MarkSfik commented on a change in pull request #403:
URL: https://github.com/apache/flink-web/pull/403#discussion_r551858801
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File path: _posts/2020-12-22-pulsar-flink-connector-270.md
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@@ -0,0 +1,171 @@
+---
+layout: post
+title: "What's New in Pulsar Flink Connector 2.7.0"
+date: 2020-12-22T08:00:00.000Z
+categories: news
+authors:
+- jianyun:
+ name: "Jianyun Zhao"
+ twitter: "yihy8023"
+- jennifer:
+ name: "Jennifer Huang"
+ twitter: "Jennife06125739"
+
+excerpt: Batch and streaming is the future, Pulsar Flink Connector provides an
ideal solution for unified batch and streaming with Apache Pulsar and Apache
Flink. Pulsar Flink Connector 2.7.0 supports features in Pulsar 2.7 and Flink
1.12, and is fully compatible with Flink data format. Pulsar Flink Connector
2.7.0 will be contributed to the Flink repository, the contribution process is
ongoing.
+---
+
+## About Pulsar Flink Connector
+In order for companies to access real-time data insights, they need unified
batch and streaming capabilities. Apache Flink unifies batch and stream
processing into one single computing engine with “streams” as the unified data
representation. Although developers have done extensive work at the computing
and API layers, very little work has been done at the data and messaging and
storage layers. However, in reality, data is segregated into data silos,
created by various storage and messaging technologies. As a result, there is
still no single source-of-truth and the overall operation for the developer
teams is still messy. To address the messy operations, we need to store data in
streams. Apache Pulsar (together with Apache BookKeeper) perfectly meets the
criteria: data is stored as one copy (source-of-truth), and can be accessed in
streams (via pub-sub interfaces) and segments (for batch processing). When
Flink and Pulsar come together, the two open source technologies create a
unified data architecture for real-time data-driven businesses.
Review comment:
```suggestion
In order for companies to access real-time data insights, they need unified
batch and streaming capabilities. Apache Flink unifies batch and stream
processing into one single computing engine with “streams” as the unified data
representation. Although developers have done extensive work at the computing
and API layers, very little work has been done at the data messaging and
storage layers. In reality, data is segregated into data silos, created by
various storage and messaging technologies. As a result, there is still no
single source-of-truth and the overall operation for the developer teams poses
significant challenges. To address such operational challenges, we need to
store data in streams. Apache Pulsar (together with Apache BookKeeper)
perfectly meets the criteria: data is stored as one copy (source-of-truth) and
can be accessed in streams (via pub-sub interfaces) and segments (for batch
processing). When Flink and Pulsar come together, the two open source
technologies
create a unified data architecture for real-time, data-driven businesses.
```
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