AWS Lambda: an Introduction and Practical Walkthrough
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This is a guest post from 47Line Technologies.
In our previous post, How to handle failures in DynamoDB – An inside look into NoSQL, we discussed handling failures via Hinted Handoff & Replica Synchronization. We also talked about the advantages of using a Sloppy Quorum and Merkle Trees.
In this last & final part of the series, we will look into Membership and Failure Detection.
In any production environment, node outages are often transient. But it rarely signifies permanent failure and hence there is no need for repair or rebalancing the partition. On the other hand, manual errors might result in the unintentional startup of new DynamoDB nodes. A proper mechanism is essential for the addition and removal of nodes from the DynamoDB Ring. An administrator uses a tool to issue a membership change command to either add/remove a node. The node that picks up this request writes into its persistent store the membership change request and the timestamp.
A gossip-based protocol transfers the membership changes and maintains a consistent view of membership across all nodes. Each node contacts a peer chosen at random every second and the two nodes efficiently reconcile their persisted membership change histories. Partitioning & placement information also propagates via the gossip-based protocol and each storage node is aware of the token ranges its peers are responsible for. This allows each node to forward a key’s read/write operations to the right set of nodes directly.
Ring Membership (Credit)
It’s best to explain with an example: An administrator joins node
A to the ring. He then joins node
B to the ring. Nodes
B consider itself as part of the ring, yet neither would be immediately aware of each other. To prevent these logical partitions, DynamoDB introduced the concept of seed nodes. Seed nodes are fully functional nodes that are discovered via an external mechanism (static configuration or a configuration service) and are known to all nodes. Since each node communicates with the seed node and gossip-based protocol transfer the membership changes, logical partitions are highly unlikely.
Failure detection in DynamoDB is used to avoid attempts to communicate with unreachable peers during
put() operations and when transferring partitions and hinted replicas. For the purpose of avoiding failed attempts at communication, a purely local notion of failure detection is entirely sufficient: node
A may consider node
B failed if node
B does not respond to node
A’s messages (even if
B is responsive to node
C‘s messages). In the presence of a steady rate of client requests generating inter-node communication in the DynamoDB ring, a node
A quickly discovers that a node
B is unresponsive when
B fails to respond to a message; Node
A then uses alternate nodes to service requests that map to
A also periodically retries
B to check for the latter’s recovery. In the absence of client requests to drive traffic between two nodes, neither node really needs to know whether the other is reachable and responsive.
This exhaustive 7-part series detailing every component is sufficient to understand the design and architecture of any NoSQL system. Phew! What an incredible journey it has been these couple of months delving into the internals of DynamoDB. Having patiently read this far, you are amongst the chosen few who have this sort of deep NoSQL knowledge. You can be extremely proud of yourself!
Let’s eagerly await another expedition soon!
Article authored by Vijay Olety.
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