Cloud computing promises easy development and deployment of
\nlarge-scale, fault tolerant, and highly available applications. Cloud
\nstorage services are a key enabler of this, because they provide
\nreliability, availability, and fault tolerance via internal mechanisms
\nthat developers need not reason about. Despite this, challenges
\nremain for distributed cloud applications developers. They still need
\nto make their code robust against failures of the machines running the
\ncode, and to reason about concurrent access to cloud storage by
\nmultiple machines.<\/p>\n
We address this problem with a new abstraction, called locks with
\nintent, which we implement in a client library called Olive. Olive
\nmakes minimal assumptions about the underlying cloud storage, enabling
\nit to operate on a variety of platforms including Amazon DynamoDB and
\nMicrosoft Azure Storage. Leveraging the underlying cloud storage,
\nOlive’s locks with intent offer strong exactly-once semantics for a
\nsnippet of code despite failures and concurrent duplicate executions.<\/p>\n
To ensure exactly-once semantics, Olive incurs the unavoidable
\noverhead of additional logging writes. However, by decoupling
\nisolation from atomicity, it supports consistency levels ranging from
\neventual to transactional. This flexibility allows applications to
\navoid costly transactional mechanisms when weaker semantics suffice.
\nWe apply Olive’s locks with intent to build several advanced storage
\nfunctionalities, including snapshots, transactions via optimistic
\nconcurrency control, secondary indices, and live table
\nre-partitioning. Our experience demonstrates that Olive eases the
\nburden of creating correct, fault-tolerant distributed cloud
\napplications.<\/p>\n","protected":false},"excerpt":{"rendered":"
Cloud computing promises easy development and deployment of large-scale, fault tolerant, and highly available applications. Cloud storage services are a key enabler of this, because they provide reliability, availability, and fault tolerance via internal mechanisms that developers need not reason about. Despite this, challenges remain for distributed cloud applications developers. 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