<h2 id="deploy-applications-anywhere">Deploy Applications Anywhere</h2>
-<p>Apache Flink is a distributed system and requires compute resources in order to execute applications. Flink integrates with all common cluster resource managers such as <a href="https://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/YARN.html">Hadoop YARN</a>, <a href="https://mesos.apache.org">Apache Mesos</a>, and <a href="https://kubernetes.io/">Kubernetes</a> but can also be setup to run as a stand-alone cluster.</p>
+<p>Apache Flink is a distributed system and requires compute resources in order to execute applications. Flink integrates with all common cluster resource managers such as <a href="https://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/YARN.html">Hadoop YARN</a> and <a href="https://kubernetes.io/">Kubernetes</a>, but can also be setup to run as a stand-alone cluster.</p>
<p>Flink is designed to work well each of the previously listed resource managers. This is achieved by resource-manager-specific deployment modes that allow Flink to interact with each resource manager in its idiomatic way.</p>
* In the **framework deployment mode**, a client submits a Flink application against a running Flink service that takes care of executing the application. This is the common deployment model for most data processing frameworks, query engines, or database systems.
-* In the **library deployment mode**, a Flink application is packaged together with the Flink master executables into a (Docker) image. Another job-independent image contains the Flink worker executables. When a container is started from the job image, the Flink master process is started and the embedded application is automatically loaded. Containers started from the worker image, bootstrap Flink worker processes which automatically connect to the master process. A container manager such as Kubernetes monitors the running containers and automatically restarts failed containers. In this mode, you don't have to setup and maintain a Flink service in your cluster. Instead you package Flink as a library with your application. This model is very popular for deploying microservices.
+* In the **library deployment mode**, a Flink application is packaged together with the Flink master executables into a (Docker) image. Another job-independent image contains the Flink worker executables. When a container is started from the job image, the Flink master process is started and the embedded application is automatically loaded. Containers started from the worker image, bootstrap Flink worker processes which automatically connect to the master process. A container manager such as Kubernetes monitors the running containers and automatically restarts failed containers. In this mode, you don't have to setup and maintain a Flink service in your cluster. Instead you package Flink as a library with your application. This model is very popular for deploying microservices.
<div class="row front-graphic">
<img src="/img/deployment-modes.png" width="600px" />
<li><strong>Consistent Checkpoints</strong>: Flink’s recovery mechanism is based on consistent checkpoints of an application’s state. In case of a failure, the application is restarted and its state is loaded from the latest checkpoint. In combination with resettable stream sources, this feature can guarantee <em>exactly-once state consistency</em>.</li>
<li><strong>Efficient Checkpoints</strong>: Checkpointing the state of an application can be quite expensive if the application maintains terabytes of state. Flink’s can perform asynchronous and incremental checkpoints, in order to keep the impact of checkpoints on the application’s latency SLAs very small.</li>
<li><strong>End-to-End Exactly-Once</strong>: Flink features transactional sinks for specific storage systems that guarantee that data is only written out exactly once, even in case of failures.</li>
- <li><strong>Integration with Cluster Managers</strong>: Flink is tightly integrated with cluster managers, such as <a href="https://hadoop.apache.org">Hadoop YARN</a>
, <a href="https://mesos.apache.org">Mesos</a>, or <a href="https://kubernetes.io">Kubernetes</a>. When a process fails, a new process is automatically started to take over its work.</li>
+ <li><strong>Integration with Cluster Managers</strong>: Flink is tightly integrated with cluster managers, such as <a href="https://hadoop.apache.org">Hadoop YARN</a> or <a href="https://kubernetes.io">Kubernetes</a>. When a process fails, a new process is automatically started to take over its work.</li>
<li><strong>High-Availability Setup</strong>: Flink feature a high-availability mode that eliminates all single-points-of-failure. The HA-mode is based on <a href="https://zookeeper.apache.org">Apache ZooKeeper</a>, a battle-proven service for reliable distributed coordination.</li>
</ul>
<hr />
-<p>Apache Flink is an excellent choice to develop and run many different types of applications due to its extensive features set. Flink’s features include support for stream and batch processing, sophisticated state management, event-time processing semantics, and exactly-once consistency guarantees for state. Moreover, Flink can be deployed on various resource providers such as YARN, Apache Mesos, and Kubernetes but also as stand-alone cluster on bare-metal hardware. Configured for high availability, Flink does not have a single point of failure. Flink has been proven to scale to thousands of cores and terabytes of application state, delivers high throughput and low latency, and powers some of the world’s most demanding stream processing applications.</p>
+<p>Apache Flink is an excellent choice to develop and run many different types of applications due to its extensive features set. Flink’s features include support for stream and batch processing, sophisticated state management, event-time processing semantics, and exactly-once consistency guarantees for state. Moreover, Flink can be deployed on various resource providers such as YARN and Kubernetes, but also as stand-alone cluster on bare-metal hardware. Configured for high availability, Flink does not have a single point of failure. Flink has been proven to scale to thousands of cores and terabytes of application state, delivers high throughput and low latency, and powers some of the world’s most demanding stream processing applications.</p>
<p>Below, we explore the most common types of applications that are powered by Flink and give pointers to real-world examples.</p>
</ul>
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projects / flink-web.git / commitdiff
