{
  "schema_version": "0.6.0",
  "paper_id": "network-analysis-microservices-alibaba",
  "page_url": "https://naser.github.io/research-publications/papers/network-analysis-microservices-alibaba/",
  "title": "Network Analysis of Microservices: A Case Study on Alibaba Production Clusters",
  "title_variants": [],
  "authors": [
    "Ghazal Khodabandeh",
    "Alireza Ezaz",
    "Naser Ezzati-Jivan"
  ],
  "author_details": [
    {
      "name": "Ghazal Khodabandeh",
      "orcid": "https://orcid.org/0009-0001-4587-1876",
      "profile_url": "https://dblp.org/pid/374/6434.html"
    },
    {
      "name": "Alireza Ezaz",
      "orcid": "https://orcid.org/0009-0001-4156-2750",
      "profile_url": "https://dblp.org/pid/374/6221.html"
    },
    {
      "name": "Naser Ezzati-Jivan",
      "orcid": "https://orcid.org/0000-0003-1435-6297",
      "profile_url": "https://naser.github.io/"
    }
  ],
  "publication": {
    "year": 2024,
    "venue": "ACM/SPEC International Conference on Performance Engineering (ICPE) Companion",
    "type": "conference paper",
    "publication_date": "2024-05-07",
    "online_date": "2024-05-07",
    "print_date": "2024-05-07",
    "volume": null,
    "issue": null,
    "pages": "67-71",
    "article_number": null,
    "publisher": "ACM",
    "issn": [],
    "isbn": [],
    "crossref_type": "proceedings-article"
  },
  "publication_type": "conference paper",
  "status": "published_with_public_full_text",
  "canonical_source_url": "https://doi.org/10.1145/3629527.3651842",
  "source_record_id": "network-analysis-of-microservices-a-case-study-on-alibaba-production-clusters-0817c2ae9a",
  "identifiers": {
    "doi": "10.1145/3629527.3651842"
  },
  "abstract": null,
  "abstract_source": "Abstract not reproduced; the four-part summary is paraphrased from the verified full text.",
  "abstract_available": false,
  "scholar_eligibility": {
    "eligible": false,
    "basis": "not-eligible",
    "note": "The page is a discovery record; it does not claim Google Scholar article-host eligibility."
  },
  "description": "The paper applies graph community detection and service-graph clustering to expose recurring microservice communication structures in an Alibaba production-cluster snapshot.",
  "evidence_level": "full-text-reviewed",
  "evidence": {
    "source_basis": "full-text-reviewed",
    "coverage": "material paper sections",
    "summary_origin": "AI-assisted catalog editorial summary",
    "review_status": "catalog-reviewed; paper-author approval pending",
    "verified_on": "2026-08-09",
    "sources": [
      {
        "note": "Private full PDF read: pdf-evidence/notes/network-analysis-microservices-alibaba.md"
      },
      {
        "note": "Network-analysis PDF pp. 1-3: Alibaba dataset scale, preprocessing, community algorithms, metrics, seed stability, and graph clustering"
      },
      {
        "note": "Network-analysis PDF pp. 3-5: structural findings, limitations, future work, and implementation repository"
      },
      {
        "note": "Local PDF hash verified in pdf-evidence/extraction-manifest.json"
      }
    ]
  },
  "summary": {
    "core_contribution": "The paper applies graph community detection and service-graph clustering to expose recurring microservice communication structures in an Alibaba production-cluster snapshot.",
    "problem": "Large microservice deployments contain complex call relationships whose structure is difficult to inspect directly. The paper studies graph analysis for exposing communities, dependencies, and similarities among service call graphs.",
    "method": "From an Alibaba production snapshot, the authors retain upper- and downstream-microservice identifiers plus service labels, remove unacceptable rows, construct one call graph per service, detect communities, and cluster graph structures. Greedy Modularity, Louvain, Infomap, and Label Propagation are compared; K-means groups service graphs using node/edge features.",
    "findings": "The one-hour snapshot contains more than 260 million call records, more than 28,000 microservices, and a network spanning about 10,000 bare-metal nodes. Service graphs with at least 50 requests are retained and 300 are randomly selected. On a sample exceeding 13 million records, Louvain has silhouette 0.71 and modularity 0.67, above the alternatives; varying the seed from 0 to 1000 selects the highest-modularity seed. Elbow analysis selects K=5 and graph clustering obtains silhouette 0.6141.",
    "limitations": "Only 300 service graphs and a small set of call-graph attributes are analyzed; response time is not included in edges. The paper does not show causal bottleneck localization, performance improvement, or validation over the full cluster snapshot. Tracer, trace version/format, OS, kernel, runtime, hardware specifications, and replication details are unknown.",
    "future_work": "Add response-time attributes, scale to larger data, compare or combine more community/clustering methods, and predict future network behavior/community formation."
  },
  "tags": [
    "microservices",
    "performance-analysis",
    "observability",
    "social-network-analysis"
  ],
  "keywords": [
    "microservice networks",
    "Alibaba production clusters",
    "service call graphs",
    "community detection",
    "Louvain",
    "Infomap",
    "Label Propagation",
    "graph clustering",
    "K-Means",
    "silhouette score",
    "modularity"
  ],
  "versions": [
    {
      "id": "published-version",
      "label": "Published version",
      "relation": "version-of-record",
      "title": "Network Analysis of Microservices: A Case Study on Alibaba Production Clusters",
      "url": "https://doi.org/10.1145/3629527.3651842",
      "pdf_url": null,
      "status": "published",
      "canonical_for_citation": true
    },
    {
      "id": "public-acm-pdf",
      "label": "Public ACM PDF",
      "relation": "source-record",
      "title": "Network Analysis of Microservices: A Case Study on Alibaba Production Clusters",
      "url": "https://dl.acm.org/doi/pdf/10.1145/3629527.3651842",
      "pdf_url": "https://dl.acm.org/doi/pdf/10.1145/3629527.3651842",
      "status": "public_full_text",
      "canonical_for_citation": false
    }
  ],
  "access": {
    "status": "published_with_public_full_text",
    "note": "The DOI is the canonical citation target. The external source PDF is linked for readers; no PDF is redistributed in this repository.",
    "license": null
  },
  "resources": {
    "code": "https://github.com/ghazalkhb/ICPE2024_DataChallenge",
    "data": null,
    "slides": null,
    "demo": null
  },
  "citation_guidance": {
    "when_to_cite": "Cite this paper when your work uses or compares applying community detection to Alibaba-scale microservice call graphs.",
    "points": [
      "applying community detection to Alibaba-scale microservice call graphs.",
      "the Louvain-versus-Greedy-Modularity/Infomap/Label-Propagation comparison with coverage, modularity, and silhouette metrics.",
      "the K-means service-graph similarity workflow with elbow-selected K=5 and silhouette 0.6141.",
      "as structural-dependency evidence, not as a causal latency or bottleneck-improvement result."
    ],
    "canonical_version_id": "published-version"
  },
  "provenance": {
    "metadata_verified_on": "2026-08-09",
    "metadata_source": [
      "Private full PDF read: pdf-evidence/notes/network-analysis-microservices-alibaba.md",
      "Network-analysis PDF pp. 1-3: Alibaba dataset scale, preprocessing, community algorithms, metrics, seed stability, and graph clustering",
      "Network-analysis PDF pp. 3-5: structural findings, limitations, future work, and implementation repository",
      "Local PDF hash verified in pdf-evidence/extraction-manifest.json"
    ],
    "summary_written_by": "AI-assisted",
    "summary_verified_by": "full-text-grounded catalog review; author approval pending",
    "linked_preprint_record": null,
    "author_order_note": null
  },
  "batch": {
    "phase": 2,
    "batch_label": "expanded forty-paper release",
    "status": "included_in_expanded_catalog",
    "selected_at": "2026-08-09"
  }
}