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This commit is contained in:
31
note/slides/Makefile
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31
note/slides/Makefile
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@@ -0,0 +1,31 @@
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MARP ?= npx @marp-team/marp-cli
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SRC := seaweedfs-production-setup.md
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PDF := $(SRC:.md=.pdf)
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HTML := $(SRC:.md=.html)
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PPTX := $(SRC:.md=.pptx)
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FLAGS := --allow-local-files
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.PHONY: all pdf html pptx watch clean
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all: pdf
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pdf: $(PDF)
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html: $(HTML)
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pptx: $(PPTX)
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$(PDF): $(SRC)
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$(MARP) $(SRC) --pdf $(FLAGS) -o $@
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$(HTML): $(SRC)
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$(MARP) $(SRC) --html $(FLAGS) -o $@
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$(PPTX): $(SRC)
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$(MARP) $(SRC) --pptx $(FLAGS) -o $@
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watch:
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$(MARP) $(SRC) --watch --html $(FLAGS)
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clean:
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rm -f $(PDF) $(HTML) $(PPTX)
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118
note/slides/seaweedfs-production-setup.md
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118
note/slides/seaweedfs-production-setup.md
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---
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marp: true
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theme: default
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paginate: true
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---
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# SeaweedFS Production Setup
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A walkthrough of the recommended deployment topology
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- Storage layer
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- File access layer
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- Backend operations
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- Erasure coding for durability
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---
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---
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# Storage Layer
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**3 Masters + Volume Servers**
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- **Masters (run 3)**
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- Form a Raft quorum; tolerate 1 failure
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- Track volume locations and cluster topology
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- Lightweight; not on the data path for reads/writes after lookup
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- **Volume Servers (scale out)**
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- Hold the actual needle data on local disks
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- Add more servers for capacity and throughput
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- Heartbeat to masters; clients talk to them directly for I/O
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Rule of thumb: start with 3 masters, then grow volume servers with data.
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---
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# File Access Layer
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**Filer + DB for metadata**
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- Filer serves POSIX-like directory and file metadata
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- Metadata store options: PostgreSQL, MySQL, Redis, Cassandra, TiKV, etc.
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- Run **3 filers** for HA
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- Filers are stateless relative to each other — state lives in the DB
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**S3 Servers**
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- Expose the S3 API on top of the filer
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- Scale the count based on throughput requirements
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- Can be co-located with filers or run independently
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---
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# Backend Operations
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**1 Admin Server + a few Workers**
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- **Admin server (1 is enough)**
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- Coordinates background jobs: balancing, EC encoding, vacuum, replication fixes
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- **Not on the data path** — a restart does not affect object store reads/writes
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- No HA required for normal operation
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- **Workers (a few)**
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- Execute long-running tasks issued by the admin server
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- Horizontally scalable based on maintenance workload
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Keeps housekeeping off the hot path.
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---
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# Production Topology Summary
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| Component | Count | Role |
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|----------------|----------------------|-----------------------------------|
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| Master | 3 | Raft quorum, topology, volume map |
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| Volume Server | N (scale out) | Stores data needles |
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| Filer | 3 | Metadata gateway |
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| Metadata DB | HA cluster | Persists filer metadata |
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| S3 Server | N (by throughput) | S3 API frontend |
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| Admin | 1 | Background job coordinator |
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| Worker | A few | Executes admin-scheduled tasks |
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---
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# Erasure Coding for Durability
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Prefer **many volume servers** so EC shards spread across failure domains.
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**Example: 8 volume servers, EC 5+3**
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- Each volume becomes 5 data shards + 3 parity shards
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- Shards are placed on 8 distinct volume servers
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- **Tolerates up to 3 simultaneous volume server failures**
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- Storage overhead: 1.6x vs 3x for full replication
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```
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Volume -> [D1][D2][D3][D4][D5] + [P1][P2][P3]
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| | | | | | | |
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VS1 VS2 VS3 VS4 VS5 VS6 VS7 VS8
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```
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More volume servers = more EC layouts available (e.g. 10+4, 6+3).
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---
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# Getting Started Checklist
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1. Provision 3 master nodes (small boxes are fine)
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2. Provision volume servers sized to your data footprint
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3. Stand up an HA metadata DB, then 3 filers pointing at it
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4. Add S3 servers sized to required throughput
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5. Run 1 admin + a few workers for background maintenance
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6. Once you have enough volume servers, enable EC (e.g. 5+3 on 8 servers)
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|
||||
Scale each layer independently as usage grows.
|
||||
Reference in New Issue
Block a user