Hi Mike 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 2022/03/14 15:24:46 Michael McCandless wrote: > Hi Sharan, > > I think this is indeed a very interesting topic and would make a good > ApacheCon track! It's a great idea. > > In Lucene development we struggle with proper performance measurement > often. We have a set of external benchmarking tools ( > https://github.com/mikemccand/luceneutil ) for this purpose but they are > complex and tricky to set up and use. Java has noisy performance from JVM > instance to instance, further complicating things. > > Drawing attention to this problem and sharing ideas would be really > helpful, not just for Lucene but other complex Java projects. > > I would most likely be able to give a talk about how we > approach Performance Engineering in Lucene, but probably don't have > enough bandwidth to help organize/run the full track. > > Thanks, > > Mike McCandless > > http://blog.mikemccandless.com > > On Fri, Mar 11, 2022 at 5:17 PM kujira m <[email protected]> wrote: > > > I'd like to unsubscribe the newsletter. > > > > 2022年3月11日(金) 22:09 sharanf <[email protected]>: > > > >> 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 > >> > > >> > >> > >> --------------------------------------------------------------------- > >> To unsubscribe, e-mail: [email protected] > >> For additional commands, e-mail: [email protected] > >> > >> > --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
