That’s great to hear. I would also be available to help review submissions.
> On Apr 6, 2022, at 8:14 AM, Sharan Foga <sha...@apache.org> wrote: > > Hi Paulo > > We have great news - the Performance Engineering track has been accepted so > we will be looking to encourage and promote CFP submissions for it. We are > also looking for reviewers to help us rate the submissions---if you are still > interested in doing that. ;-) > > Thanks > Sharan > >> On 2022/03/16 15:36:04 Sharan Foga wrote: >> Hi Paulo >> >> Thanks for the feedback. If we do get the track accepted then we will >> definitely be needing help reviewing the submissions - so may take you up on >> your offer :-) >> >> Thanks >> Sharan >> >>> On 2022/03/14 16:32:23 Paulo Motta wrote: >>> This Apachecon track sounds fun! I hope someone from the Cassandra >>> community steps up to help on this track. >>> >>> I would be happy to help on reviews but not organize the event per se as I >>> will likely not attend the event. >>> >>>> Em sex., 11 de mar. de 2022 às 09:26, sharanf <sha...@apache.org> escreveu: >>> >>>> Hi All >>>> >>>> The call for tracks for ApacheCon NA is open. There is a suggestion to >>>> try and run a Performance Engineering track at ApacheCon this year. At >>>> the end of the message I have included some details including a >>>> definition of what we mean by it and some reasoning about why it could >>>> be good to run. We have a list of projects that have something to do >>>> with performance engineering and if you take a look - you will see that >>>> this project is on the list! >>>> >>>> So what I need is a some feedback as to whether the community thinks >>>> that this could be an interesting track topic to run at ApacheCon..and >>>> more importantly would the community be willing to submit talks for it >>>> or attend ApacheCon to see it. >>>> >>>> Like I say - this is just an idea at this stage. If the Performance >>>> Engineering track does get approval to be included at ApacheCon - do we >>>> have any volunteers willing to help with managing and promoting the >>>> track on behalf of the project? >>>> >>>> Thanks >>>> Sharan >>>> >>>> ----------------------------- >>>> >>>> *Performance Engineering* is the science and practice of engineering >>>> software with the required performance and scalability characteristics. >>>> Many Apache projects focus on solving hard Big Data performance and >>>> scalability challenges, while others provide tools for performance >>>> engineering - but there are few projects that don’t care about some >>>> aspect of software performance. >>>> >>>> This track will enable Apache projects members to share their >>>> experiences of performance engineering best practices, tools, >>>> techniques, and results, from their own communities, with the benefits >>>> of cross-fertilization between projects. Performance Engineering in the >>>> wider open source community is pervasive and includes methods and tools >>>> (including automation and agile approaches) for performance: >>>> architecting and design, benchmarking, monitoring, tracing, analysis, >>>> prediction, modeling and simulation, testing and reporting, regression >>>> testing, and source code analysis and instrumentation techniques. >>>> >>>> Performance Engineering also has wider applicability to DevOps, the >>>> operation of cloud platforms by managed service providers (hence some >>>> overlap with SRE - Site Reliability Engineering), and customer >>>> application performance and tuning. This track would therefore be >>>> applicable to the wider open source community. >>>> >>>> *SUPPORTING DETAILS* >>>> >>>> *Google Searches* >>>> Google “Open source performance engineering” has 4,180,000,000 results >>>> Google “site:apache.org<http://apache.org> performance” has 147,000 >>>> results >>>> >>>> *Apache Projects *which may have some interest in, or focus on, >>>> performance (just the top results): >>>> JMeter, Cassandra, Storm, Spark, Samza, Pulsar, Kafka, Log4J, SystemML, >>>> Drill, HTTP Server, Cayenne, ActiveMQ, Impala, Geode, Flink, Ignite, >>>> Impala, Lucene, TVM, Tika, YuniKorn, Solr, Iceberg, Dubbo, Hudi, >>>> Accumulo, Xerces, MXNet, Zookeeper >>>> >>>> *Incubator projects *which may have some interest in, or focus on, >>>> performance**(again just top results): >>>> Crail, Eagle, Nemo, Skywalking, MXnet, HAWQ, Mnemonic, CarbonData, >>>> Drill, ShenYu, Tephra, Sedona >>>> >>>> *References *(randomly selected to show the range of open-source >>>> performance engineering topics available, rather than the quality of >>>> articles): >>>> >>>> 1. Performance Engineering for Apache Spark and Databricks Runtime >>>> ETHZ, Big Data HS19 >>>> < >>>> https://archive-systems.ethz.ch/sites/default/files/courses/2019-fall/bigdata/Databricks%20ETHZ%20Big%20Data%20HS19.pdf >>>>> >>>> 2. Real time insights into LinkedIn's performance using Apache Samza >>>> < >>>> https://engineering.linkedin.com/samza/real-time-insights-linkedins-performance-using-apache-samza >>>>> >>>> 3. A day in the life of an open source performance engineering team >>>> <https://opensource.com/article/19/5/life-performance-engineer> >>>> 4. Locating Performance Regression Root Causes in the Field Operations >>>> of<https://ieeexplore.ieee.org/document/9629300>Web-based Systems: >>>> An Experience Report Published in: IEEE Transactions on Software >>>> Engineering (Early Access) >>>> <https://ieeexplore.ieee.org/document/9629300> >>>> 5. How to Detect Performance Changes in Software History: Performance >>>> Analysis of Software System Versions >>>> <https://dl.acm.org/doi/10.1145/3185768.3186404> >>>> 6. Performance-Regression Pitfalls Every Project Should Avoid >>>> < >>>> https://www.eetimes.eu/performance-regression-pitfalls-every-project-should-avoid/ >>>>> >>>> 7. How to benchmark your websites with the open source Apache Bench >>>> tool >>>> < >>>> https://www.techrepublic.com/article/how-to-benchmark-your-websites-with-the-open-source-apache-bench-tool/ >>>>> >>>> 8. Benchmarking Pulsar and Kafka - A More Accurate Perspective on >>>> Pulsar’s Performance >>>> < >>>> https://streamnative.io/blog/tech/2020-11-09-benchmark-pulsar-kafka-performance/ >>>>> >>>> 9. Performance-Analyse: Apache Cassandra 4.0.0 Release >>>> <https://benchant.com/blog/cassandra-4-performance> >>>> 10. Log4J Performance - This page compares the performance of a number >>>> of logging frameworks >>>> <https://logging.apache.org/log4j/2.x/performance.html> >>>> 11. SystemML Performance Testing >>>> <https://systemds.apache.org/docs/1.0.0/python-performance-test.html> >>>> >>>> >>> >>
