Results for “metrics”

Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources using the Azure Monitor Query SDK for Java.

Export OpenTelemetry traces, metrics, and logs to Azure Monitor/Application Insights using the deprecated exporter or the recommended autoconfigure package.

Add EAS Observe to an Expo project for startup, navigation, and custom-event performance metrics, query them via the EAS CLI, and interpret the results.

Track and visualize ML training experiments with Trackio, including logging metrics, firing alerts, and retrieving data via CLI. Supports real-time dashboards, webhook alerts, and HF Space syncing.

Export OpenTelemetry traces, metrics, and logs to Azure Application Insights using Python.

Run evaluation tasks against a NeMo Platform server using the Evaluator plugin CLI and Python SDK.

Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization.

Queries video analytics incidents, alerts, metrics, and sensor data from Elasticsearch via the VA-MCP server.

Configures GKE observability with Cloud Logging, Cloud Monitoring, and managed Prometheus for monitoring, logging, and metrics collection.

Analyze AWS resource health, diagnose issues from CloudWatch logs and metrics, and create a remediation plan for identified problems.

Structure board meetings, investor updates, and executive communication that builds trust and drives decisions.

Audits Vercel projects for cost and performance optimization by collecting metrics, scanning code, and producing ranked recommendations grounded in data.

Generates a compact HTML KPI digest from Adobe Analytics, showing how key metrics changed over a period and what drove the movement.

Guides monitoring and observability setup for Qdrant vector search deployments, including Prometheus scraping, health checks, and metric-based debugging of production issues.

Generates a concise, executive-ready performance summary covering key metrics, trends, and what's driving movement, using Adobe Analytics data.

Evaluates RAG pipelines using a filesystem-based benchmark with corpus/ and train.json, running evaluate_rag.py to tune retrieval and generation flags and interpret RAGAS metrics.

Classify AEM 6.5 LTS and AMS workflow issues by symptom, gather relevant logs and metrics, and map to runbooks or Splunk searches.

Generates a compact KPI digest showing how key metrics changed over a period and what's driving the movement, using Customer Journey Analytics data.

Configures dynamic threshold alerting policies for Google Cloud Vertex AI Agent Platform agents, monitoring latency, error rates, and quality metrics using Terraform and PromQL.

Deploy, debug, and operate the RTVI-CV 2D detection/tracking microservice and call its REST API for stream management, health checks, and metrics.

Query EAS Update health metrics from the CLI: crash rates, install/launch counts, unique users, payload size, and embedded vs OTA user splits per channel.

Compares 2–5 audience segments side by side across key metrics, identifying winners, losers, and significant differences to inform product decisions and personalization strategy.

Compares the performance of two or more audience segments across key metrics side by side, using Adobe Analytics data to determine winners, losers, and spreads for each metric.

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics, including VPC Flow Logs, NAT, firewall, threat logs, latency, throughput, and Connectivity Tests.

Guides users through defining goals, metrics, and scope, then runs an autonomous loop of code changes, testing, measuring, and keeping or discarding results for any programming task with a measurable outcome.

Installs and configures the official Google Ads MCP Server to connect AI assistants to Google Ads accounts for querying campaigns and retrieving reporting metrics using natural language.

Audits web performance by measuring Core Web Vitals (LCP, INP, CLS) and supplementary metrics, identifying render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps using Chrome DevTools MCP.