Hi Sijie (and everyone else that may be interested) We have great news - the Performance Engineering track has been accepted for ApacheCon NA in New Orleans. So next we will be looking to promote and encourage people to submit something for the CFP.
If you'd like to submit something then you can find the call for proposals (CFP) on the https://apachecon.com/acna2022/ website and please don't forget to select 'Performance Engineering' as the talk category. We are very excited to have this new track available and are hoping that we get some interesting submissions. Thanks Sharan On 2022/03/19 14:24:38 Sharan Foga wrote: > Hi Sijie > > Thanks very much for the response and interest! I will post an update about > the track as soon as I have one. > > Thanks > Sharan > > On 2022/03/15 23:59:46 Sijie Guo wrote: > > Sharan, > > > > I think it is a very great idea to have a performance engineering track. > > Some committers and I are definitely interested in contributing talks to > > this track. > > > > - Sijie > > > > On Fri, Mar 11, 2022 at 4:44 AM sharanf <sha...@apache.org> wrote: > > > > > 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. 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 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> > > > > > > > > >
