'monitoring' 검색 결과

Turn Cloud Monitoring metric definitions and resource filters into validated PromQL queries, a language for querying monitoring data. Choose suitable aggregation functions, preserve supplied resource names, and format queries for use in Cloud Monitoring.

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• Convert Cloud Monitoring metric definitions into PromQL
• Filter monitoring queries to specific resources
• Choose aggregations that match metric types

Turn existing PromQL or ListTimeSeries queries into Cloud Monitoring chart definitions in textproto, a text format for Protocol Buffers. Generate readable titles, axis labels, units, and plot types, then validate the resulting widget files.

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• Create chart definitions from existing monitoring queries
• Set chart titles, axis labels, and units
• Prepare widget definitions for dashboard provisioning

Configure GKE logging, metrics collection, dashboards, and alerts with Cloud Logging, Cloud Monitoring, and managed Prometheus. Diagnose missing measurements, collection failures, permission errors, and alert rule problems to identify appropriate configuration changes.

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• Setting up GKE logging and metrics collection
• Investigating missing Prometheus metrics
• Planning dashboards and alerts for cluster health

Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c). Covers CCTV and video surveillance, employee monitoring, location tracking, internet monitoring, and behavioural analytics. Applies EDPB WP248rev.01 criteria for systematic monitoring of publicly accessible areas. Keywords: DPIA, large-scale monitoring, CCTV, employee monitoring, systematic monitoring, surveillance, location tracking.

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Creates Terraform configuration for Google Cloud Monitoring notification channels, including email, Slack, and Pub/Sub, and attaches channels to existing alert policies. It also checks Pub/Sub topic compatibility and publishing permissions when inspecting the cloud environment.

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• Configuring email or Slack alert notifications
• Adding notification channels to existing alert policies
• Checking Pub/Sub topic compatibility and publishing permissions

Build Cloud Monitoring requests from metric definitions and resource details. Generate JSON parameters, filters, and aggregation settings for retrieving time series data, then validate the request against the live API.

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• Build JSON requests to retrieve monitoring data
• Filter metrics for specific VMs or databases
• Set aggregation intervals and resource grouping

Set up host-based intrusion detection to monitor changes on Windows and Linux endpoints. Configure Wazuh agents, file integrity checks, registry monitoring, alert rules, and automated responses, with guidance on exclusions and centralized security monitoring.

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• Deploying Wazuh agents on Windows and Linux
• Monitoring critical files and registry changes
• Planning change detection for compliance requirements

Find relevant Google Cloud monitoring metrics for a service or resource. Retrieves current metric definitions through the API, filters them by the requested concepts, and presents selected metrics with their names, data types, units, and monitored resources.

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• Find CPU metrics for Compute Engine
• Identify Cloud Storage write throughput and request metrics
• Check metric data types and units

Implements email and internet monitoring compliance in the workplace per Barbulescu v Romania (ECHR Grand Chamber), EDPB guidance, and national labour law. Covers acceptable use policies, legitimate expectation of privacy, proportionality testing, and content vs metadata monitoring. Keywords: email monitoring, Barbulescu, workplace privacy, internet monitoring, acceptable use policy, ECHR, proportionality.

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Guides DPIA for workplace monitoring including email surveillance, internet usage monitoring, CCTV, GPS tracking, and keystroke logging. Covers GDPR Art. 88 employment context provisions, WP29 Opinion 2/2017 on data processing at work, and proportionality balancing for employee monitoring. Keywords: employee surveillance, workplace monitoring, DPIA, Art. 88, WP29 Opinion 2/2017, CCTV, email monitoring, GPS tracking.

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Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.

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Set up Zeek to observe network traffic and produce structured logs for security analysis. Create custom detection scripts, investigate suspicious DNS activity and repeated external connections, and forward logs to a central security monitoring system.

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• Set up passive monitoring at key network points
• Create detection scripts for suspicious DNS and repeated connections
• Forward Zeek logs to a central security monitoring system

Deploy osquery on Windows, macOS, and Linux to inspect processes, listening ports, software, and system settings using SQL, a database query language. Configure scheduled checks and centralized management to support threat hunting and compliance monitoring.

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• Deploying osquery across Windows, macOS, and Linux
• Investigating suspicious processes and network connections with SQL
• Periodically checking software inventories and system settings

Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.

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• Investigate AI application problems using execution traces
• Evaluate answer quality across a test dataset
• Compare prompts and models through experiments

Diagnose GKE TPU slice creation failures caused by shared nodes. Check slice status, partition labels, and monitoring data to identify conflicting resource groups, then provide resolution steps for the user to apply.

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• Investigating node overlap behind SliceCreationFailed
• Finding slices that share nodes across partition shapes
• Checking whether resource conflicts existed at incident time

Investigate slow TPU training on GKE by comparing diagnostic events with one-minute monitoring metrics. Separate memory or CPU bottlenecks from hardware and network issues, and identify the appropriate next steps.

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• Investigating slower TPU training without pod crashes
• Checking PERFORMANCE_DEGRADATION events
• Separating resource bottlenecks from infrastructure issues

Monitor TPU workloads on GKE using system metrics and PromQL, a metrics query language. Check utilization, memory, node availability, and interruptions to investigate infrastructure issues and calculate average recovery times and intervals between interruptions.

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• Checking TPU utilization and memory usage
• Investigating node and node pool availability
• Tracing maintenance and preemption interruptions

Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.

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• Investigate AI application problems using execution traces
• Evaluate answer quality across a test dataset
• Compare prompts and models through experiments

Ongoing vendor privacy compliance monitoring program. Covers annual reassessment procedures, continuous monitoring signals, contract renewal privacy triggers, performance metrics, KPIs, and vendor governance reporting dashboards.

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Conducts Data Protection Impact Assessments for employee monitoring systems per EDPB Guidelines 3/2019 on workplace data processing. Covers video surveillance, email monitoring, GPS tracking, keystroke logging, and productivity tools. Applies proportionality testing under Art. 35 GDPR. Keywords: DPIA, employee monitoring, surveillance, proportionality, EDPB, workplace privacy, keystroke logging, GPS tracking.

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Define monitoring strategy, metrics collection, and alerting thresholds during PRD v0.8 Deployment & Ops. Triggers on requests to set up monitoring, define alerts, or when user asks "what should we monitor?", "alerting strategy", "observability", "metrics", "SLOs", "dashboards", "monitoring setup". Outputs MON- entries with monitoring rules and alert configurations.

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Checkly is a synthetic monitoring platform that runs API checks and Playwright browser checks from locations worldwide and lets you define them as code with the Checkly CLI. Use when a developer asks to set up monitoring as code, write API or browser checks, configure Slack or email alerts, run checks in CI after a deploy, or turn Playwright tests into production monitors.

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Set up or review production error monitoring to capture unhandled errors, failed requests, and performance signals. Check event context, release labels, and alert routing so teams receive useful information when problems occur.

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• Setting up error monitoring for a new production app
• Investigating errors that monitoring fails to capture
• Reviewing critical alerts and on-call routing

Configure Prometheus to collect and store operational metrics from infrastructure and applications. Covers collection schedules, alert rules, automatic discovery of monitored services, and troubleshooting checks to help establish and maintain monitoring.

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• Setting up infrastructure and application monitoring
• Configuring metric collection intervals and retention
• Designing alert rules