I have an application separated in various OSGI bundles which run on a single Apache Karaf instance. However, I want to migrate to a microservice framework because
Apache Karaf is pretty tough to set up due its dependency mechanism and
I want to be able to bring the application later to the cloud (AWS, GCloud, whatever)
I did some research, had a look at various frameworks and concluded that Quarkus might be the right choice due to its container-based approach, the performance and possible cloud integration opportunities.
Now, I am struggeling at one point and I didn't find a solution so far, but maybe I also might have a misunderstanding here: my plan is to migrate almost every OSGI bundle of my application into a separate microservice. In that way, I would be able to scale horizontally only the services for which this is necessary and I could also update/deploy them separately without having to restart the whole application. Thus, I assume that every service needs to run in a separate Quarkus instance. However, Quarkus does not not seem to support this out of the box?!? Instead I would need to create a separate configuration for each Quarkus instance.
Is this really the way to go? How can the services discover each other? And is there a way that a service A can communicate with a service B not only via REST calls but also use objects of classes and methods of service B incorporating a dependency to service B for service A?
Thanks a lot for any ideas on this!
I think you are mixing some points between microservices and osgi-based applications. With microservices you usually have a independent process running each microservice which can be deployed in the same o other machines. Because of that you can scale as you said and gain benefits. But the communication model is not process to process. It has to use a different approach and its highly recommended that you use a standard integration mechanism, you can use REST, you can use Json RPC, SOAP, or queues or topics to use a event-driven communication. By this mechanisms you invoke the 'other' service operations as you do in osgi, but you are just using a different interface, instead of a local invocation you do a remote invocation.
Service discovery is something that you can do with just Virtual IP's accessing other services through a common dns name and a load balancer, or using kubernetes DNS, if you go for kubernetes as platform. You could use also a central configuration service or let each service register itself in a central registry. There are already plenty different flavours of solutions to tackle this complexity.
Also more importantly, you will have to be aware of your new complexities, but some you already have.
Contract versioning and design
Synchronous or asynchronous communication between services.
How to deal with security in the boundary of the services / Do i even need security in most of my services or i just need information about the user identity.
Increased maintenance cost and redundant side code for common features (here quarkus helps you a lot with its extensions and also you have microprofile compatibility).
...
Deciding to go with microservices is not an easy decision and not one that should be taken in a single step. My recommendation is that you analyse your application domain and try to check if your design is ok to go with microservices (in terms of separation of concenrs and model cohesion) and extract small parts of your osgi platform into microservices, otherwise you mostly will be force to make changes in your service interfaces which would be more difficult to do due to the service to service contract dependency than change a method and some invocations.
We need to find best way to address distributed transaction management in our microservices architecture.
Here is the Problem Statement.
We have one Composite microservice which shall interact with underlying other 2 Atomic microservices (Which are meant for specific purpose obviously) and have separate database e.g. We can consider these 2 microservices as
STUDENT_SERVICE (STU_DB)
TEACHER_SERVICE (TEACHR_DB)
Here in Composite Service Usecase is like user (Administrator) can assign a Teacher to a student for the specific course etc.
I wonder how can we address this problem in one transaction as each servie (STUDENT_SERVICE and TEACHER_SERVICE ) has separate DB and all should happen in one transaction either commit or rollback.
Since those 2 services are separate and I see JTA would not be of help as it is meant for having these 2 applications (services) deployed on same application server!
I have opted out JTA as mentioned above
//Pseudo Code
class CompositeService{
AssignStaff(resquest){
//txn Start
updateStudentServiceAPI(request);
UpdateTeacherServiceAPI(request);
//txn End
}
}
System should be in consistent state after api execution
This is a tricky question even it's not obvious at the first sight.
The functionality you call for is understood to be an anti-pattern for microservice architecture.
Microservice architecture is in general a distributed system. Transactions in distributed systems are hard (see https://martin.kleppmann.com/2015/09/26/transactions-at-strange-loop.html). Your application consists from two services.
The JTA is a Java API for ACID style transactions. ACID transactions usually requires locks to be established in databases. As the transaction spans over multiple services (in your case there are two) then a failure of one service can block processing of the other service. In such case you are loosing the advantage of the microservice architecture - loose coupling and Independence of the services. You can end up of building a distributed monolith (see nice article https://blog.christianposta.com/microservices/the-hardest-part-about-microservices-data/).
Btw. there are several discussion on the topic of transactions in microservices here at Stackoverflow. Just search or check e.g.
Distributed transactions in microservices
Transactions in microservices
Transactions across REST microservices?
What are your options
(disclaimer: I'm a developer for http://narayana.io and presented options are from perspective of Java EE and Narayana. There could be other projects providing similar functionality. Plus, even Narayana integrates nicely with Spring you will possibly need to handle some integration issues.)
you really need to run the ACID style transaction in your project - aka you insists you need the transaction behaviour in way you describe. Then you need to span transaction over services. Then if services communicate over REST you can consider for example Narayana REST-AT (http://jbossts.blogspot.com/2011/03/rest-cloud-and-transactions.html, start looking into quickstart here https://github.com/jbosstm/quickstart/tree/master/rts)
you relax your requirements for atomicity and then you can cosider some transaction model relaxing the consistency (you are fine to be eventual consistent). You can consider for example LRA (https://github.com/eclipse/microprofile-lra/blob/master/spec/src/main/asciidoc/microprofile-lra-spec.adoc). (Unfortunately the spec and implementation is still not ready but PoC could be run on current state.)
you want to use a different approach for transaction processing completely. Then you can investigate on event sourcing. You would deploy e.g. Apache Kafka and send events for updates to the event store. Each service will reads those events and updates independently the DBs.
I'm fairly new to Microservices...
I've taken an interest in learning more about two main patterns like service discovery and circuit breaker and I have conducted research on how these could be implemented.
As a Java Developer, I'm using Spring Boot. From what I understand, these patterns are useful if microservices communicate via HTTP.
One of the topics I've recently seen is the importance of event-driven architecture, which makes use of an event message bus that services would use to send messages to for other services, which subscribe to the bus
and process the message.
Given this event-driven nature, how can service-discovery and circuit breakers be achieved/implemented, given that these are commonly applicable for services communicating via HTTP?
From what I understand, these patterns are useful if microservices communicate via HTTP.
It is irrelevant that the communication is HTTP. The circuit breaker is useful in prevention of cascade failures that are more probable to occur in the architectures that use a synchronous communication style.
Event-driven architectures are in general asynchronous so cascade failure is less probable to occur.
Service discovery is used in order for the microservices to discover each other but in Event-driven architectures microservices communicate only to the messaging infrastructure (i.e. the Event store in Event sourcing) so discoverability could be used only at the infrastructure level.
I. circuit breaker and service discovery are patterns. When we say Pattern they can be implemented with any programming language. 'HTTP' protocol is for transfer of data.
circuit breaker can be implemented within Java. You can find many implementations (of course, with varying capabilities and interpretation of pattern) on github.
Some of the well-known, built for purpose implementations are :
Hysterix from NetflixOSS For using Hysterix: You can follow Spring Guide - Spring Circuit Breaker
Apache Polygene - which has example of JMX circuit breaker
Resilience4j
II. About,
Given this event-driven nature, how can service-discovery and circuit
breakers be achieved/ implemented, given that these are commonly
applicable for services communicating via HTTP?
It seems you need bit more research on topic of Microservices interactions.
There are two ways to which microservices interactions are possible. You have to choose one over the other. You can/should not mix both.
Orchestration: An interaction style that has an intelligent controller that dispatches events to processes. Please note the word 'processes' which is representing business processes here. Orchestration style was preferred in old SOA implementations as well.
Choreography: An interaction style that allows processes to subscribe to events and handle them independently or through integration with other processes without the need for a central controller.
These topics are greatly covered under
Orchestration vs. Choreography
Need of Service Discovery:
With choreography, two or more microservices can coordinate their activities and processes to share information and value.
But, these microservices may not be aware of each other's existence i.e. There are no hard-coded or service references of dependency endpoints configured or coded into them. Why we do this, is for avoiding any kind of coupling between services. So, the question remains is how one service, if required will find another services' endpoint? This is where service discovery mechanism is used.
Another perspective is, with microservices deployment with containers etc, microservices endpoints will not be even tied to any hosts etc. [due to spin-up and spin-down of containers]. So, for this case as well, we need 'service discovery' mechanism.
So, In service discovery mechanism, a centralized service discovery tool helps services to register themselves and to discover other services via a DNS or HTTP interface.
Service discovery can be implemented with
1. Server-side service discovery
2. Client Side service discovery
Consul,etcd, zookeeper are some of the key-tools names within service discovery space.
Spring Boot integrates well with Spring Cloud. And Spring Cloud provides Eureka (for service discovery) as well as Hystrix (for circuit breaker patterns). Also, Spring Cloud Stream to provide event driven patterns
Very easy to use with Spring Boot
I believe there is a misunderstanding in the question in that you assume that event-driven architectures cannot be implemented on top of HTTP.
An event-driven architecture may be implemented in many different ways and (when the architecture is that of a distributed system), on top of many different protocols.
It can be implemented using a message broker (i.e. Kafka, RabbitMQ, ActiveMQ, etc) as you suggested it too. However, this is just a choice and certainly not the only way to do it.
For example, the seminal book Building Microservices by Sam Newman, in Chapter 4: Integration, under Implementing Asynchronous Event-Based Collaboration says:
“Another approach is to try to use HTTP as a way of propagating
events. ATOM is a REST-compliant specification that defines semantics
(among other things) for publishing feeds of resources. Many client
libraries exist that allow us to create and consume these feeds. So
our customer service could just publish an event to such a feed when
our customer service changes. Our consumers just poll the feed,
looking for changes. On one hand, the fact that we can reuse the
existing ATOM specification and any associated libraries is useful,
and we know that HTTP handles scale very well. However, HTTP is not
good at low latency (where some message brokers excel), and we still
need to deal with the fact that the consumers need to keep track of
what messages they have seen and manage their own polling schedule.
I have seen people spend an age implementing more and more of the
behaviors that you get out of the box with an appropriate message
broker to make ATOM work for some use cases. For example, the
Competing Consumer pattern describes a method whereby you bring up
multiple worker instances to compete for messages, which works well
for scaling up the number of workers to handle a list of independent
jobs. However, we want to avoid the case where two or more workers see
the same message, as we’ll end up doing the same task more than we
need to. With a message broker, a standard queue will handle this.
With ATOM, we now need to manage our own shared state among all the
workers to try to reduce the chances of reproducing effort. If you
already have a good, resilient message broker available to you,
consider using it to handle publishing and subscribing to events. But
if you don’t already have one, give ATOM a look, but be aware of the
sunk-cost fallacy. If you find yourself wanting more and more of the
support that a message broker gives you, at a certain point you might
want to change your approach.”
Likewise, if your design uses a message broker for the event-driven architecture, then I'm not sure if a circuit breaker is needed, because in that case the consumer applications control the rate at which event messages are being consumed from the queues. The producer application can publish event messages at its own pace, and the consumer applications can add as many competing consumers as they want to keep up with that pace. If the server application is down the client applications can still continue consuming any remaining messages in the queues, and once the queues are empty, they will just remain waiting for more messages to arrive. But that does not put any burden on the producer application. The producer and the consumer applications are decoupled in this scenario, and all the work the circuit breaker does in other scenarios would be solved by the message broker application.
Somewhat similar can be said of the service discovery feature. Since the producer and the consumer do not directly talk to each other, but only through the message broker, then the only service you need to discover would be the message broker.
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Can someone please explain to me about Hystrix? I googled it, but still, I am not clear.
What is Hystrix?
Why do we use Hystrix?
Please provide me with an example of Hystrix usage.
What is hystrix?
Hystrix is a library developed by Netflix and is part of Spring via the Spring Cloud Netflix project. Hystrix is a fault tolerance library and is used as strategy against failures (at different levels) in a service-layer.
Why do we use Hystrix?
Hystrix can be used in situations where your application depends on remote services. In case one or more remote services are down you can handle the situation by using a circuit breaker in your application.
In simpler terms: How to allow one service to continue functioning – when it calls external services which are failing?
Hystrix is watching methods for failing calls to related services. If there is such a failing method, it will open the circuit, which means, it forwards the call to a fallback method. In case the services is restored it will close the circuit and the applications acts as expected again.
See this great article for more background.
What Is Hystrix?
Hystrix is a latency and fault tolerance library designed to isolate points of access to remote systems, services and 3rd party libraries, stop cascading failure and enable resilience in complex distributed systems where failure is inevitable.
In a distributed environment, inevitably some of the many service dependencies will fail. Hystrix is a library that helps you control the interactions between these distributed services by adding latency tolerance and fault tolerance logic. Hystrix does this by isolating points of access between the services,
stopping cascading failures across them, and providing fallback options, all of which improve your system’s overall resiliency.
What does it do?
1) Latency and Fault Tolerance
Stop cascading failures. Fallbacks and graceful degradation. Fail fast and rapid recovery. Thread and semaphore isolation with circuit breakers.
2) Realtime Operations
Realtime monitoring and configuration changes. Watch service and property changes take effect immediately as they spread across a fleet.Be alerted, make decisions, affect change and see results in seconds.
3) Concurrency
Parallel execution. Concurrency aware request caching. Automated batching through request collapsing.
Some of the major implementations of hystrix are used in
Circuit Breaker
This guide walks you through the process of applying circuit breakers to potentially-failing method calls using the Netflix Hystrix fault tolerance library.
Hystrix Dashboard
The Hystrix Dashboard allows you to monitor Hystrix metrics in real time.
For further information on hystrix visit https://github.com/Netflix/Hystrix/wiki/How-To-Use
For further info regarding hystrix dashboard visit https://github.com/Netflix/Hystrix/wiki/Dashboard
I am looking to implement a web application in which the end user is likely to cause invocation of business logic methods which are both cpu heavy and require a fair amount of memory to run.
My initial thought is to provide these methods as part of a standalone stateless business service, which can run on a separate machine to the web application. This can then be horizontally scaled as much as I need.
As these service methods are synchronous I am opting to us RMI as opposed to JMS.
My first question is if the above approach seems viable or seems to be good, or if my though process has got lost somewhere (this will be the first time I don't work on a standalone application).
Should that be the case I have been looking at spring RMI which seems to do an excellent job of exposing remote services non-intrusively. However I am unsure as how I could use this API to load balance between multiple servers. Are there any ways of doing this using spring or do I need a seperate API?
JBoss has the ability provide RMI proxies that are automatically load-balanced: http://docs.jboss.org/jbossas/jboss4guide/r4/html/cluster.chapt.html