https://github.com/cloudera/flume/blob/master/flume-docs/src/docs/UserGuide/Introduction

=== Reliability
   
  Reliability, the ability to continue delivering events in the face of
  failures without losing data, is a vital feature of Flume. Large
  distributed systems can and do suffer partial failures in many ways -
  physical hardware can fail, resources such as network bandwidth or
  memory can become scarce, or software can crash or run slowly. Flume
  emphasizes fault-tolerance as a core design principle and keeps
  running and collecting data even when many components have failed.
   
  Flume can guarantee that all data received by an agent node will
  eventually make it to the collector at the end of its flow as long as
  the agent node keeps running. That is, data can be *reliably*
  delivered to its eventual destination.
   
  However, reliable delivery can be very resource intensive and is often
  a stronger guarantee than some data sources require. Therefore, Flume
  allows the user to specify, on a per-flow basis, the level of
  reliability required. There are three supported reliability levels:
   
  * End-to-end
  * Store on failure
  * Best effort
   
  .A Note About Reliability
  ******************
  Although Flume is extremely tolerant to machine, network, and software
  failures, there is never any such thing as '100% reliability'. If all
  the machines in a Flume installation were irrevocably destroyed in
  some terrible data center incident, all copies of Flume's data would
  be lost and there would be no way to recover them. Therefore all of
  Flume's reliability levels make guarantees about data delivery 'until
  some maximum number of failures have occurred'. Flume's failure modes
  - in terms of what can fail and what will keep running if they do -
  are described in detail later in this guide.
  ******************
   
  The *end-to-end* reliability level guarantees that once Flume accepts
  an event, that event will make it to the endpoint - as long as the
  agent that accepted the event remains live long enough. The first
  thing the agent does in this setting is write the event to disk in a
  ''write-ahead log'' (WAL) so that, if the agent crashes and restarts,
  knowledge of the event is not lost. After the event has successfully
  made its way to the end of its flow, an acknowledgment is sent back to
  the originating agent so that it knows it no longer needs to store the
  event on disk. This reliability level can withstand any number of
  failures downstream of the initial agent.
   
  The *store on failure* reliability level causes nodes to only require
  an acknowledgement from the node one hop downstream. If the sending
  node detects a failure, it will store data on its local disk until the
  downstream node is repaired, or an alternate downstream destination
  can be selected. While this is effective, data can be lost if a
  compound or silent failure occurs.
   
  The *best-effort* reliability level sends data to the next hop with no
  attempts to confirm or retry delivery. If nodes fail, any data that
  they were in the process of transmitting or receiving can be
  lost. This is the weakest reliability level, but also the most
  lightweight.
=== Reliability
   
  Reliability, the ability to continue delivering events in the face of
  failures without losing data, is a vital feature of Flume. Large
  distributed systems can and do suffer partial failures in many ways -
  physical hardware can fail, resources such as network bandwidth or
  memory can become scarce, or software can crash or run slowly. Flume
  emphasizes fault-tolerance as a core design principle and keeps
  running and collecting data even when many components have failed.
   
  Flume can guarantee that all data received by an agent node will
  eventually make it to the collector at the end of its flow as long as
  the agent node keeps running. That is, data can be *reliably*
  delivered to its eventual destination.
   
  However, reliable delivery can be very resource intensive and is often
  a stronger guarantee than some data sources require. Therefore, Flume
  allows the user to specify, on a per-flow basis, the level of
  reliability required. There are three supported reliability levels:
   
  * End-to-end
  * Store on failure
  * Best effort
   
  .A Note About Reliability
  ******************
  Although Flume is extremely tolerant to machine, network, and software
  failures, there is never any such thing as '100% reliability'. If all
  the machines in a Flume installation were irrevocably destroyed in
  some terrible data center incident, all copies of Flume's data would
  be lost and there would be no way to recover them. Therefore all of
  Flume's reliability levels make guarantees about data delivery 'until
  some maximum number of failures have occurred'. Flume's failure modes
  - in terms of what can fail and what will keep running if they do -
  are described in detail later in this guide.
  ******************
   
  The *end-to-end* reliability level guarantees that once Flume accepts
  an event, that event will make it to the endpoint - as long as the
  agent that accepted the event remains live long enough. The first
  thing the agent does in this setting is write the event to disk in a
  ''write-ahead log'' (WAL) so that, if the agent crashes and restarts,
  knowledge of the event is not lost. After the event has successfully
  made its way to the end of its flow, an acknowledgment is sent back to
  the originating agent so that it knows it no longer needs to store the
  event on disk. This reliability level can withstand any number of
  failures downstream of the initial agent.
   
  The *store on failure* reliability level causes nodes to only require
  an acknowledgement from the node one hop downstream. If the sending
  node detects a failure, it will store data on its local disk until the
  downstream node is repaired, or an alternate downstream destination
  can be selected. While this is effective, data can be lost if a
  compound or silent failure occurs.
   
  The *best-effort* reliability level sends data to the next hop with no
  attempts to confirm or retry delivery. If nodes fail, any data that
  they were in the process of transmitting or receiving can be
  lost. This is the weakest reliability level, but also the most
  lightweight.

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