Thank you Sharan! I will try to submit a "What we've learned from 11+ years of (nearly) continuous Lucene nightly benchmarks" talk soon!
Mike McCandless http://blog.mikemccandless.com On Wed, Apr 6, 2022 at 11:25 AM Sharan Foga <[email protected]> wrote: > Hi Mike (and everyone that is interested) > > We have great news - the Performance Engineering track has been accepted > for ApacheCon NA in New Orleans. The CFP is open and you can submit your > proposal on the https://apachecon.com/acna2022/ website. > > Please don't forget to select 'Performance Engineering' as the track > category. And we are looking forward to receiving some interesting > submissions. ;-) > > Thanks > Sharan > > On 2022/03/19 14:27:28 Sharan Foga wrote: > > 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] > > > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > >
