Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
The Slides from the ESUG presentation are now inline here: https://www.slideshare.net/zweidenker/docker-and-pharo-zweidenker >>> >>> As presented on ESUG here is the brief description of one of our current >>> projects. >>> >>> Mobility Map >>> —— >>> >>> Mobility Map is a broker for mobility services. It offers multi-modal >>> routing search enabling users to find the best travel options between >>> locations. Travel options include car sharing, bikes, trains, busses etc. >>> Rented cars can be offered for ride sharing on booking time letting other >>> people find it to participate in the ride. Single travel options are >>> combined in travel plans that can be booked and managed in a very easy way. >>> >>> For this project main requirements were scalability to serve a large user >>> base and flexibility to add more additional providers to the broker. The >>> application has been realized using web technologies for the frontend and >>> pharo for the backend. Using a microservice architecture combined with a >>> broker it is easy to extend the platform with additional brokers. >>> Deployment is done using docker swarm for distributing dozens of pharo >>> images among multiple server machines connected by a message queue for the >>> communication. Pharo supported that scenario very well enabling us the meet >>> the requirements with less effort. >>> >>> Pharo turned out to be a perfect fit to develop the application in a agile >>> way. Small development cycles with continuous integration and continuous >>> delivery enables fast turnarounds for the customers to validate progress. >>> >>> This is a screenshot of the search page for multi-modal results: >>> >>> >>> >> >> > >
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
> Am 30.09.2018 um 13:01 schrieb Pierce Ng : > > On Wed, Sep 26, 2018 at 07:49:10PM +0200, Norbert Hartl wrote: And a lot more. This is a coarse grained overview over the architecture. I’m happy to answer further questions about this. [very nice writeup] > > Hi Norbert, > > Very nice write-up, thanks. > thanks > What persistence mechanism are you using - Gemstone/S, Glorp, Voyage, …? We use voyage with a mongo replica set. Norbert
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
On Wed, Sep 26, 2018 at 07:49:10PM +0200, Norbert Hartl wrote: >>> And a lot more. This is a coarse grained overview over the >>> architecture. I’m happy to answer further questions about this. >>> [very nice writeup] Hi Norbert, Very nice write-up, thanks. What persistence mechanism are you using - Gemstone/S, Glorp, Voyage, ...? Pierce
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
> Am 25.09.2018 um 17:44 schrieb Sven Van Caekenberghe : > > > >> On 25 Sep 2018, at 14:39, Norbert Hartl wrote: >> >> >> >>> Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe : >>> >>> Wow. Very nice, well done. >>> >>> Any chance on some more technical details, as in what 'connected by a >>> message queue for the communication' exactly means ? How did you approach >>> micro services exactly ? >>> >> Sure :) > > Thanks, this is very interesting ! > >> The installation spawns multiple physical machines. All the machines are >> joined to a docker swarm. The installation is reified as either task or >> service from the view on the docker swarm. Meaning you instantiate an >> arbitrary amount of services and docker swarm distributes them among the >> physical machines. Usually you don’t take control which is running where but >> you can. At this point you have spread dozens of pharo images among multiple >> machines and each of them has an IP address. Furthermore in docker swarm you >> have a reification of a network meaning that every instance in a network can >> see all other instances on this network. Each service can be reached by its >> service name in that network. Docker swarm does all the iptables/firewall >> and DNS setup for you. > > Are you happy with docker swarm's availability/fail-over behaviour ? In other > words: does it work when one image/instance goes bad, does it detect and > restore the missing functionality ? > Yes, I‘m very satisified. Instances are automatically restarted if they crash. And not necessarily on the same machine exactly how I expect it. Docker has something called Healthcheck. You can have a command executed every 20 seconds. I hooked this to a curl command and to your SUnit Rest handler. The rest is writing unit tests for server health. If tests fail in sequence the instances are taken out of operation and are replaced with a new instance. The same is done for updating. Instances are started in a fashion that one instance of the new image is started, if it survives a couple of health checks it is taken operational and an old one is taken out. Then the next new is started... For simple software updates you have zero-downtime deployment. >> In order to have communication between those runtimes we use rabbitmq >> because you were so nice writing a driver for it ;) The rabbitmq does have a >> support for cluster setup, meaning each of the physical machines has a >> rabbitmq installation and they know each other. So it does not matter to >> which instance you send messages to and on which you register for receiving >> messages. So every pharo image connects to the service rabbitmq and opens a >> queue for interaction. > > Same question: does RabbitMQ's clustering work well under stress/problems ? > Syncing all queues between all machines sounds quite heavy (I never tried it, > but maybe it just works). I did not yet have time to real stress test the queue. And you are right copying between nodes might be a lot but still I have the feeling it is better to have then a single instance but no real reason. We also use huge payloads which might have to change if we encounter problems. > >> Each service like the car sharing opens a queue e.g. /queue/carSharing and >> listens on it. The broker images are stateful so they open queues like >> /queue/mobility-map-afdeg32 where afdeg32 is the container id of the >> instance (hostname in docker). In each request the queue name to reply is >> sent as a header. So we can make sure that the right image gets the message >> back. This way we can have sticky sessions keeping volatile data in memory >> for the lifecycle of a session. There is one worker image which opens a >> queue /queue/mobility-map where session independent requests can be >> processed. > > I think I understand ;-) > >> In order to ease development we are sharing code between the broker and the >> micro service. Each micro service has a -Common package where the classes >> are in that build the interface. The classes in here are a kind of data >> entity facades. They use NeoJSON to map to and from a stream. The class name >> is send with the message as a header so the remote side knows what to >> materialize. The handling is unified for the four cases >> >> - Request as inquiry to another micro service >> - Response returns values to a Request >> - Error is transferred like a Response but is then signalled on the >> receiving side >> - Notification connects the announcers on the broker and the micro service >> side. > > Yes, makes total sense. > >> Asynchronous calls we solved using Promises and Futures. Each async call to >> the Q becomes a promise (that blocks on #value) and is combined to a future >> value containing all promises with support to generate a delta of all >> resolved promises. This we need because you issue a search that takes longer >> and you want to display results as
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
Yes, this is impressive. I agree that any technical details and architectural insight (no matter how high-level) would be useful. Related: There's enough in http://pharo.org/success that it could be sectioned by tags (industries, technologies, etc.). There's a lot there that could really be showcased. Sven Van Caekenberghe-2 wrote > Wow. Very nice, well done. > > Any chance on some more technical details, as in what 'connected by a > message queue for the communication' exactly means ? How did you approach > micro services exactly ? > >> On 25 Sep 2018, at 12:20, Norbert Hartl > norbert@ > wrote: >> >> As presented on ESUG here is the brief description of one of our current >> projects. >> >> Mobility Map >> —— >> >> Mobility Map is a broker for mobility services. It offers multi-modal >> routing search enabling users to find the best travel options between >> locations. Travel options include car sharing, bikes, trains, busses etc. >> Rented cars can be offered for ride sharing on booking time letting other >> people find it to participate in the ride. Single travel options are >> combined in travel plans that can be booked and managed in a very easy >> way. >> >> For this project main requirements were scalability to serve a large user >> base and flexibility to add more additional providers to the broker. The >> application has been realized using web technologies for the frontend and >> pharo for the backend. Using a microservice architecture combined with a >> broker it is easy to extend the platform with additional brokers. >> Deployment is done using docker swarm for distributing dozens of pharo >> images among multiple server machines connected by a message queue for >> the communication. Pharo supported that scenario very well enabling us >> the meet the requirements with less effort. >> >> Pharo turned out to be a perfect fit to develop the application in a >> agile way. Small development cycles with continuous integration and >> continuous delivery enables fast turnarounds for the customers to >> validate progress. >> >> This is a screenshot of the search page for multi-modal results: >> >> >> > -- Sent from: http://forum.world.st/Pharo-Smalltalk-Users-f1310670.html
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
> On 25 Sep 2018, at 14:39, Norbert Hartl wrote: > > > >> Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe : >> >> Wow. Very nice, well done. >> >> Any chance on some more technical details, as in what 'connected by a >> message queue for the communication' exactly means ? How did you approach >> micro services exactly ? >> > Sure :) Thanks, this is very interesting ! > The installation spawns multiple physical machines. All the machines are > joined to a docker swarm. The installation is reified as either task or > service from the view on the docker swarm. Meaning you instantiate an > arbitrary amount of services and docker swarm distributes them among the > physical machines. Usually you don’t take control which is running where but > you can. At this point you have spread dozens of pharo images among multiple > machines and each of them has an IP address. Furthermore in docker swarm you > have a reification of a network meaning that every instance in a network can > see all other instances on this network. Each service can be reached by its > service name in that network. Docker swarm does all the iptables/firewall and > DNS setup for you. Are you happy with docker swarm's availability/fail-over behaviour ? In other words: does it work when one image/instance goes bad, does it detect and restore the missing functionality ? > In order to have communication between those runtimes we use rabbitmq because > you were so nice writing a driver for it ;) The rabbitmq does have a support > for cluster setup, meaning each of the physical machines has a rabbitmq > installation and they know each other. So it does not matter to which > instance you send messages to and on which you register for receiving > messages. So every pharo image connects to the service rabbitmq and opens a > queue for interaction. Same question: does RabbitMQ's clustering work well under stress/problems ? Syncing all queues between all machines sounds quite heavy (I never tried it, but maybe it just works). > Each service like the car sharing opens a queue e.g. /queue/carSharing and > listens on it. The broker images are stateful so they open queues like > /queue/mobility-map-afdeg32 where afdeg32 is the container id of the instance > (hostname in docker). In each request the queue name to reply is sent as a > header. So we can make sure that the right image gets the message back. This > way we can have sticky sessions keeping volatile data in memory for the > lifecycle of a session. There is one worker image which opens a queue > /queue/mobility-map where session independent requests can be processed. I think I understand ;-) > In order to ease development we are sharing code between the broker and the > micro service. Each micro service has a -Common package where the classes are > in that build the interface. The classes in here are a kind of data entity > facades. They use NeoJSON to map to and from a stream. The class name is send > with the message as a header so the remote side knows what to materialize. > The handling is unified for the four cases > > - Request as inquiry to another micro service > - Response returns values to a Request > - Error is transferred like a Response but is then signalled on the receiving > side > - Notification connects the announcers on the broker and the micro service > side. Yes, makes total sense. > Asynchronous calls we solved using Promises and Futures. Each async call to > the Q becomes a promise (that blocks on #value) and is combined to a future > value containing all promises with support to generate a delta of all > resolved promises. This we need because you issue a search that takes longer > and you want to display results as soon as they are resolved not after all > haven been resolved. Which Promise/Future framework/library are you using in Pharo ? You did not go for single threaded worker images ? > And a lot more. This is a coarse grained overview over the architecture. I’m > happy to answer further questions about this. > > Norbert > >>> On 25 Sep 2018, at 12:20, Norbert Hartl wrote: >>> >>> As presented on ESUG here is the brief description of one of our current >>> projects. >>> >>> Mobility Map >>> —— >>> >>> Mobility Map is a broker for mobility services. It offers multi-modal >>> routing search enabling users to find the best travel options between >>> locations. Travel options include car sharing, bikes, trains, busses etc. >>> Rented cars can be offered for ride sharing on booking time letting other >>> people find it to participate in the ride. Single travel options are >>> combined in travel plans that can be booked and managed in a very easy way. >>> >>> For this project main requirements were scalability to serve a large user >>> base and flexibility to add more additional providers to the broker. The >>> application has been realized using web technologies for the frontend and >>>
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
> Am 25.09.2018 um 12:52 schrieb Sven Van Caekenberghe : > > Wow. Very nice, well done. > > Any chance on some more technical details, as in what 'connected by a message > queue for the communication' exactly means ? How did you approach micro > services exactly ? > Sure :) The installation spawns multiple physical machines. All the machines are joined to a docker swarm. The installation is reified as either task or service from the view on the docker swarm. Meaning you instantiate an arbitrary amount of services and docker swarm distributes them among the physical machines. Usually you don’t take control which is running where but you can. At this point you have spread dozens of pharo images among multiple machines and each of them has an IP address. Furthermore in docker swarm you have a reification of a network meaning that every instance in a network can see all other instances on this network. Each service can be reached by its service name in that network. Docker swarm does all the iptables/firewall and DNS setup for you. In order to have communication between those runtimes we use rabbitmq because you were so nice writing a driver for it ;) The rabbitmq does have a support for cluster setup, meaning each of the physical machines has a rabbitmq installation and they know each other. So it does not matter to which instance you send messages to and on which you register for receiving messages. So every pharo image connects to the service rabbitmq and opens a queue for interaction. Each service like the car sharing opens a queue e.g. /queue/carSharing and listens on it. The broker images are stateful so they open queues like /queue/mobility-map-afdeg32 where afdeg32 is the container id of the instance (hostname in docker). In each request the queue name to reply is sent as a header. So we can make sure that the right image gets the message back. This way we can have sticky sessions keeping volatile data in memory for the lifecycle of a session. There is one worker image which opens a queue /queue/mobility-map where session independent requests can be processed. In order to ease development we are sharing code between the broker and the micro service. Each micro service has a -Common package where the classes are in that build the interface. The classes in here are a kind of data entity facades. They use NeoJSON to map to and from a stream. The class name is send with the message as a header so the remote side knows what to materialize. The handling is unified for the four cases - Request as inquiry to another micro service - Response returns values to a Request - Error is transferred like a Response but is then signalled on the receiving side - Notification connects the announcers on the broker and the micro service side. Asynchronous calls we solved using Promises and Futures. Each async call to the Q becomes a promise (that blocks on #value) and is combined to a future value containing all promises with support to generate a delta of all resolved promises. This we need because you issue a search that takes longer and you want to display results as soon as they are resolved not after all haven been resolved. And a lot more. This is a coarse grained overview over the architecture. I’m happy to answer further questions about this. Norbert >> On 25 Sep 2018, at 12:20, Norbert Hartl wrote: >> >> As presented on ESUG here is the brief description of one of our current >> projects. >> >> Mobility Map >> —— >> >> Mobility Map is a broker for mobility services. It offers multi-modal >> routing search enabling users to find the best travel options between >> locations. Travel options include car sharing, bikes, trains, busses etc. >> Rented cars can be offered for ride sharing on booking time letting other >> people find it to participate in the ride. Single travel options are >> combined in travel plans that can be booked and managed in a very easy way. >> >> For this project main requirements were scalability to serve a large user >> base and flexibility to add more additional providers to the broker. The >> application has been realized using web technologies for the frontend and >> pharo for the backend. Using a microservice architecture combined with a >> broker it is easy to extend the platform with additional brokers. Deployment >> is done using docker swarm for distributing dozens of pharo images among >> multiple server machines connected by a message queue for the communication. >> Pharo supported that scenario very well enabling us the meet the >> requirements with less effort. >> >> Pharo turned out to be a perfect fit to develop the application in a agile >> way. Small development cycles with continuous integration and continuous >> delivery enables fast turnarounds for the customers to validate progress. >> >> This is a screenshot of the search page for multi-modal results: >> >> >> > >
Re: [Pharo-users] [Pharo-dev] [ANN] Success story Mobility Map
Wow. Very nice, well done. Any chance on some more technical details, as in what 'connected by a message queue for the communication' exactly means ? How did you approach micro services exactly ? > On 25 Sep 2018, at 12:20, Norbert Hartl wrote: > > As presented on ESUG here is the brief description of one of our current > projects. > > Mobility Map > —— > > Mobility Map is a broker for mobility services. It offers multi-modal routing > search enabling users to find the best travel options between locations. > Travel options include car sharing, bikes, trains, busses etc. Rented cars > can be offered for ride sharing on booking time letting other people find it > to participate in the ride. Single travel options are combined in travel > plans that can be booked and managed in a very easy way. > > For this project main requirements were scalability to serve a large user > base and flexibility to add more additional providers to the broker. The > application has been realized using web technologies for the frontend and > pharo for the backend. Using a microservice architecture combined with a > broker it is easy to extend the platform with additional brokers. Deployment > is done using docker swarm for distributing dozens of pharo images among > multiple server machines connected by a message queue for the communication. > Pharo supported that scenario very well enabling us the meet the requirements > with less effort. > > Pharo turned out to be a perfect fit to develop the application in a agile > way. Small development cycles with continuous integration and continuous > delivery enables fast turnarounds for the customers to validate progress. > > This is a screenshot of the search page for multi-modal results: > > >
