This was extracted (@ 2025-06-25 23:10) from a list of minutes
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## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (3 years ago) There are currently 53 committers and 31 PMC members in this project. The Committer-to-PMC ratio is roughly 7:4. Community changes, past quarter: - Wenwei Huang was added to the PMC on 2025-02-07 - No new committers. ## Project Activity: In the past quarter, InLong has successfully released 2.1.0, and the project is working on 2.2.0, which will be released next month. For the newly released 2.1.0, it closed about 120+ issues, including 4+ major features and 110+ optimizations, for example: - Dashboard supports batch operation of agents - Manager supports multiple scheduling engines - Agent supports COS data source - Sort supports archiving dirty data through the InLong SDK ## Community Health: The community health looks good overall. - dev@inlong.apache.org had a 36% decrease in traffic in the past quarter (251 emails compared to 388) - 120 commits in the past quarter (-52% change) - 19 code contributors in the past quarter (-20% change) - 102 PRs opened on GitHub, past quarter (-49% change) - 104 PRs closed on GitHub, past quarter (-56% change) - 108 issues opened on GitHub, past quarter (-47% change) - 150 issues closed on GitHub, past quarter (-43% change) The developing data experienced some decline, but it's within expectations, and the project is still undergoing normal iteration and evolution.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (3 years ago) There are currently 53 committers and 30 PMC members in this project. The Committer-to-PMC ratio is roughly 7:4. Community changes, past quarter: - No new PMC members. - ShuoMing Qiu was added as committer on 2024-12-12 - Xiangming Zhou was added as committer on 2024-12-16 - Yifei Gao was added as committer on 2024-12-16 ## Project Activity: In the past quarter, InLong has successfully released 2.0.0, and the project is working on 2.1.0, which will be released next month. For the newly released 2.0.0, it closed about 315+ issues, including 6+ major features and 96+ optimizations, for example: - New Transform Capabilities - Community Documentation Restructuring - Support for OceanBase Data Source - Dynamic Resource Calculation for Sort Tasks - SortStandalone Supports HTTP Sink - Full-Link Management of Offline Synchronization There were no meetups during the past quarter. ## Community Health: The community health looks good overall. - dev@inlong.apache.org had a 35% decrease in traffic in the past quarter (430 emails compared to 661) - 249 commits in the past quarter (-38% change) - 24 code contributors in the past quarter (-40% change) - 189 PRs opened on GitHub, past quarter (-51% change) - 236 PRs closed on GitHub, past quarter (-28% change) - 195 issues opened on GitHub, past quarter (-52% change) - 259 issues closed on GitHub, past quarter (-24% change) The developing data experienced some decline, but it's within expectations, and the project is still undergoing normal iteration and evolution.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (2 years ago) There are currently 50 committers and 30 PMC members in this project. The Committer-to-PMC ratio is 5:3. Community changes, past quarter: - Wenkai Fu was added to the PMC on 2024-08-16 - Wensong Zhang was added as committer on 2024-08-17 ## Project Activity: In the past quarter, InLong has successfully released 1.13.0, and the project is working on 1.14.0, which will be released at the end of this month. For the newly released 1.13.0, it closed about 270+ issues, including 5+ major features and 50+ optimizations, for example: - Support offline data synchronization - Agent support PostgreSQL data soruce - Support transform - DataProxy supports Python SDK - Audit support exactly once semantic - Sort support unified configuration There were no meetups during the past quarter. ## Community Health: The community health looks good overall. - dev@inlong.apache.org had a 17% increase in traffic in the past quarter (694 emails compared to 593) - 199 commits in the past quarter (-52% change) - 30 code contributors in the past quarter (-11% change) - 220 PRs opened on GitHub, past quarter (-31% change) - 199 PRs closed on GitHub, past quarter (-38% change) - 233 issues opened on GitHub, past quarter (-33% change) - 213 issues closed on GitHub, past quarter (-40% change) The developing data experienced some decline, but it's within expectations, and the project is still undergoing normal iteration and evolution.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention. ## Membership Data: Apache InLong was founded 2022-06-15 (2 years ago) There are currently 50 committers and 30 PMC members in this project. The Committer-to-PMC ratio is 5:3. Community changes, past quarter: - Mingyu Bao was added to the PMC on 2024-05-27 - Wenkai Fu was added to the PMC on 2024-08-16 - Wensong Zhang was added as a committer on 2024-08-17 ## Project Activity: In the past quarter, InLong has successfully released 1.13.0, and the project is working on 1.14.0 (or 2.0.0), which will be released in early October. For the newly released 1.13.0, it closed about 275+ issues, including 6+ major features and 100+ optimizations, for example: - Support installing Agent by SSH - Support field template management - Support configuring offline synchronization tasks - Optimize the Sort Standalone configuration process In addition, The community had an offline meetup with the Apache Pulsar community during the past quarter. ## Community Health: The community health looks good overall. The project continues to release versions, and new contributors are constantly joining.
No report was submitted.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention ## Membership Data: Apache InLong was founded 2022-06-15 (2 years ago) There are currently 48 committers and 28 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - Lu Chunliang was added to the PMC on 2024-03-07 - No new committers. Last addition was Wenwei Huang on 2023-12-27. ## Project Activity: In the past quarter, InLong has successfully released 1.11.0, and the project is working on 1.12.0, which will be released at the end of this month. For the newly released 1.11.0, it closed about 97+ issues, including 3+ major features and 10+ optimizations, for example: - Refactor the file collector - Dashboard add audit data for Agent module - Unify the data format for the Sort module - Support migrating group resources for tenant There were no meetups during the past quarter, but the community plans an offline meetup with the Apache Pulsar community at the end of the month. ## Community Health: The community health looks good overall. In the past quarter, - dev@inlong.apache.org had a 23% decrease in traffic in the past quarter (429 emails compared to 553) - 216 commits in the past quarter (-26% decrease) - 26 code contributors in the past quarter (-7% change) - 215 PRs opened on GitHub, in the past quarter (-19% change) - 210 PRs closed on GitHub, in the past quarter (-21% change) - 202 issues opened on GitHub, in the past quarter (-28% change) - 213 issues closed on GitHub, in the past quarter (-19% change) The development data has declined a bit, and the main reason is that many developers are from China, and there was a Chinese New Year holiday in the last quarter.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (2 years ago) There are currently 48 committers and 27 PMC members in this project. The Committer-to-PMC ratio is roughly 8:5. Community changes, past quarter: - No new PMC members. The last addition was Fan Deng on 2023-08-09. - Wenwei Huang was added as a committer on 2023-12-27 ## Project Activity: In the past quarter, InLong has successfully released 1.10.0, and the project is working on 1.11.0, which will be released next month. For the newly released 1.10.0, it closed about 200+ issues, including 6+ major features and 30+ optimizations, for example: - Support periodic collection for Agent module - Support for viewing Agent audit by IP dimension - Add group operation logs for the Manager module - Support switch group for managing multi-cluster - C++ SDK supports multi-dimensional isolation And there were no meetups during the past quarter. ## Community Health: The community health looks good overall. In the past quarter, - dev@inlong.apache.org had an 11% decrease in traffic in the past quarter (557 emails compared to 621) - 286 commits in the past quarter (-15% decrease) - 261 PRs opened on GitHub, past quarter (-11% change) - 262 PRs closed on GitHub, past quarter (-13% change) - 264 issues opened on GitHub, past quarter (-11% change) - 259 issues closed on GitHub, past quarter (-15% change) The developing data experienced some decline, but it's within expectations, and the project is still undergoing normal iteration and evolution.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (a year ago) There are currently 47 committers and 27 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - Fan Deng was added to the PMC on 2023-08-09 - MengHui Yu was added as committer on 2023-08-30 - Ganfeng Tan was added as committer on 2023-07-20 ## Project Activity: In the past quarter, InLong has successively released 1.8.0, and t he project is working on 1.9.0 now, which will be released next week. For the coming 1.9.0, it close about about 220+ issues, including 2+ major features and 30+ optimizations, for example: - Build observability capabilities based on OpenTelemetry - Optimize DataProxy CPP SDK - Optimize retry logic after failed sending - Support more DDL types - Add TubeMQ command-line tool - Optimize multi-tenancy And there were two meetups for university students. ## Community Health: The community health looks good overall. In the past quarter, - dev@inlong.apache.org had a 9% increase in traffic (702 emails compared to 643) - 409 commits in the past quarter (17% increase) - 49 code contributors in the past quarter (32% increase) - 333 PRs opened on GitHub, past quarter (5% increase) - 337 PRs closed on GitHub, past quarter (6% increase) - 353 issues opened on GitHub, past quarter (3% increase) - 355 issues closed on GitHub, past quarter (6% increase)
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop, full-scenario data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data. ## Project Status: Current project status: Ongoing, with moderate activity. Issues for the board: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (a year ago) There are currently 45 committers and 26 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - No new PMC members. Last addition was Yunqing Mo on 2023-01-18. - Zuofeng Zhang was added as committer on 2023-06-17 - Haif Xu was added as committer on 2023-05-10 - Wenkai Fu was added as committer on 2023-05-02 ## Project Activity: In the past quarter, InLong has successively released 1.7.0, and the project is working on 1.8.0 now, which will be released next week. For the coming 1.8.0, it close about 230 issues, including 8+ major features and 60+ optimizations, for example: - Add `full-scenario` for the project description - Support multi-tenancy - Support data preview - Split data synchronization feature And there is no meetups and conferences in the past quarter. ## Community Health: The community health looks good overall. In the latest month, - 6 new code contributors contributed to the project (142 in total). - 131 commits to master (+15% increase). - 29 active contributors (-6.4% decrease). - 139 PRs opened on GitHub (+9.4% increase). - 150 issues closed on GitHub (+12.7% increase). The community is improving the project ecosystem and capabilities through fixed-period version releases, and will enhance the project's influence through some activities in the future.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (10 months ago) There are currently 42 committers and 26 PMC members in this project. The Committer-to-PMC ratio is roughly 3:2. Community changes, past quarter: - Yunqing Mo was added to the PMC on 2023-01-18 - Xueying Zhang was added as a committer on 2023-03-17 - The Xia was added as a committer on 2023-01-18 ## Project Activity: In the past quarter, InLong has successively released 1.6.0, which closed about 202+ issues, including 11+ major features and 80+ optimizations, for example: - the addition of the Kudu data stream - improvement of Redis data stream - the addition of the 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 - expansion of Audit support for using Kafka to cache audit data And there is no meetups and conferences in the past quarter. ## Community Health: The community health looks good overall. In the latest month, - 9 new code contributors contributed to the project (136 in total). - 114 commits to master (-36% decrease). - 31 active contributors (-11% decrease). - 127 PRs opened on GitHub (-32% decrease). - 133 issues closed on GitHub (-29% decrease). The last quarter had some big holidays for most contributors, and the community was focusing on addressing stability issues, which I think are the reasons for the decline in some data.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded on 2022-06-15 (7 months ago) There are currently 40 committers and 25 PMC members in this project. The Committer-to-PMC ratio is 8:5. Community changes, past quarter: - No new PMC members. The last addition was Junjie Chen on 2022-07-10. - There is a candidate PMC member who is in the voting process. - Cisco Zhou was added as a committer on 2022-10-25 - Xin Gong was added as a committer on 2022-11-08 - Fan Deng was added as a committer on 2022-12-20 - Zixuan Zhao was added as a committer on 2022-12-20 ## Project Activity: In the past quarter, InLong has successively released two versions, 1.4.0 and 1.5.0. The just-released version 1.5.0 mainly completes the following things, including: - Added new load data node for StarRocks, Hudi, Doris, Elasticsearch, etc. - Optimize Dashboard experience. - Refactoring the MQ management model. - Add dirty data processing. - Full link Apache Kafka support. - TubeMQ C++/Python SDK supports production. Meetups and Conferences in the past month: - Attend Doris Summit 2022 and share the topic — "Integration of Apache InLong and Apache Doris, sharing of the whole database migration proposal". - Attend the Hudi Community meetup and share the topic - "The new paradigm for InLong supports of data lake Hudi". - The community summaries year-end review and 2023 planning. ## Community Health: The community health looks good overall. In the latest month, - 9 new code contributors contributed to the project (127 in total). - 178 commits to master (+35% increase). - 35 active contributors (+16% increase). - 186 PRs opened on GitHub (+30% increase). - 188 issues closed on GitHub (+10% increase).
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (4 months ago) There are currently 36 committers and 25 PMC members in this project. The Committer-to-PMC ratio is roughly 9:7. Community changes, past quarter: - No new PMC members. Last addition was Junjie Chen on 2022-07-10. - Yunqing Mo was added as committer on 2022-08-23 ## Project Activity: At this time, we are focusing on trying to develop 1.4.0, the following 1.4.0 will be released around the end of this month and looks to achieve these goals: - Agent adds Redis, CloudEvents, MongoDB collection types - Unified DataProxy MQ framework - Full support for Apache Kafka In the past month, the community has mainly completed the following work: - Fix 1.3.0 data inaccurate about audit module - Support dynamic topic for kafka data node - File data node support hidden directories - Command line tool to increase cluster management Meetups and Conferences in the past month: - Prepare for a course/topic for beginners ## Community Health: The community health is good. In the past month, - 2 new code contributors contributed to the project (118 in total). - 131 commits to master (-16% decrease). - 30 active contributors (-6% decrease). - 143 PRs opened on GitHub (-22% decrease). - 170 issues closed on GitHub (-5% decrease). The main data of the community declined this month, which may be caused by the short interval between reports, and many Chinese contributors have had a long holiday recently.
## Description: The mission of Apache InLong is the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (3 months ago) There are currently 36 committers and 25 PMC members in this project. The Committer-to-PMC ratio is roughly 9:7. Community changes, past quarter: - Junjie Chen was added to the PMC on 2022-07-10 - Mingyu Bao was added as committer on 2022-06-25 - Yupeng Shi was added as committer on 2022-06-25 - Yunqing Mo was added as committer on 2022-08-23 ## Project Activity: At this time, the community released the 1.3.0 version, which closes about 410+ issues,contains 110+ features and 170+ optimizations. Mainly include the following features: - Enhance management and control capabilities. - Extended collection node. - Optimize write node. - Support data conversion. - Strengthen Agent function. At same time, we are focusing on trying to develop 1.4.0, the following 1.4.0 will be relased in about 2 monthes and looks to achieve these goals: - Agent adds Redis, CloudEvents, MongoDB collection types - Unified DataProxy MQ framework - Full support for Apache Kafka Meetups and Conferences in the past month: - Prepare an online meetup to introduce the just-released 1.3.0. ## Community Health: The community health is good. In the past month, - 6 new code contributors contributed to the project (116 in total). - 156 commits to master (-17% decrease). - 32 active contributors (-13% decrease). - 185 PRs opened on GitHub (-13% decrease). - 178 issues closed on GitHub (-28% decrease). Because the community is preparing to release version 1.3.0, mainly dealing with bug fix-related PRs, which caused a decline in some data. the community still looks healthy.
## Description: InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (2 months ago) There are currently 35 committers and 25 PMC members in this project. The Committer-to-PMC ratio is 7:5. Community changes, past quarter: - Junjie Chen was added to the PMC on 2022-07-10 - Mingyu Bao was added as committer on 2022-06-25 - Yupeng Shi was added as committer on 2022-06-25 ## Project Activity: At this time, we are focusing on trying to develop 1.3.0, and 1.3.0 looks to achieve these goals: - Increase the stability of lightweight architecture - Complete the label-based cross-regional and multi-cluster model - Add more connectors 1.3.0 will be released in the next 1-2 weeks. Software development activity in the past month: - Dashboard added 4 new Load Data Nodes. - DataProxy supported C++ SDK. - Manager added a heartbeat mechanism for Agent and DataProxy. - Agent refactored the metric system to extend the new listener. - Sort added a unified metric framework for all connectors. Meetups and Conferences in the past month: - 2 Contributors attended Apache Asia 2022, giving two talks on Apache InLong ## Community Health: The community health is good. In the past month, - 4 new code contributors contributed to the project (110 in total). - 190 commits to master (+32% increase). - 37 active contributors (+27% increase). - 212 PRs opened on GitHub (+50% increase). - 247 issues closed on GitHub (+40% increase).
## Description: InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. ## Issues: There are no issues requiring board attention at this time. ## Membership Data: Apache InLong was founded 2022-06-15 (a month ago) There are currently 35 committers and 25 PMC members in this project. The Committer-to-PMC ratio is 7:5. Community changes, past quarter: - Junjie Chen was added to the PMC on 2022-07-10 - Mingyu Bao was added as committer on 2022-06-25 - Yupeng Shi was added as committer on 2022-06-25 ## Project Activity: Apache InLong just completed the release process for 1.2.0, which closes about 410+ issues, and contains 30+ features and 190+ optimizations. At this time, we are focusing on trying to develop 1.3.0, and 1.3.0 looks to achieve these goals: - Increase the stability of lightweight architecture - Complete the label-based cross-regional and multi-cluster model - Add more connectors Software development activity: - We released the 1.2.0 version on 2022-06-21 - We are preparing to make release candidates for 1.3.0 in the coming week - We have completed support for the label-based cross-regional and multi-cluster model - We added an end2end unit test framework to cover all connectors - We improved the stability of the InLong Audit module Meetups and Conferences: - 2 Contributors will attend Apache Asia 2022, giving two talks on Apache InLong - The community is discussing the roadmap for the second half of the 2022 ## Community Health: Overall community health is good, the status is "no change" because it's the first report. - 3 new contributors contributed to the project in the past month (no change). - 143 commits to master in the past month (no change). - 29 active contributors in the past month (no change). - 141 PRs opened on GitHub in the past month (no change). - 176 issues closed on GitHub in the past month (no change).
WHEREAS, the Board of Directors deems it to be in the best interests of the Foundation and consistent with the Foundation's purpose to establish a Project Management Committee charged with the creation and maintenance of open-source software, for distribution at no charge to the public, related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data. NOW, THEREFORE, BE IT RESOLVED, that a Project Management Committee (PMC), to be known as the "Apache InLong Project", be and hereby is established pursuant to Bylaws of the Foundation; and be it further RESOLVED, that the Apache InLong be and hereby is responsible for the creation and maintenance of software related to a one-stop data integration framework that provides automatic, secure, and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling, and other real-time applications based on streaming data; and be it further RESOLVED, that the office of "Vice President, Apache InLong" be and hereby is created, the person holding such office to serve at the direction of the Board of Directors as the chair of the Apache InLong Project, and to have primary responsibility for management of the projects within the scope of responsibility of the Apache InLong Project; and be it further RESOLVED, that the persons listed immediately below be and hereby are appointed to serve as the initial members of the Apache InLong Project: * Peng Chen <pengchen@apache.org> * Zili Chen <tison@apache.org> * Guangxu Cheng <gxcheng@apache.org> * Heal Chow <healchow@apache.org> * Junping Du <junping_du@apache.org> * Yuanhao Ji <jiyuanhao@apache.org> * Guo Jiwei <technoboy@apache.org> * Daniel Li <leezng@apache.org> * Haiji Li <charleli@apache.org> * Osgoo Li <osgooli@apache.org> * Lamber Liu <lamberliu@apache.org> * Yuanbo Liu <yuanbo@apache.org> * Lizhen <lzwang@apache.org> * Zijie Lu <alfredlu@apache.org> * Justin Mclean <jmclean@apache.org> * Jean-Baptiste Onofré <jbonofre@apache.org> * Zirui Peng <zirui@apache.org> * Seraph <seraph@apache.org> * Jerry Shao <jshao@apache.org> * Zak Wu <zakwu@apache.org> * ZhongBo Wu <kaynewu@apache.org> * Aloys Zhang <aloyszhang@apache.org> * Charles Zhang <dockerzhang@apache.org> * Guocheng Zhang <gosonzhang@apache.org> NOW, THEREFORE, BE IT FURTHER RESOLVED, that Charles Zhang be appointed to the office of Vice President, Apache InLong, to serve in accordance with and subject to the direction of the Board of Directors and the Bylaws of the Foundation until death, resignation, retirement, removal or disqualification, or until a successor is appointed. Special Order 7E, Establish the Apache InLong Project, was approved by Unanimous Vote of the directors present.
InLong is a one-stop data integration framework that provides automatic,
secure, and reliable data transmission capabilities. InLong supports both
batch and stream data processing at the same time, which offers great power
to build data analysis, modeling, and other real-time applications based on
streaming data.
InLong has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Gain more active contributors/committers to build a diverse community.
2. Prepare to discuss in the community.
### Are there any issues that the IPMC or ASF Board need to be aware of?
No issues.
### How has the community developed since the last report?
1. 2 new committers and 1 PPMC have voted from different organizations.
2. About 26 new contributors have joined the community (currently: 95).
3. 36+ authors have pushed 720+ commits to master.
4. Add GitHub Discussions Board to communicate with contributors and users.
5. Attend the Pulsar Summit and share a topic about InLong.
6. Attend the DataFun Summit and share a topic about InLong.
7. Prepare a joint meetup with the SeaTunnel community.
### How has the project developed since the last report?
1. Release 1.0.0 on Feb 17, 2022
2. Release 1.1.0 on Apr 24, 2022
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [ ] Community building
- [X] Nearing graduation
- [ ] Other:
### Date of last release:
2022-04-24
### When were the last committers or PPMC members elected?
1. committer, bluewang was elected as committer on 2022-04-22
2. PPMC, healchow was elected as PPMC on 2022-03-30
### Have your mentors been helpful and responsive?
Yes, our mentors are very helpful and responsive.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (inlong) Junping Du
Comments:
- [ ] (inlong) Justin Mclean
Comments:
- [ ] (inlong) Sijie Guo
Comments:
- [ ] (inlong) Zhijie Shen
Comments:
- [X] (inlong) Jean-Baptiste Onofré
Comments: I think InLong is not so far from graduation. Worth to
start the maturity assesment as see if we can move forward on the
graduation.
### IPMC/Shepherd notes:
InLong is a one-stop data streaming platform that provides automatic,
secure, distributed, and efficient data publishing and subscription
capabilities. This platform helps you easily build stream-based data
applications.
InLong has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Improve and optimize the system to solve the system shortboard
2. Promote the system, to let more people use and participate in the
community
3. Building a diverse community with open governance
### Are there any issues that the IPMC or ASF Board need to be aware of?
No issues
### How has the community developed since the last report?
1. 1 new contributor has joined the community since the last report
(currently: 57)
2. Participated in the ApacheCon Asia online conference in August,
introducing the architecture and advantages of InLong
3. Plan to hold an offline + online meetup in October to discuss how to
run the InLong community well in the next
### How has the project developed since the last report?
In version 0.10.0, we integrated the project, Dockerized all components,
provided one-click installation capabilities, simplified module
configuration, and lowered the threshold for using InLong; in the upcoming
0.11.0 version, we are doing the following Improvement: the entire chain
adds support for Pulsar reporting, and the Sort module adds support for
IceBerg and ClickHouse landing to increase the use of components.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2021-09-14
### When were the last committers or PPMC members elected?
The last committer or PPMC was elected on on 2020-12-15.
Judging from the current contribution situation,it is expected that
someone contributor will be promoted to the committer in the next version.
### Have your mentors been helpful and responsive?
Yes, our mentors are very helpful and responsive.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [X] (inlong) Junping Du
Comments:
- [X] (inlong) Justin Mclean
Comments:
- [ ] (inlong) Sijie Guo
Comments:
- [ ] (inlong) Zhijie Shen
Comments:
- [ ] (inlong) Jean-Baptiste Onofré
Comments:
### IPMC/Shepherd notes:
InLong is a one-stop data streaming platform that provides automatic,
secure, distributed, and efficient data publishing and subscription
capabilities. This platform helps you easily build stream-based data
applications.
InLong has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1.Improve and optimize the system to solve the system shortboard
2.Promote the system, to let more people use and participate in the
community
3.Building a diverse community with open governance.
### Are there any issues that the IPMC or ASF Board need to be aware of?
No issues
### How has the community developed since the last report?
- 3+ new contributors participate in the community since the last
report(currently: 56)
- Held 1 online meetup to discuss the renamed project architecture and
goals.
- InLong history issues have migrate from JIRA to GitHub Issues
successfully, include all issues status.
### How has the project developed since the last report?
- Improve the ease of deployment and documentation quality.
- Refactor the submodules to be more unified.
- Develop the issues for next release.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2021-07-12
### When were the last committers or PPMC members elected?
The last PPMC was elected on on 2020-12-15
### Have your mentors been helpful and responsive?
Yes, our mentors are very helpful and responsive.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (inlong) Junping Du
Comments:
- [X] (inlong) Justin Mclean
Comments:
- [ ] (inlong) Sijie Guo
Comments:
- [ ] (inlong) Zhijie Shen
Comments:
- [X] (inlong) Jean-Baptiste Onofré
Comments: The podling is moving forward cleanly and I have the chance
to chat with them on Slack. Great podling.
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1.Complete the project rename task
2.Improve and optimize the system to solve system Short board
3.Promote the system, to let more people to use and participate in the
community
### Are there any issues that the IPMC or ASF Board need to be aware of?
One,
Our rename implementation Jira[1] still has no clear completion time. Since
the new name passed and mentor JB submitted the rename Jira[1] on March 11,
after the priority of the jira was adjusted from Major to Minor on March
13, the mentors has pinged several times, but still no more movement.
1.
https://issues.apache.org/jira/projects/INFRA/issues/INFRA-21558?filter=allo
penissues
### How has the community developed since the last report?
We have recently deployed the community TubeMQ 0.8.0 version in our
environment, from the comparison of before and after the gray-scale, the
performance of the version is at least 5% higher than before, especially
the metric of the number of disks written has dropped significantly, and
the problems found have been reported back to the community for repair.
At the same time, we have conducted three times offline technical exchanges
with the technical teams of other different companies (the relevant
communication documents have been placed on the external website for other
business review and analysis). Through the comparison of the environmental
issues of different companies in the big data scenario, TubeMQ has
relatively good cost advantages and technical characteristics. We will
continue to choose to cooperate with companies with similar scenario
requirements to let more people, company, who need this ability uses this
component, and participates in the operation of the community.
In addition to using email to synchronize information, we created an
"inlong" channel in ASF on Slack to meet and solve the needs of users for
timely communication.
### How has the project developed since the last report?
When we were preparing for the release of TubeMQ 0.8.0 without the "-WIP"
tag, we discovered that the BDB component that the project metadata
management module relies on has a license authorization problem, we are
refactoring this part to meet Apache's license requirements.
At the same time, our project has submitted an application for name change
and has been approved by Apache. We are currently preparing for the content
of the project after the name change, including the project homepage, Logo,
modules to be open sourced, documentation, etc, and some of the content has
been completed and is waiting to be applied online after the name change is
completed; the name change implementation Jira [1] has been submitted by
Mentor JB on March 11, and is still in pending status without clear
implementation completion time.
1.
https://issues.apache.org/jira/projects/INFRA/issues/INFRA-21558?filter=allo
penissues
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2021-03-05
### When were the last committers or PPMC members elected?
yuanboliu - was added as committers on 2020-12-10
dockerzhang - was added as PPMC on 2020-12-15
### Have your mentors been helpful and responsive?
Yes, the mentors Justin and JB in the project improvement stage gave us a
lot of help.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (tubemq) Junping Du
Comments:
- [X] (tubemq) Justin Mclean
Comments: Rename issue has been resolved.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments: I helped with renaming process
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1.Adjust project goal && project name
2.Keep growing the community, attract more contributors and committers
3.Release Apache standard releases regularly
### Are there any issues that the IPMC or ASF Board need to be aware of?
We hope more IPMCs will pay attention to our project and give more
suggestions.
### How has the community developed since the last report?
Since the last report, the TubeMQ community has continued to improve its
functions
as well as external publicity and communication; at the same time, we
PPMCs conducted
a discussion on adjusting project objectives and project names.
We hope to provide a complete one-stop streaming data service platform:
the system
integrates a series of components in the form of plug-ins for collection,
aggregation,
storage and forwarding to build a complete data reporting service; based
on this platform,
users only need to publish and subscribe to data, and they can easily
build analysis and
applications based on streaming data; and TubeMQ will continue to develop
in this project.
### How has the project developed since the last report?
At this stage, we released the SDK of the Python language and the
tubemq-manager module for
cluster management. The tubemq-manager module is used for cross-cluster
control to make
the project more usable; we have also made a number of improvements in
the function of the project,
for details information, please refer to our project issues:
https://issues.apache.org/jira/projects/TUBEMQ/issues.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2020-12-04
### When were the last committers or PPMC members elected?
1. yuanboliu was added as committer on 2020-12-10
2. dockerzhang was added as PPMC on 2020-12-15
### Have your mentors been helpful and responsive?
In the recent period, the mentors have given us a lot of help and
guidance;
We hope that the mentors can continue to pay attention to the development
of our project and continue to provide more help and suggestions to the
project.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (tubemq) Junping Du
Comments:
- [X] (tubemq) Justin Mclean
Comments: Don't forget you can reach out to your mentors if you need
help. Keeping discussions on the mailing list also helps.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments:
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1.Keep growing the community, attract more contributors and committers
2.Release Apache standard releases regularly
3.Continuously improve system performance and increase system features
### Are there any issues that the IPMC or ASF Board need to be aware of?
We hope more IPMCs will pay attention to our project and give more
suggestions.
### How has the community developed since the last report?
Since the last report, the TubeMQ community has attracted many real users
who have given feedback to the project many bugs,
and enthusiastic contributors have made multilingual SDK contributions to
the project and successfully applied them in the actual environment;
the community periodically releases iteratively to provide stable and
easy-to-use new features.
### How has the project developed since the last report?
This stage is mainly for the development and implementation of
multi-language SDKs: the C/C++ SDK delivery has been completed;
at the same time, SDKs for Go, Python, Rust and other languages are under
development. In addition to the new features of the multi-language SDKs,
the project initiated the development of the tubemq-manager module for
cross-cluster control to make the project more usable;
for details, please refer to our project issues:
https://issues.apache.org/jira/projects/TUBEMQ/issues.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2020-07-22
### When were the last committers or PPMC members elected?
dockerzhang was added as committer on 2020-07-13
### Have your mentors been helpful and responsive?
The mentors gave us a lot of help and guidance at the beginning of the
project, but as the project deepened,
the mentors paid less attention. We hope that the mentors can continue to
pay attention to
the development of our project and continue to provide help and
suggestions to the project.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (tubemq) Junping Du
Comments:
- [X] (tubemq) Justin Mclean
Comments:
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments: Effort is on the community building now, it's on the way.
### IPMC/Shepherd notes:
JM: I think if you move some of your GitHub traffic off the dev list and
had more discussions there it would help with mentor engagement.
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Keep growing the community
2. Improve documentation, including document translation
3. Continuously improve system performance and increase system features
### Are there any issues that the IPMC or ASF Board need to be aware of?
None.
### How has the community developed since the last report?
Since the last report,the TubeMQ community has welcomed one new committer
member: the project community has continued to be active,
attracting many contributors for extensive cooperation and
contributions,the total number of contributors has increased to
53(code:39,website:14).
At the same time,we have adapted to the project operation style of the
Apache community:we move project-related communications,program
discussions,
and task implementation to e-mail, transparentize the entire project
process, and operate according to community standards.
### How has the project developed since the last report?
We successfully released the first release version according to the
Apache process: the project has made a lot of usability improvements under
the contribution of everyone,including document finishing,support based
on Docker and K8S container operation,
and data reporting pipeline support upstream and downstream (Including
data access based on Flume,source and sink based on Flink and Spark), etc;
at the same time, we have also made a lot of adjustments in functions and
performance.
For details, please refer to our project issue:
https://issues.apache.org/jira/projects/TUBEMQ/issues.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
2020-06-08
### When were the last committers or PPMC members elected?
Technoboy- was added as committer on 2020-04-21
### Have your mentors been helpful and responsive?
Yes.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [ ] (tubemq) Junping Du
Comments:
- [X] (tubemq) Justin Mclean
Comments:
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments:
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system. TubeMQ has been
incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Launch the first Apache release.
2. Grow the community
3. Make development document more easily to read
### Are there any issues that the IPMC or ASF Board need to be aware of?
None
### How has the community developed since the last report?
We elected the first external Committer, and at the same time,
the questions based on the use of feedback gradually increased,
from this point, it can be speculated that the project has begun
to be followed and used by more people; the official version
is being prepared, we will release the first version recently.
### How has the project developed since the last report?
Near the first Apache release launch.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [X] Initial setup
- [X] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
None
### When were the last committers or PPMC members elected?
Technoboy- was added as committer on 2020-04-15
### Have your mentors been helpful and responsive?
Yes.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [X] (tubemq) Junping Du
Comments:
- [X] (tubemq) Justin Mclean
Comments:
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments:
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Launch the first Apache release.
2. Grow community
3. Make development document more easily to read
### Are there any issues that the IPMC or ASF Board need to be aware of?
None
### How has the community developed since the last report?
We are applying TubeMQ to the actual environment, at this stage
we have discovered and fixed some bugs; at the same time, we are
learning and preparing for the first release. It is expected that
in the next stage we will release the first release
### How has the project developed since the last report?
Near the first Apache release launch.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [X] Initial setup
- [X] Working towards first release
- [X] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
None
### When were the last committers or PPMC members elected?
Aloys Zhang was added as committer on 2020-02-20
### Have your mentors been helpful and responsive?
Yes.
### Is the PPMC managing the podling's brand / trademarks?
Yes, all good here.
### Signed-off-by:
- [X] (tubemq) Junping Du
Comments: Better to be more active for community activities.
- [X] (tubemq) Justin Mclean
Comments: Looking froward to the first release.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [ ] (tubemq) Jean-Baptiste Onofre
Comments:
### IPMC/Shepherd notes:
## TVM
TVM is a full stack open deep learning compiler stack for CPUs, GPUs, and
specialized accelerators. It aims to close the gap between the productivity-
focused deep learning frameworks, and the performance- or efficiency-
oriented hardware backends.
TVM has been incubating since 2019-03-06.
### Three most important unfinished issues to address before graduating:
1. Keep growing the community
2. Improve documentations
### Are there any issues that the IPMC or ASF Board need to be aware of?
no
### How has the community developed since the last report?
TVM community has welcomed two new committers/PPMC members since last
report. There are also on-going new committer nominations.
The community is active and vibrate, with wide collaborations from
many contributors. The total number of contributors has grown to 343.
The community also actively worked on items under the guide of the Apache
maturity model
https://docs.google.com/document/d/18nyAH-fcptVezAxPQe6H3FeTKPRkujOp1tc1Y
RSPLok/edit?usp=sharing
### How has the project developed since the last report?
A lot of improvements have been made. Including major improvements to
the unified IR and Pytorch support.
See also our monthly reports for detailed improvements
- Jan https://discuss.tvm.ai/t/tvm-monthly-january-2020/5589
- Feb https://discuss.tvm.ai/t/tvm-monthly-february-2020/5935
- Mar https://discuss.tvm.ai/t/tvm-monthly-march-2020/6199
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [ ] Initial setup
- [ ] Working towards first release
- [X] Community building
- [X] Nearing graduation
- [ ] Other:
### Date of last release:
2019-12-1
### When were the last committers or PPMC members elected?
Feb 20 2020
### Have your mentors been helpful and responsive?
Our mentors are super helpful.
### Is the PPMC managing the podling's brand / trademarks?
Yes, we have completed the name search.
### Signed-off-by:
- [X] (tvm) Byung-Gon Chun
Comments:
- [ ] (tvm) Sebastian Schelter
Comments:
- [X] (tvm) Henry Saputra
Comments:
- [ ] (tvm) Timothy Chen
Comments:
- [X] (tvm) Furkan Kamaci
Comments:
- [X] (tvm) Tianqi Chen
Comments:
- [X] (tvm) Markus Weimer
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1.Launch the first Apache release.
2.Make development document more easily to read.
3.Grow the community to involve more contributors and increase the
diversity.
### Are there any issues that the IPMC or ASF Board need to be aware of?
None
### How has the community developed since the last report?
At this stage, no community activities were initiated, but we internally
initiated
a vote for the project committer and selected the first committer of the
project.
I believe this will promote the subsequent development of the project
community.
### How has the project developed since the last report?
The project is nearing completion of the migration to the Apache
incubator:
at this stage, we have completed the change of the project's package
name, the standardization of file's LICENSE, and the launch of the project
home page but the documentation and project home page content relatively
lacking, this part needs to be improved in the next stage.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [X] Initial setup
- [X] Working towards first release
- [ ] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
None
### When were the last committers or PPMC members elected?
2020-02-20
### Have your mentors been helpful and responsive?
Yes
### Is the PPMC managing the podling's brand / trademarks?
Yes.
### Signed-off-by:
- [X] (tubemq) Junping Du
Comments: I saw there are new committers get voted, good move!
- [X] (tubemq) Justin Mclean
Comments: Showing better progress than before.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments: Podling is still in bootstrap phase but moving forward.
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Launch the first Apache release.
2. Make development document more easily to read
3. Grow the community to involve more contributors and increase the
diversity.
### Are there any issues that the IPMC or ASF Board need to be aware of?
None
### How has the community developed since the last report?
Currently the project is still on migrating, a few contributions
in the bug reports and pull requests are offered on the repository.
We hosted 1 below-the-line meetups to promote this project.
### How has the project developed since the last report?
Towards migrating to Apache incubator, we submitted SGA, builded home
pages, all PPMC’s apache id, icla, roster are ready.
Some things are being worked on, such as ensuring that
all PPMCs join private mailing lists, adjusting project packages, etc.
We are leading everyone to communicate via email, Jira(not just IM).
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [X] Initial setup
- [X] Working towards first release
- [ ] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
None
### When were the last committers or PPMC members elected?
None
### Have your mentors been helpful and responsive?
Yes
### Is the PPMC managing the podling's brand / trademarks?
Still on migrating.
### Signed-off-by:
- [X] (tubemq) Junping Du
Comments: Overall looks good. Next time if there is community meetup,
we'd better to notice everyone on dev mail list.
- [X] (tubemq) Justin Mclean
Comments: Needed a little help of getting the report together. Try
to keep offlist communication to a minimum and bring things back
to the mailing list.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [ ] (tubemq) Jean-Baptiste Onofre
Comments:
### IPMC/Shepherd notes:
TubeMQ is a distributed messaging queue (MQ) system.
TubeMQ has been incubating since 2019-11-03.
### Three most important unfinished issues to address before graduating:
1. Bootstrap the Apache project and migrate repos to Apache.
2. Grow the community to involve more contributors and increase the
diversity.
3. Polish the code and document to satisfy the Apache way.
### Are there any issues that the IPMC or ASF Board need to be aware of?
Needs mentors and IPMCs to help to bootstrap the project and follow the
Apache way to grow the community.
### How has the community developed since the last report?
Currently the project is still on migrating, because of the migrating
gap, there's 60+ GH issues and 80+ GH PRs submitted,
and over 25 contributors on this project, but this was not happened in
Apache JIRA/repo, we will migrate them soon.
Also We hosted 3 meetups to promote this project.
### How has the project developed since the last report?
Towards migrating to Apache incubator, like building home pages, launch
first Apache release.
### How would you assess the podling's maturity?
Please feel free to add your own commentary.
- [x] Initial setup
- [x] Working towards first release
- [ ] Community building
- [ ] Nearing graduation
- [ ] Other:
### Date of last release:
None
### When were the last committers or PPMC members elected?
None
### Have your mentors been helpful and responsive?
Yes
### Is the PPMC managing the podling's brand / trademarks?
Still on migrating.
### Signed-off-by:
- [x] (tubemq) Junping Du
Comments: IPMCs and PPMCs need to work hard together towards the goal
of graduating.
- [X] (tubemq) Justin Mclean
Comments: Off to a slow start and needs to engage with mentors more,
more communication on the mailing list is needed.
- [ ] (tubemq) Sijie Guo
Comments:
- [ ] (tubemq) Zhijie Shen
Comments:
- [X] (tubemq) Jean-Baptiste Onofre
Comments: Slow bootstrapping, but it seems it moved forward.
I would be happy to help.
### IPMC/Shepherd notes:
Junping Du: The project get bootstrap a bit late due to misunderstanding
on Champion role of the project. The email list and JIRA are setup just
recently, so contributors and committers are still learning how to
communicate through JIRA and dev alias - it takes time but things are
getting better.
Justin Mclean: Your mentors can't help if you don't communicate on the
dev list. Your number one aim should be to move communication on list and
work with your mentors in the open to complete the bootstrap process. This
is the PPMC responsibility not just the mentors or the IPMC as mentioned in
the issues. Several mentors and IPMC requests have gone unanswered, please
make sure these are responded to.
Dave Fisher: It is important that PPMC Members drive the move with the
help of active Mentors. I feel that Junping is in a dual role but is less
experienced. Justin and JBO are the experienced mentors that will need to
step in with the guidance. Two months in including the year end holidays
the podling is actually doing OK.