LinkedIn — Detailed

flowchart TB
  subgraph Clients
    Web
    Mobile
  end

  subgraph Edge
    CDN
    LB
    GW[REST + GraphQL]
  end

  subgraph Profile
    PSVC[Profile Service]
    PDB[(Profiles - Espresso<br/>document store)]
    SKILL[Skills / Endorsements]
  end

  subgraph Graph[Economic Graph]
    CONN[Connection Service]
    GDB[(Distributed Graph<br/>LiquidGraph)]
    DEG[Degree / shortest path]
  end

  subgraph Search
    PEO[People Search]
    JOB[Jobs Search]
    GAL[Galene / Lucene search]
    QU[Query understanding]
  end

  subgraph Feed
    HOMEFEED[Home Feed]
    AGG([Aggregator])
    RANK([ML Ranker])
    CANDS([Candidate Gen<br/>followed + suggested])
  end

  subgraph Jobs
    JOBS[Jobs Service]
    JDB[(Jobs DB)]
    REC([Job Recommendations])
    ALERT[Job Alerts]
    APPLY[Easy Apply / ATS]
  end

  subgraph Msg
    INMAIL[InMail]
    DM[Messaging Service]
    WS[WebSocket gateway]
  end

  subgraph Async
    KAFKA[[Kafka pipelines]]
    SAMZA([Samza / Flink])
    EMB([Embeddings - Pinot])
    LAKE[(Data lake)]
  end

  subgraph ML
    PYM[People You May Know - PYMK]
    PYMW[People You May Work With]
    NOTIF([Notifications Ranker])
    ADS[Ads / Sponsored]
  end

  Clients --> CDN --> LB --> GW
  GW --> Profile --> PDB
  GW --> Graph --> GDB
  GW --> Search --> GAL
  GW --> Feed --> AGG --> CANDS
  CANDS --> Graph
  Feed --> RANK
  GW --> Jobs --> JDB
  GW --> Msg --> WS
  Profile --> KAFKA
  Graph --> KAFKA
  Jobs --> KAFKA
  KAFKA --> SAMZA --> EMB
  EMB --> PYM
  EMB --> JOBS
  PYM --> CANDS
  ADS --> RANK

    classDef client fill:#dbeafe,stroke:#1e40af,stroke-width:1px,color:#0f172a;
    classDef edge fill:#cffafe,stroke:#0e7490,stroke-width:1px,color:#0f172a;
    classDef service fill:#fef3c7,stroke:#92400e,stroke-width:1px,color:#0f172a;
    classDef datastore fill:#fee2e2,stroke:#991b1b,stroke-width:1px,color:#0f172a;
    classDef cache fill:#fed7aa,stroke:#9a3412,stroke-width:1px,color:#0f172a;
    classDef queue fill:#ede9fe,stroke:#5b21b6,stroke-width:1px,color:#0f172a;
    classDef compute fill:#d1fae5,stroke:#065f46,stroke-width:1px,color:#0f172a;
    classDef storage fill:#e5e7eb,stroke:#374151,stroke-width:1px,color:#0f172a;
    classDef external fill:#fce7f3,stroke:#9d174d,stroke-width:1px,color:#0f172a;
    classDef obs fill:#f3e8ff,stroke:#6b21a8,stroke-width:1px,color:#0f172a;
    class WS edge;
    class GW,PSVC,SKILL,CONN,DEG,PEO,JOB,GAL,QU,HOMEFEED,JOBS,APPLY,INMAIL,DM,PYM,PYMW,ADS service;
    class PDB,GDB,JDB,LAKE datastore;
    class KAFKA queue;
    class AGG,RANK,CANDS,REC,SAMZA,EMB,NOTIF compute;
    class ALERT obs;

Distinctive parts

• Economic Graph: members, companies, skills, jobs as nodes. Used for PYMK, job match, talent insights.
• People You May Know (PYMK): ML-driven candidate gen using 2nd/3rd-degree contacts, school/company overlap, embeddings.
• Galene = LinkedIn's Lucene-based search platform (now superseded internally) with custom relevance for "name + headline + company" queries.
• Espresso = LinkedIn's distributed document store (Helix-managed, Avro schemas).
• Voldemort historically for KV; replaced by Espresso + Venice.

Messaging

• InMail (one-off to non-connections, paid) vs Direct Messaging (connections).
• Same kind of WS + inbox queue as WhatsApp but simpler (no E2E).

Jobs

• Index = job postings + filters (location, exp, remote).
• Recommendations combine collaborative + content (skills, profile embedding).

Trade-offs

• Strongly typed graph unlocks rich features but ops complexity.
• Multi-DC writes for profile but mostly single-region for graph hot path.
• Privacy & compliance (GDPR, recruiter visibility) drive complex ACL.

Glossary & fundamentals

Concepts referenced in this design. Each row links to its canonical page; the tag column shows whether it is a high-level (HLD) or low-level (LLD) concept.

Tag	Concept	What it is	Page
HLD	CDN	edge caching for static assets	cdn
HLD	Pub/Sub & message brokers	topics, consumer groups, delivery semantics	pub-sub-pattern
HLD	Realtime protocols	WS / SSE / polling / gRPC streaming	realtime-protocols
HLD	Batch & stream processing	Lambda vs Kappa, watermarks, windows	batch-stream-processing
LLD	REST API design	verbs, statuses, pagination, errors	rest-api-design