[GitHub] [inlong-website] EMsnap commented on a diff in pull request #737: [INLONG-714][Release] Add blog for the 1.6.0 release

["EMsnap (via GitHub)" <gi...@apache.org>]

EMsnap commented on code in PR #737:
URL: https://github.com/apache/inlong-website/pull/737#discussion_r1147093997


##########
blog/2023-03-23-release-1.6.0.md:
##########
@@ -0,0 +1,102 @@
+---
+title: Release 1.6.0
+author: Charles Zhang
+author_url: https://github.com/dockerzhang
+author_image_url: https://avatars.githubusercontent.com/u/18047329?v=4
+tags: [Apache InLong, Version]
+---
+
+Apache InLong recently released version 1.6.0, which closed about 202+ issues, including 11+ major features and 80+ optimizations. Mainly completed the addition of Kudu data stream, improvement of Redis data stream, the addition of MQ cache cluster selector strategy, optimization of Audit ID allocation rules, the addition of data node connection testing, optimization of Sort Audit reconciliation benchmark time, and expansion of Audit support for using Kafka to cache audit data.
+<!--truncate-->
+
+## About Apache InLong
+As the industry's first one-stop open-source massive data integration framework, Apache InLong provides automatic, safe, reliable, and high-performance data transmission capabilities to facilitate businesses to build stream-based data analysis, modeling, and applications quickly. At present, InLong is widely used in various industries such as advertising, payment, social networking, games, artificial intelligence, etc., serving thousands of businesses, among which the scale of high-performance scene data exceeds 1 trillion lines per day, and the scale of high-reliability scene data exceeds 10 trillion lines per day.
+
+The core keywords of InLong project positioning are "one-stop" and  "massive data". For "one-stop", we hope to shield technical details, provide complete data integration and support services, and implement out-of-the-box; With its advantages, such as multi-cluster management, it can stably support larger-scale data volumes based on trillions lines per day.

Review Comment:
   multiple blanks



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: commits-unsubscribe@inlong.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org