Log
A log is a record of events, activity, or diagnostic information produced during the operation of a system or process.
Building Web APIs with ASP.NET Core
Logging is the recording of application events and diagnostic information for later inspection.
- How it is used
- Records web API events for later investigation, monitoring, and compliance.
- How deep it goes
- Defines logs and works through controller entries, severity levels, structured storage, file output, and verification.
- Examples
- Uses a board-game controller message, a Visual Studio Output entry, a LogEvents table, and a daily rolling file.
- What you can do after
- Operate/configure it by writing ILogger entries, setting Serilog destinations and levels, and checking the recorded events.
ASP.NET Core in Action, 3e
A structured log is a log record whose message details are represented as named fields, commonly as key-value pairs.
- How it is used
- Uses named log fields to investigate production errors and search or filter recorded events.
- How deep it goes
- Explains positional message-template values, provider-dependent output, Seq setup, and scopes; does not prescribe one universal record format.
- Examples
- Shows a recipe-count Information log, a missing-recipe warning with JSON-like fields, and logs inspected in Seq.
- What you can do after
- Apply it via ILogger<T> and Seq to capture named values and search logs by their properties.
Think Like a CTO
Logging is the recording of system or application events in persistent logs for monitoring, diagnosis, auditing, or analysis.
- How it is used
- Uses logs to monitor production, diagnose faults, audit activity, and investigate possible security breaches.
- How deep it goes
- Develops collection, review, data-handling, and incident-use decisions without specifying log formats or implementation code.
- Examples
- Illustrates risks with clear-text passwords in request logs and diagnosis with web-application SQL errors pointing toward database trouble.
- What you can do after
- Operate/configure it by centralizing and reviewing logs, masking sensitive values, and documenting signals that require action.
Delivering Machine Learning Projects: From design to deployment
Logging is the recording of software or system events, states, and messages for operational analysis and troubleshooting.
- How it is used
- Supports production acceptance and troubleshooting by making system activity traceable for technical support.
- How deep it goes
- Defines operational goals and event categories but does not specify log schemas, instrumentation APIs, or alert thresholds.
- Examples
- Illustrates database connections, user logins, data updates, model decisions, and Splunk receiving model-server and data-subsystem logs.
- What you can do after
- Practice/perform it by planning production log coverage, retention, and support alerts, then checking inherited ML systems for gaps.
Read how Delivering Machine Learning Projects: From design to deployment explains log →
Google Anthos in Action
Logging is the recording of system and application events for analysis, troubleshooting, and auditing.
- How it is used
- Supports Kubernetes operations, workload investigation, and security observability through recorded system, application, and access events.
- How deep it goes
- Distinguishes log sources, retrieval, and forwarding paths, without detailing log formats or analysis procedures.
- Examples
- Uses Kubernetes service and workload logs, pod output, stdout, and /var/log/syslog as concrete sources.
- What you can do after
- Operate log retrieval through the Connect Agent and kubectl logs, and forward node logs to Cloud Logging with the operations suite agent enabled.
Acing the Certified Kubernetes Administrator Exam, Second Edition
A log is time-based behavioral data recorded as text to provide information about events or problems in a running system.
- How it is used
- Uses application logs to troubleshoot Kubernetes problems and detect failures in running containers.
- How deep it goes
- Traces stdout and stderr to node log files and demonstrates retrieval for one or all pod containers.
- Examples
- Uses a MySQL CrashLoopBackOff diagnosis and a two-container BusyBox pod to demonstrate log retrieval.
- What you can do after
- Diagnose pod failures by retrieving container logs with kubectl and identifying error messages.
Read how Acing the Certified Kubernetes Administrator Exam, Second Edition explains log →
Bootstrapping Microservices, Second Edition: With Docker, Kubernetes, GitHub Actions, and Terraform
Logging is the practice of recording runtime events, messages, and diagnostic information generated by software.
- How it is used
- Uses event records to monitor microservice behavior and support investigation of problems.
- How deep it goes
- Explains console output, log selection, aggregation, and retrieval without requiring a sophisticated logging system.
- Examples
- Shows console output, Docker Compose log capture and search, and Kubernetes pod-log retrieval.
- What you can do after
- Operate Docker Compose, kubectl, or Stern to collect and inspect microservice logs.
Secrets of the JavaScript Ninja, Second Edition
The practice of recording useful runtime information to help understand program behavior or diagnose problems.
- How it is used
- Records useful runtime information to understand program behavior and investigate bugs.
- How deep it goes
- Defines logging and works through proxy get and set traps, demonstrating property access logging without covering broader instrumentation.
- Examples
- Uses a Ninja skillLevel getter and setter, then a makeLoggable proxy that reports reads and writes.
- What you can do after
- Apply it via JavaScript Proxy traps to log property reads and writes without scattering statements through domain code.
Read how Secrets of the JavaScript Ninja, Second Edition explains log →
Microsoft Azure in Action
Logging is the practice of recording system or application events and diagnostic information.
- How it is used
- Diagnoses VM problems, audits Azure actions, and investigates recorded AI decisions.
- How deep it goes
- Distinguishes VM log types and demonstrates centralized queries for investigating unexpected restarts.
- Examples
- Uses VM heartbeat gaps, Windows Event Logs, Linux syslog, Azure activity records, and logged recommendation rationales.
- What you can do after
- Diagnose unexpected VM restarts by correlating heartbeat, operating-system, and activity records.
gRPC Microservices in Go
A log is a recorded event or message describing activity in a software system.
- How it is used
- Uses application logs to investigate live-service problems and track anomalies across microservices.
- How deep it goes
- Works through structured log fields and a context-aware Go formatter, then identifies a cluster logging pipeline.
- Examples
- Shows order-ID metadata, a CreateOrder log entry, and trace and span IDs in formatted output.
- What you can do after
- Apply it via logrus to produce filterable contextual logs, then search related entries in a logging backend.
Learn Haskell by Example
An event log is an ordered record of events produced during computation.
- How it is used
- Collects synchronization outcomes during effectful file operations and optionally reports them through a command-line interface.
- How deep it goes
- Defines event constructors, a list wrapper, accumulation instances, and formatted output, but does not develop persistent log storage.
- Examples
- Uses file-copy success, IOException failure, skipped files, and a verbose synchronization run as concrete examples.
- What you can do after
- Build it from scratch with typed entries, WriterT accumulation, derived combination instances, and optional formatted printing.
Learn Go with Pocket-Sized Projects
A structured log message represents log information as machine-parseable fields with defined meanings rather than as unstructured prose.
- How it is used
- Uses machine-parseable events to feed dashboards and operational measurements.
- How deep it goes
- Explains JSON fields and Marshal, including exported-field requirements, but defers time validation and broader service implementation.
- Examples
- Uses a JSON warning containing time, level, and message fields.
- What you can do after
- Apply structured logging by encoding records with encoding/json or choosing Go's slog logger for services.
Pro ASP.NET Core 7, Tenth Edition
The practice of recording informational, diagnostic, warning, and error messages generated by software.
- How it is used
- Records application state to track errors, monitor performance, and help diagnose problems.
- How deep it goes
- Works through providers, categories, severity levels, class and Program.cs logging, and console verification.
- Examples
- Logs request start and completion for a population endpoint and startup pipeline configuration.
- What you can do after
- Apply it via ILogger<T> or app.Logger to emit categorized, leveled messages and verify them in console output.
MongoDB 8.0 in Action, Third Edition
Logging is the systematic recording of system activities, user actions, and application events for later review and analysis.
- How it is used
- Uses logs to troubleshoot database issues, check performance, and detect security problems.
- How deep it goes
- Details log categories, retention, access, and filtering, but does not specify a full analysis procedure.
- Examples
- Shows database, audit, trigger, and mongosh logs, plus Atlas CLI downloads and mongosh log paths.
- What you can do after
- Diagnose database problems and investigate performance bottlenecks or potential security issues by reviewing logs.
Read how MongoDB 8.0 in Action, Third Edition explains log →
Related concepts
- Proxyused by · A JavaScript Proxy is an object that intercepts operations on a target object through trap functions defined by a handler.
- cybersecurity forensicsused by · Cybersecurity forensics is the systematic collection, preservation, and analysis of digital evidence to reconstruct events and investigate security-related activity.
- monitoringkind of · Monitoring is the ongoing observation and measurement of a system’s behavior, state, or performance to assess its operation and detect changes or problems.
- unstructured loggingcontrasts with · Unstructured logging records application events as free-form human-readable text without a predefined schema or standardized queryable fields.
- Elasticsearchused by · Elasticsearch is a distributed search and analytics engine that indexes data for searching, retrieval, and analysis.
- JSONuses · JSON is a standardized, language-independent text format for representing structured data using objects, arrays, strings, numbers, Boolean values, and null.
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