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Gorilla – Facebook’s Cache for Time Series Data
Facebook operates a huge infrastructure that needs to be constantly monitored for performance and stability. Such monitoring collects huge amounts of data that must be easily accessible to various diagnosis and anomaly detection tools in order to quickly identify and react to possible issues. Many of such parameters can be represented as real-valued time series.…
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Pivot Tracing Part 2
After looking more at Pivot Tracing tool described in my earlier post, I asked myself about the limitations of such monitoring approach. Pivot tracing is not a universal tool, so it appears that there are few problems it does not address well enough. The basic idea of the Pivot Tracing is to collect the information…
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Review – Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems
Debugging can be a nightmare for software engineers, it is even more so in the distributed systems that span many machines in potentially more than one datacenter. Unfortunately, many of the debugging and monitoring techniques for such large system do not differ much from the methods used to debug and monitor simple single-machine software. Logs…
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Review: Implementing Linearizability at Large Scale and Low Latency
In this post I will talk about Implementing Linearizability at Large Scale and Low Latency SOSP 2015 paper. Linearizability, the strongest form of consistency, can be very important in large scale data storage systems, although many such systems either do not implement linearizability or do not fully expose serializable operation to the clients. The later type…
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A Few Words about Inconsistent Replication (IR)
Recently I was reading the “Building Consistent Transaction with Inconsistent Replication” paper. In this paper authors use inconsistently replicated state machine, but yet they are capable of creating a consistent transaction system. So what is Inconsistent Replication (IR)? In the previous posts I summarized Raft and EPaxos. These two algorithms are used to achieve consensus…
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EPaxos: Consensus with no leader
In my previous post I talked about Raft consensus algorithm. Raft has a strong leader which may present some problems under certain circumstances, for example in case of leader failure or when deployed over a wide area network (WAN). Egalitarian Paxos, or EPaxos, discards the notion of a leader and allows each node to be…
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Consensus with Raft Algorithm
When we talk about consensus in a distributed system, we talk about a system consisting of multiple machines that act as one state machine yet capable of surviving failures of some of the system nodes. Consensus algorithms are designed to enforce all distributed nodes have the same state so that the distributed system can tolerate…
I am an assistant professor of computer science at the University of New Hampshire. My research interests lie in distributed systems, distributed consensus, fault tolerance, reliability, and scalability.
@AlekseyCharapko
aleksey.charapko@unh.edu