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Dynamo: Amazon’s Highly Available Key-value Store. DeCandia , Hastorun , Jampani , Kakulapati , Lakshman , Pilchin , Sivasubramanian , Vosshall , Vogels. PRESENTED BY: KIMIISA OSHIKOJI. OUTLINE. Amazon Dynamo Architecture Performance. AMAZON. Huge Infrastructure

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dynamo amazon s highly available key value store

Dynamo: Amazon’s Highly Available Key-value Store

DeCandia, Hastorun, Jampani, Kakulapati, Lakshman, Pilchin, Sivasubramanian, Vosshall, Vogels

PRESENTED BY: KIMIISA OSHIKOJI

outline
OUTLINE
  • Amazon
  • Dynamo
  • Architecture
  • Performance
amazon
AMAZON
  • Huge Infrastructure
  • Customer oriented business
  • Reliability is key
dynamo
DYNAMO
  • Data storage system
  • Flexible
  • Automated addition and removal of storage nodes
dynamo query model
DYNAMO-QUERY MODEL
  • Key identifies operations
  • Operations don’t require multiple data items
  • Data to be stored is relatively small
dynamo assumptions
DYNAMO-ASSUMPTIONS
  • Only used by internal Amazon systems
  • No security considerations
  • Limited scalability
dynamo sla
DYNAMO-SLA
  • Service Level Agreement: contract between client and service about their relationship
  • In Amazon a typical client request involves over 100 services who might have dependencies
  • SLA are governed by 99.9th percentile
dynamo design
DYNAMO-DESIGN
  • Focus on correctness of an answer rather than how quickly it can be available
  • Eventually consistent data store
  • Writes can never be rejected
  • 99.9th percentile
  • Zero-hop DHT
architecture storage
ARCHITECTURE-STORAGE
  • Objects stored with a key using:
    • Get(key): locates object with key and returns object or list of objects with a context
    • Put(key, context): places an object at a replica along with the key and context
    • Context: metadata about object
architecture replication
ARCHITECTURE-REPLICATION
  • Data is replicated on N hosts (N is determined by user)
  • Coordinator nodes replicate the data for nodes they are responsible for coordinating
architecture versioning
ARCHITECTURE-VERSIONING
  • Multiple versions can exist
  • Vector clock is used for version control
  • Vector clock size issue
architecture failure
ARCHITECTURE-FAILURE

*Failure are not automatically detected by a central node

performance buffer
PERFORMANCE-BUFFER
  • System can be optimized without sacrificing the 99.9th percentile
  • Buffer usage can decrease latency by a factor of 5 during peak traffic times
performance load distribution
PERFORMANCE-LOAD DISTRIBUTION

*Third strategy is the best in terms of balancing