We are planning to refactor our J2EE Monolith into Microservicesapplication. We are planning to build using Spring, Spring boot, Spring cloud and Pivotal cloud foundry as PaaS.
When i was validating whether my current application is cloud ready using The twelve-factor app , the important think i noticed is the usuage of 'HTTP Sessions' in our application. The link suggestes
Some web systems rely on “sticky sessions” – that is, caching user
session data in memory of the app’s process and expecting future
requests from the same visitor to be routed to the same process.
Sticky sessions are a violation of twelve-factor and should never be
used or relied upon. Session state data is a good candidate for a
datastore that offers time-expiration, such as Memcached or Redis.
I don't understand how can i use im-memory data store to track the user session? Could someone please explain? Should i use some unique key for users to retrieve information form in-memory data store?
As a good example, you can have a look on this explanation of Spring Session implementation
https://www.infoq.com/articles/Next-Generation-Session-Management-with-Spring-Session
It has a reference to Redis storage, which you can bind to your application from PCF services.
Related
I need to create a API where the Vendors will push the data to the server using REST calls and this data needs to further pushed to a user on mobile app(using Websocket guessing as of now) to whom the data belongs.
For Vendors to use REST API : I need to check the Vendor credential and Write that data to DB.
I am keen to know what approach should I use ? Should I use AWS API Gateway which can help for security and scalability.
and while using AWS API Gateway - what would be a better approach to have EC2 Endpoint or Lambda Endpoint.
Using EC2 vs Lambda depends on how you want to design your services and specific use cases. Going serverless is a trend these days, but you do not need to go serverless, just for the sake of being serverless.
For your use case, If the REST API you will expose updates a Database, let's say RDS, Lambda function probably is not an ideal choice. As you will need to open a connection every time the lambda function is invoked. Moreover, if you are running the lambda in a NO VPC config, You will need to publicly expose your RDS port. If its DynamoDB, it works out well.
But again, you want to push out the update to Mobile apps over say web sockets. You definitely need a WebSocket Server somewhere, and I guess its EC2.
You may design your application in way such that all your business logic resides in the lambda functions, updates the DB, posts a message to an SQS queue. The WebSocket server can then pick up messages from the SQS queue and post updates. This decouples your application architecture. This is just one approach and wont scale horizontally out of the box.
OR - You may choose to put everything in one EC2 instance, expose a REST API that updates the DB and also posts updates to the WebSocket connection.
I am building a JavaFX client application communicating with Spring MVC Restful server(Spring boot 1.4.1) application which works as expected.
Some features require fast interaction with the server to validate limits and availability before proceeding to next input example check if member number insert is valid and if has exceeded limit to insert, during accumulation of records(each confirmed record temporarily stored in a tableview before sent to server for storage) before the records are actually saved.
Within JavaFX and Spring framework(in both frontend and backend) scope, how can such kind of features made look more interactive(or live) than normal "let-me-wait-for-response" approach
If question is not clear, just ask, otherwise i think it is
It appears that the only interaction you have between client (JavaFX) and server (SpringBoot) is through a REST API. This will make short bursts of data (such a validation) take longer.
Switching to another communication mechanism (for example gRPC or Netty with Msgpack) could help. Note that once you open the door for non-REST calls it'll make you re-think the use of REST in the first place.
Non-REST communication may not be an option depending on your requirements (firewalls, etc) or may need additional setup in order to surmount other obstacles, in other words, there's no free lunch.
In a distributed systems environment, we have a RESTful service that needs to provide high read throughput at low-latency. Due to limitations in the database technology and given its a read-heavy system, we decided to use MemCached. Now, in a SOA, there are atleast 2 choices for the location of the cache, basically client looks up in Cache before calling server vs client always calls server which looks up in cache. In both cases, caching itself is done in a distributed MemCached server.
Option 1: Client -> RESTful Service -> MemCached -> Database
OR
Option 2: Client -> MemCached -> RESTful Service -> Database
I have an opinion but i'd love to hear arguments for and against either option from SOA experts in the community. Please assume either option is feasible, its a architecture question. Appreciate sharing your experience.
I have seen the
Option 1: Client -> RESTful Service -> Cache Server -> Database
working very well. Pros IMHO are that you are able to operate wtih and use this layer in a way allowing you to "free" part of the load on the DB. Assuming that your end-users can have a lot of similar requests and after all the Client can decide what storage to spare for caching. Also how often to clear it.
I prefer Option 1 and I am currently using it. In this way it is easier to control the load on the DB (just as #ekostatinov mentioned). I have lots of data that are required for every user in the system, but the data is never changed (such as some system rules, types of items, etc). It really reduces the DB load. In this way you can also control the behavior of the cache (such as when to clear the items).
Option 1 is the prefered option as it makes memcache an implementation detail of the service. the other option means that if the business changes and things can't be kept in the cache (or other can etc.) the clients would have to change. Option 1 hides all that behind the service interface.
Additionally option 1 lets you evolve the service as you wish. e.g. maybe later you think you need a new technology, maybe you'd solve the performance problem with the DB etc. Again, option 1 lets you make all these changes without dragging the clients into the mess
Is the REST ful API exposed to external consumers. In that case it is up to the consumer to decide if they want to use a cache and how much stale data can they use.
As for as the REST ful service goes, the service is the container of business logic and it is the authority of data, so it decides how much to cache, cache expiry, when to flush etc. A client consuming the REST service always assumes that the service is providing it with the latest data. And hence option 1 is preferred.
Who is the client in this case?
Is it a wrapper for your REST API. Are you providing both client and the service.
I can share my experience with Enduro/X middleware implementation. For local XATMI service calls any client process connects to shared memory (LMDB) and checks the result there. If there is response saved it returns data directly from shm. If data is not there, client process goes the longest path and performs the IPC. In case of REST access, network clients still performs the HTTP invocation, but HTTP server as XATMI client returns the data from shared mem. From real life, this technique was greatly boosting the web frontend web application which used middleware via REST calls.
I have a RESTful web-service application that I developed using the Netbeans IDE. The application uses MySQL server as its back end server. What I am wondering now is how often a client application that uses my RESTful application would refresh to reflect the data change in the server.
Are there any default pull intervals that clients get from the RESTful application? Does the framework(JAX-RS) do something about it Or is that my business to take care of.
Thanks in advance
#Abraham
There are no such rules. Only thing you can use for properly implementing this is HTTP's caching capabilities. Service must include control information how long representation of a particular resource can be cached, revalidated, never cached etc...
On client application side of things each client may decide it's own path how it will keep itself in sync with a service. It can be done by locally storing data and serve end user from local cache etc... Service can not(and shouldn't know) how clients are implemented, only thing service can do is to include caching information in response messages as i already mentioned above.
It is your responsibility to schedule the service to execute again and again. We can set time out interval but there is no pull interval.
I have a bunch of web servers(frontends) behind balancer. Each apache process runs with it's own user for every virtualhost. Code that apache runs is PHP and it's not trusted code.
I need to have shared (between web servers) session storage and limit user(vhost) to only access it's session storage. So I want to avoid one tenant to be able to purge or corrupt memcached stored data.
So I basically looking for solution to authenticate users + create private buckets.
I know there is always MySQL way avaliable but I want to avoid performance penalty introduced by SQL layer.
Any solution in your mind so far?
I found product called CouchBase which fully comply with my requirements. It has buckets along with memcache caching layer and access protocol. It has SASL authentication and a bonus of load balancing and fail tolerance.