Results for “data”

Query and filter Datadog logs from the shell using the Composio CLI, enabling scoped log searches, pivoting across services and environments, and exporting structured JSON for downstream analysis.

Deploys Datadog Cloud SIEM, CSM, and Workload Protection to detect threats, enforce compliance, and respond to security events across cloud and hybrid infrastructure.

Implements database replication, failover, backups, connection pooling, and monitoring for production PostgreSQL, MySQL, and MongoDB systems.

Diagnose and observe an Oxla distributed analytical database using system catalog tables, Prometheus metrics, runtime log-level changes, and troubleshooting workflows for slow queries, node health, and memory/OOM pressure. Also covers debugging Oxla's external data sources, including the Redpanda/Kafka ingestion path.

Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Self-hosted observability platform for LLM applications, providing tracing, evaluation, datasets, experiments, and real-time monitoring to debug and improve AI systems.

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Send custom logs to Azure Monitor Log Analytics workspace using the Logs Ingestion API and Python SDK.

Manage Kuma service mesh by discovering meshes, dataplanes, and policies via the Kuma API, then analyzing configuration and producing structured reports.

Deep-dive analysis of AWS RDS instances using Performance Insights, event subscriptions, proxy health, and global database status, with parallel execution and anti-hallucination guardrails.

Profiles application performance across database queries, API call chains, memory usage, bundle sizes, network waterfalls, and frontend rendering, then produces ranked optimization recommendations with estimated impact.

Detect cyber attacks targeting OT historian servers (OSIsoft PI, Ignition, Wonderware) that sit at the IT/OT boundary and serve as pivot points for lateral movement between enterprise and control networks, including data manipulation, unauthorized queries, and exploitation of historian-specific vulnerabilities.

Debug, evaluate, and monitor LLM applications with tracing, datasets, and built-in evaluators.

Instrument a web application to send telemetry data to Azure Application Insights for observability of app health.

Diagnose and eliminate performance bottlenecks across web, API, database, and code with load testing, profiling, and optimization techniques.

Guides reliable application deployment with CI/CD pipelines, zero-downtime strategies, rollback plans, and post-deploy monitoring.

Instrument LLM applications with Langfuse for tracing, prompt versioning, evaluation, and dataset management across Python and JavaScript SDKs.

Measure Jetson DRAM and NvMap usage, capture before/after baselines, and verify memory reclamation with live audit data.

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

Guides developers through capturing diagnostic artifacts to diagnose production .NET performance issues, including tool selection and data collection across Windows, Linux, containers, and Kubernetes.

Queries and analyzes PRTG Network Monitor data via its HTTP API, covering sensor status, device trees, alerts, and bandwidth metrics.

Diagnoses and validates Redpanda Connect pipelines using linting, dry-run connection tests, logging, metrics, tracing, and health endpoints, including enterprise feature troubleshooting.

Diagnoses Redpanda broker and cluster health using debug bundles, metrics endpoints, logs, CPU profiling, and partition/raft checks, with triage playbooks for common failure modes.

Diagnoses and reduces Qdrant memory usage by analyzing resident memory, page cache, and providing optimization techniques like quantization, on-disk storage, and async_scorer.

Collect local and remote Redpanda diagnostics bundles and inspect broker process info using the `rpk debug` command group, including triaging enterprise features from captured logs, metrics, and profiles.

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Manages and monitors dbt projects, model runs, and test results via dbt CLI and dbt Cloud API, covering run status, test failures, source freshness, and manifest analysis.