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ben stopford gently flexing the grid book: designing event driven systems i wrote a book: designing event driven systems pdf epub apr 27th, 2018 the data dichotomy data systems are about exposing data, services are about hiding it. dec 14th, 2016 elements of scale: composing and scaling data platforms this transcribed talk explores a range of data platforms through a lens of basic hardware and software tradeoffs. apr 28th, 2015 log structured merge trees a detailed look at the interesting lsm file organisation seen in bigtable, cassandra and most recently mongodb feb 14th, 2015 talks (all) devoxx-2017: rethinking services with stateful streams (video) stratasa-2017: the data dichotomy confluent-2017: microservices with kafka series (video) qcon-2017: the power of the log (video) codemesh-2016: streaming, databases & distributed systems – bridging the divide jaxlondon-2016: microservices for a streaming world (the data dichotomy) qcon-2016: microservices for a streaming world ( video ) codemesh-2015: contemporary approaches to data at scale ( video ) øredev-2015: the future of data technology ( video ) jaxlondon-2015: intuitions for scaling data-centric architectures ( video ) progscon/jaxf-2015: elements of scale rbs-2014: scaling data bigdatacon-2013: the return of big iron? jax-2013: the return of big iron? qcon-2012: where big data meets big database ( video ) qcon-2012: progressive architectures at rbs ( video ) javaone-2011: balancing replication and partitioning in a distributed java database qcon-2011: beyond the data grid ( video ) ucl-2011: a paradigm shift: the increasing dominance of memory-oriented solutions for high performance data access cosig-2011: oracle coherence implementation patterns (special interest group) icst-2011: test-oriented languages: a new era? icst-2011: enabling development practices in remote locations birkbeck-2011: data storage for extreme use cases reftest-2010: has mocking gone wrong? rbs-2009: data grids with oracle coherence brunel-2008: the architect's two hats brunel-2007: architecture and design in industry essays (all) the data dichotomy (2016) the benefits of “in-memory” data are often overstated (2016) elements of scale: composing and scaling data platforms (2015) upside down databases: bridging the operational and analytic worlds with streams (2015) log structured merge trees (2015) building a career in technology (2015) a world of chinese whispers (2014) database y (2013) the big data conundrum (2012) where does big data meet big database? (2012) a story about george (2012) the rebirth of the in-memory database (2011) is the traditional database a thing of the past? (2009) shared nothing v.s. shared disk architectures: an independent view (2009) component software. where is it going? (2005) do metrics have a place in software engineering today? (2004) test driven development (all) test oriented languages: is it time for a new era? (2011) beyond stubs: why we need interaction testing (2010) isolating functional units: why we need stubs (2010) are mocks all they are cracked up to be? (2010) coherence (all) about there are four ‘picks’ above. general content is categorised to the left. below is a more traditional chronological blog. twitter , rss , github , photography , full bio . data tech (all) best of vldb 2014 (2015) a guide to building a central, consolidated data store for a company (2014) an initial look at actian’s ‘sql in hadoop’ (2014) the best of vldb 2012 (2012) thinking in graphs: neo4j (2012) a brief summary of the nosql world (2012) odc – a distributed datastore built at rbs (2012) looking at intel xeon phi (kinghts corner) (2012) team / process / interviewing (all) the iffy tractor (can they code oo?) (2011) the business analyst test (2011) distributing skills across a continental divide (2011) learning practices for distributed teams (icst) (2011) interviewing: the importance of examining applied knowledge (2010) mapping personal practices (2010) four hpc architecture questions – with answers (2009) blog/news rest request-response gateway jun 7th, 2018 this post outlines how you might create a request-response gateway in kafka using the good old correlation id trick and a shared response topic. it’s just a sketch. i haven’t tried it out. a rest gateway provides an efficient request-response bridge to kafka. this is in some ways a logical extension of the rest proxy, wrapping the concepts of both a request and a response. what problem does it solve? allows you to contact a service, and get a response back, for example: to display the contents of the user’s shopping basket to validate and create a new order. access many different services, with their implementation abstracted behind a topic name. simple restful interface removes the need for asynchronous programming front-side of the gateway. so you may wonder: why not simply expose a rest interface on a service directly? the gateway lets you access many different services, and the topic abstraction provides a level of indirection in much the same way that service discovery does in a traditional request-response architecture. so backend services can be scaled out, instances taken down for maintenance etc, all behind the topic abstraction. in addition the gateway can provide observability metrics etc in much the same way as a service mesh does. you may also wonder: do i really want to do request response in kafka? for commands, which are typically business events that have a return value, there is a good argument for doing this in kafka. the command is a business event and is typically something you want a record of. for queries it is different as there is little benefit to using a broker, there is no need for broadcast and there is no need for retention, so this offers little value over a point-to-point interface like a http request. so the latter case we wouldn’t recommend this approach over say http, but it is still useful for advocates who want a single transport and value that over the redundancy of using a broker for request response (and yes these people exist). this pattern can be extended to be a sidecar rather than a gateway also (although the number of response topics could potentially become an issue in an architecture with many sidecars). implementation above we have a gateway running three instances, there are three services: orders, customer and basket. each service has a dedicated request topic that maps to that entity. there is a single response topic dedicated to the gateway. the gateway is configured to support different services, each taking 1 request topic and 1 response topic. imagine we post and order and expect confirmation back from the orders service that it was saved. this work as follows: the http request arrives at one node in the gateway. it is assigned a correlation id. the correlation id is derived so that it hashes to a partition of the response topic owned by this gateway node (we need this to route the request back to the correct instance). alternatively a random correlation id could be assigned and the request forwarded to the gateway node that owns the corresponding partition of the response topic. the request is tagged with a unique correlation id and the name of the gateway response topic (each gateway has a dedicated response topic) then forwarded to the orders topic. the http request is then parked in the webserver. the orders service processes the request and replies on the supplied response topic (i.e. the response topic of the rest gateway), including the correlation id as the key of the response message. when the rest gateway receives the response, it extracts the correlation id key and uses it to unblock the outstanding request so it responds to the user http request. exactly the same process can be used for get requests, although providing streaming gets will require some form of batch markers or similar, which would be awkward for services to implement probably necessitating a client-side

URL analysis for benstopford.com

http://www.benstopford.com/2011/10/23/slides-for-financial-computing-course-ucl/
http://www.benstopford.com/2015/03/08/best-of-vldb-2014/
http://www.benstopford.com/category/coherence/
http://www.benstopford.com/2010/02/18/beyond-stubs-why-we-need-interaction-testing/
http://www.benstopford.com/category/talks/
http://www.benstopford.com/2011/03/03/learning-practices-for-distributed-teams/
http://www.benstopford.com/2011/11/04/coherence-implementation-patterns-slides-from-coherence-sig/
http://www.benstopford.com/2004/03/14/do-metrics-have-a-place-in-software-engineering-today/
http://www.benstopford.com/2013/11/22/database-y/
http://www.benstopford.com/2010/11/14/interviewing-the-importance-of-examining-applied-knowledge/
http://www.benstopford.com/2012/10/28/the-best-of-vldb-2012/
http://www.benstopford.com/2013/11/01/slides-from-jax-london/
http://www.benstopford.com/2011/05/11/the-iffy-tractor-can-they-code-oo/
http://www.benstopford.com/2013/03/27/the-return-of-big-iron-big-data-2013/
http://www.benstopford.com/2018/06/07/rest-request-response-gateway/

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Domain Name: BENSTOPFORD.COM
Registry Domain ID: 149913809_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.tucows.com
Registrar URL: http://www.tucowsdomains.com
Updated Date: 2017-03-09T14:02:46Z
Creation Date: 2005-04-08T13:26:13Z
Registry Expiry Date: 2018-04-08T13:26:13Z
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  PORT 43

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  NAME benstopford.com

  CHANGED 2017-03-09

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