detailing backend implementation.
- Examples
- Uses agent traces, tool calls, latency, token use, costs, errors, retries, prompts, outputs, and runtime records.
- What you can do after
- Diagnose/debug agent behavior, evaluate reliability and cost, detect anomalies, and inspect request execution through telemetry.
Read how Build an AI Agent (From Scratch) explains telemetry →
Platform Engineering on Kubernetes
Telemetry is automatically generated data about software and system behavior, including metrics, logs, and traces.
- How it is used
- Supports diagnosing distributed-application behavior and performance when services fail or users experience poor responses.
- How deep it goes
- Describes metrics, logs, traces, instrumentation, centralized collection, and dashboards without detailing collector configuration.
- Examples
- Uses centralized service telemetry and an approved-versus-rejected proposals dashboard as concrete examples.
- What you can do after
- Operate services with OpenTelemetry instrumentation and Prometheus-Grafana dashboards for behavior and performance visibility.
Read how Platform Engineering on Kubernetes explains telemetry →
Architecture Modernization: Socio-technical alignment of software, strategy, and structure
An event containing measured operational data emitted by a device or system.
- How it is used
- Supports remote monitoring and connected-boat experiences within an IoT growth strategy.
- How deep it goes
- Defines telemetry through sensor readings and frames its throughput demands without detailing event schemas or processing internals.
- Examples
- Uses boat engine speed, temperature, geofence movement, and thousands of connected devices as concrete telemetry contexts.
- What you can do after
- Evaluate whether an architecture can process telemetry at the scale required by thousands of concurrently connected devices.
Related concepts
- observabilityused by · Observability is the ability to infer a system’s internal state and behavior from its externally available outputs, such as logs, metrics, and traces.
- trajectoryhas part · A trajectory is an ordered sequence of states, actions, events, or operations that records or describes progression through successive steps or over time.
- instrumentationproduced by · Instrumentation is the addition or activation of mechanisms in software or systems to observe, measure, or record their behavior during execution.
- monitoringincludes · Monitoring is the ongoing observation and measurement of a system’s behavior, state, or operational signals to assess its condition and detect changes or problems.
- OpenTelemetryproduced by · OpenTelemetry is an open, vendor-neutral observability standard and framework for instrumenting software and generating, collecting, and exporting telemetry such as traces, metrics, and logs.
- metrichas part · A metric is a quantitative measure used to characterize or assess a property, condition, behavior, performance, or outcome.
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