'elasticsearch' 검색 결과

Build or tune a monitoring pipeline that learns normal user behavior from activity logs. Use Elasticsearch or OpenSearch to score unusual activity, compare colleagues in similar roles, and combine warning signs into insider threat alerts.

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• Building continuous monitoring for insider threats
• Scoring unusual logins and large downloads
• Comparing behavior across similar job roles

Build and maintain Elasticsearch search and analytics systems with guidance on queries, field types, and aggregations. Plan index migrations, automate data retention, diagnose cluster allocation problems, and investigate slow searches.

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• Designing full-text search and autocomplete
• Aggregating logs and time-series data
• Planning index migrations and data retention

Create monitoring dashboards for Grafana, SigNoz, and similar platforms. Choose metrics around operational questions, organize panels by purpose, and define clear titles, units, filters, and thresholds to help operators assess health and bottlenecks.

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• Build a Kafka monitoring dashboard
• Monitor Elasticsearch health and performance
• Track API gateway latency and errors

Elasticsearch provider for obz. Supports log search and trace operations using Elasticsearch Query DSL (Lucene-based). Requires --index flag. This skill should be used when the user mentions "Elasticsearch", "obz -p es", or needs to search logs or traces from an Elasticsearch cluster.

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Amazon Elasticsearch integration. Manage data, records, and automate workflows. Use when the user wants to interact with Amazon Elasticsearch data.

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Configure and use Elasticsearch for full-text search, custom analyzers, aggregations, and index management. Use when a user needs to design search mappings, write complex queries, build aggregation pipelines, tune relevance scoring, or optimize index performance for search workloads.

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Expert en Elasticsearch (indexing, mappings, aggregations, Kibana, DSL queries)

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Integrate Elasticsearch and implement search index Sync patterns in NestJS. Use when integrating Elasticsearch or implementing search index sync in NestJS.

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Manages Volcano Engine (Volcengine/火山引擎) ESCloud and CloudSearch clusters for lifecycle operations and Elasticsearch/OpenSearch data-plane tasks. Use when the user mentions ESCloud, CloudSearch, or Elasticsearch/OpenSearch on Volcengine.

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Guide the official Elasticsearch Python client for cluster connections, generated APIs, async code, bulk ingestion, query DSL, ES|QL, optional integrations, and runtime troubleshooting.

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Expert guide for full-text search engines (Typesense, Meilisearch, Elasticsearch), faceted search, and autocomplete / Panduan ahli mesin pencarian full-text (Typesense, Meilisearch, Elasticsearch), pencarian berfaset, dan autocomplete.

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Elasticsearch patterns -- client setup, index management, search DSL, aggregations, vector search, bulk operations, deep pagination

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Elasticsearch search and analytics — mappings, queries, and cluster health — use when building search or log analytics.

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Elasticsearch guidance — index design, mappings, query DSL, aggregations, cluster operations, and performance tuning.

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Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.

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Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.

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Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.

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Set up MISP to collect threat feeds and centrally manage indicators such as suspicious IP addresses and domains. Configure automated synchronization, connect related findings, and export indicators to security monitoring platforms or blocklists.

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• Centralizing threat indicators from multiple feeds
• Deploying MISP with Docker
• Automating threat feed synchronization

Build an OpenCTI pipeline that adds external context to indicators of compromise, such as suspicious IP addresses. Connect intelligence services, relate indicators to known attackers and campaigns, and score confidence to help analysts prioritize investigations.

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• Deploying OpenCTI and configuring enrichment connectors
• Automatically adding context to suspicious IP addresses and domains
• Relating indicators to known attackers and campaigns

Build a central platform for collecting, analyzing, and sharing cyber threat information. Connect MISP, OpenCTI, TheHive, and Cortex to import feeds, add context to suspicious indicators, manage cases, and track platform activity.

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• Build a central threat intelligence platform
• Automate threat feed ingestion
• Add context to suspicious IP addresses and domains

Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Prepper); ai-assistant (natural language data exploration, incident investigation, root cause analysis). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, Solr, vector/k-NN/semantic/hybrid search, RAG, log analytics, PPL, trace analytics, ISM, FAISS, HNSW, Migration Assistant, UltraWarm, OR1, query my data, analyze logs, investigate errors, root cause analysis.

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Deploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis. Configure log pipelines, create visualizations, and implement log-based monitoring. Use when centralizing logs, implementing search functionality, or building log analytics platforms.

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将基于旧版Nest库（1.x）的C#代码迁移升级到新版Nest库（7.17.5），涵盖API变更、查询语法重构、Source过滤、聚合更新及MultiSearch逻辑重写。

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Mapping design, query optimization, aggregation patterns, index lifecycle management, and search relevance tuning.

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