Micro services using Service fabric where to place controllers - microservices

I have a micro-service project with multiple services in .NET Core. When it comes to placing the controllers, there are 2 approaches:
Place the controllers in respective Micro Services, with Startup.cs in each micro-service.
Place all controllers in a separate project and have them call the individual services.
I think the 1st approach will involve less coding effort but the 2nd one separates controllers from actual services using interfaces etc.
Is there a difference in terms of how they are created and managed in Fabric using both approaches.

This is very broad topic and can raise points for discussion because it all depends on preferences, experiences and tech stacks. I will add my two cents, but do not consider it as a rule, just my view for both approaches.
First approach (APIs for each service isolated from each other):
the services will expose their public APIs themselves and you will need to put a service discovery approach in place to enable clients to call each microservice, a simple one is using the reverse proxy to forward the calls using the service name.
Each service and it's APIs scales independently
This approach is better to deploy individual updates without taking down other microservices.
This approach tends to have more code repetition to handle authorization, authentication, and other common aspects, from there you will end up doing shared libraries using on all services.
This approach increase the points of failures, it is good because failures will affect less services, if one API is failing, other services won't be impacted (if the failure does not affect the machine like memory leak or high CPU usage).
The second approach (Single API to forward the calls to right services):
You have a single endpoint and the service discovery will happen in the API, all work will be handled by each services.
The API must scale for everyone even though one service consumes much more resources than others. just the service will scale independently.
This approach, to add or modify api endpoints, you will likely update the API and the service, taking down the API will affect other services.
This approach reduces the code duplication and you can centralize many common aspects like Authorization, request throttling and so on.
This approach has less points of failures, if one microservices goes down, and a good amount of calls depend on this service, the API will handle more connection and pending requests, this will affect other services and performance. If it goes down, every services will be unavailable. Compared to the first approach, the first approach will offloaded the resilience to the proxy or to the client.
In summary,
both approaches will have a similar effort, the difference is that the effort will be split into different areas, you should evaluate both and consider which one to maintain. Don't consider just code in the comparison, because code has very little impact on the overall solution when compared with other aspects like release, monitoring, logging, security, performance.

In our current project we have a public facing API. We have several individual microservice projects for each domain. Being individual allows us to scale according to the resources each microservice use. For example we have an imaging service that consumes a lot of resources, so scaling this is easier. You also have the chance to deploy them individually and if any service fails it doesn't break the whole application.
In front of all the microservices we have an API Gateway that handles all the authentication, throttles, versioning, health checks, metrics, logging etc. We have interfaces for each microservice, and keep the Request and Response models seperately for each context. There is no business logic on this layer, and you also have the chance to aggregate responses where several services need to be called.
If you would like to ask anything about this structure please feel free to ask.

Related

Microservice Aggregator Service BFF

Let say I have 22 microservices. I developed with docker on local.
Client wants to get product model data which contains 3 different service data and aggregate them.
Should I use aggregator gateway api or SPA get separately from each service. Does Aggregator service couple services ?
These Microservices patterns always come with Trade-offs. Here you need to consider more than just a coupling issue when you are going with Aggregator pattern (Backend for Frontend).
The following are some of the points you need to think about before going with this pattern.
The Latency problem. If you want this implementation to make it better without any latency problem, then your services and aggregator should be in the same location or the same data center. Avoid third party calls from aggregators.
This can introduce a single point of failure. Make sure that you've designed in such a way that the service is highly available.
Implement a resilient design and timeout since this aggregator is calling other services and getting data. If one or more service calls take too long, it should timeout and return a partial set of data. Consider how your application will handle this scenario
Monitoring of your aggregator and it's child service calls. Implement distributed tracing using correlation IDs to track each call.
Ensure the aggregator has the adequate performance to handle the load and can be scaled to meet your anticipated growth.
These are the best practices that I can suggest, You are the best person who can decide based on your system requirements and these points.
There are some compelling advantages to using a BfF service as an orchestration layer that aggregates calls to various backend data services.
It will reduce the complexity in the data access areas of your SPA.
It can also reduce load times.
Over time, your frontend devs will be less likely to get blocked on the backend devs assuming that the BfF is maintained by the frontend devs.
Take a look at this article on Consistency, Coupling, and Complexity at the Edge that goes into more detail on this and proposes some best practices such as GraphQL vs REST.

Why API Gateway is recommended for Microservices?

For microservices, the common design pattern used is API-Gateway. I am a bit confused about its implementation and implications. My questions/concerns are as follows:
Why other patterns for microservices are not generally discussed? If they are, then did I miss them out?
If we deploy a gateway server, isn't it a bottleneck?
Isn't the gateway server vulnerable to crashes/failures due to excessive requests at a single point? I believe that the load would be enormous at this point (and keeping in mind that Netflix is doing something like this). Correct me if I am wrong in understanding.
Stream/download/upload data (like files, videos, images) will also be passing through the gateway server with other middleware services?
Why can't we use the proxy pattern instead of Gateway?
From my understanding, in an ideal environment, a gateway server would be entertaining the requests from clients and responding back after the Microservices has performed the due task.
Additionally, I was looking at Spring Cloud Gateway. It seems to be something that I am looking for in a gateway server but the routing functionality of it confuses me if it's just a routing (redirect) service and the microservice would be directly responsible for the response to the client.
The gateway pattern is used to provide a single interface to a bunch of different microservices. If you have multiple microservices providing data for your API, you don't want to expose all of these to your clients. Much better for them to have just a single point of entry, without having to think about which service to poll for which data. It's also nice to be able to centralise common processing such as authentication. Like any design pattern, it can be applied very nicely to some solutions and doesn't work well for others.
If throughput becomes an issue, the gateway is very scalable. You can just add more gateways and load balance them
There are some subtle differences between proxy pattern and API gateway pattern. I recommend this article for a pretty straightforward explanation
https://blog.akana.com/api-proxy-or-gateway/
In the area of microservices the API-Gateway is a proven Pattern. It has several advantages e.g:
It encapsulate several edge functionalities (like authentication, authorization, routing, monitoring, ...)
It hides all your microservices and controls the access to them (I don't think, you want that your clients should be able to access your microservices directly).
It may encapsulate the communication protocols requested by your microservices (sometimes the service may have a mixture of protocols internally which even are only allowed within a firewall).
An API-Gateway may also provide "API composition" (orchestrating the calls to several services an merge their results to one). It s not recommended, to implement a such composition in a microservice.
and so on
Implementing all these feature in a proxy is not trivial. There is a couple of API-Gateways which provide all these functionalities and more like the Netflix-Zuul, Spring-Gateway or the Akana Gateway.
Furthermore, in order to avoid your API-Gateway from being a bottleneck you may :
Scale your API-Gateway and load balance it (as mentioned above by Arran_Duff)
Your API-Gateway should not provide a single one-size-fits-all API for all your clients. Doing so you will, in the case of huge request amount (or large files to down/up load) for sure encounter the problems you mentioned in questions 3 and 4. Therefore in order to mitigate a such situation your Gateway e.g may provide each client with a client specific API (a API-Gateway instance serves only a certain client type or business area..). This is exactly what Netflix has done to resolve this problem (see https://medium.com/netflix-techblog/embracing-the-differences-inside-the-netflix-api-redesign-15fd8b3dc49d)
1.Why other patterns for microservices are not generally discussed? If they are, then did I miss them out?
There are many microservice pattern under different categories such as database , service etc .This is a very good article https://microservices.io/patterns/index.html
2.If we deploy a gateway server, isn't it a bottleneck?
Yes to some extent .Q3's answers image will answer this.
3.Isn't the gateway server vulnerable to crashes/failures due to excessive requests at a single point? I believe that the load would be enormous at this point (and keeping in mind that Netflix is doing something like this). Correct me if I am wrong in understanding.
4.Stream/download/upload data (like files, videos, images) will also be passing through the gateway server with other middleware services?
Why can't we use the proxy pattern instead of Gateway?
The use case for an API Proxy versus an API Gateway depends on what kinds of capabilities you require and where you are in the API Lifecycle. If you already have an existing API that doesn’t require the advanced capabilities that an API Gateway can offer than an API Proxy would be a recommended route.
You can save valuable engineering bandwidth because proxies are much easier to maintain and you won’t suffer any negligible performance loss. If you need specific capabilities that a proxy doesn’t offer you could also develop an in-house layer to accommodate your use case. If you are earlier in the API lifecycle or need the extra features that an API Gateway can provide, then investing in one would pay dividends.

Does Service Discovery microservice break idea of loose coupling?

As a mechanism to connect microservices together and make them work it is usually suggested to use APIs and Service Discovery. But they usually work as their own microservices, but these ones should apparently be "hard-coded" into others, as every microservice is supposed to register with them and query for other microservices' locations. Doesn't this break the idea of loose coupling, since a loss of a discovery service implies others being unable to communicate?
Pretty much yes. If one microservice "knows" about another microservice - it means that they are highly coupled. It doesn't matter where specifically this knowledge about other service is coming from: hardcoded, config file or maybe some service discovery, it still leads to high coupling.
What's important to understand is that many microservice evangelists are just preaching about how to build monolith apps on top of Web APIs. Some of them probably think that the more buzz words they use - the better ... not quite sure why this happens. It is probably easier to fake a language and become an "expert" by using buzzword salad instead of really building fault tolerant and horizontally scalable app.
But there is another way to look at service discovery: when it is used by service clients like SPA application or an API Gateway it may be very useful. Clients and gateways should know about service APIs, otherwise, the whole thing doesn't make sense. But they can use a registry to make it more flexible/dynamic.
So, to summarize:
if services are using discovery to get more information about each other - this is probably a bad thing and design flaw (pretty sure there are corner cases where this may be a valid scenario, please post a comment if you know some)
if discovery is used by other parts of the app, like SPA or API Gateway, this may be useful, but not necessarily it always is.
PS: to avoid high coupling, consider reading series of articles by Jeppe Cramon that illustrate the problem and possible solutions very nicely.
In a distributed system, you will always have some amount of coupling, what you want to do is to reduce all aspects of coupling to a minimum.
I'd argue that is does matter how you design your service location. if your code knows of the other service i.e. OrderService.Send(SubmitOrderMessage); (where 'OrderService' is an instance of the other service's proxy)
as opposed to transportAgent.Send(SubmitOrderMessage); (where 'transportAgent' is an instance of the transport's proxy i.e. the queuing service/agent and the actual address of the queue can be in your config), this reduces the coupling and your business logic code (Service) and delegates the routing to your infrastructure.
Make Sense?
Each microservice is expected to be functionally independent. For interacting with other microservices, it should rely on rest api calls only. Service Discovery plays a role to keep the services fairly loose coupled with each other. Also due to dynamic nature of the service urls, the hard dependencies are removed. Hope this helps
Reduced coupling or fairly loose coupling still has one thing in common; coupling. In my opinion, coupling to any degree will always create rigid communication patterns that are difficult to maintain and difficult to troubleshoot as a platform grows into a large distributed platform. Isn't the idea behind microservices to allow consumers to engage in "Permissionless innovation?" I would suggest that this is only possible by decomposing to microservices that have high cohesion and low coupling and then let the consumer decide how to route, orchestrate or aggregate.

Splitting monolith into microservices

I have an existing web service that supports ordering and it has multiple operations (approximately 20). This is a single webservice that support the ordering function. It interacts with multiple other services to provide ordering capability.
Since there is a lot of business functionality within this app and it is supported by a 10 member team , I believe it is a monolith (though I assume there is no hard and fast rule to define what a monolith is).
We are planning to get the application deployed in cloud foundry environment and we are planning to split the app into 2-3 microservices , primarily to enable them scale independently.
The first few apis which enable searching for a product typically have more number of hits whereas the api that support actual order submission receives less that 5% of the hits. So the product search api should have significantly larger number of instances as compared to order submission api.
Though I am not sure if we could split is based on sub-domains (which I have read should be the basis) , we are thinking of splitting them based on the call sequence as explained earlier.
I have also read that microservices should be choreographed and not orchestrated. However in order to ensure our existing consumers are not impacted , I believe we should expose a api layer which would orchestrate the calls to these microservices. Is providing an api gateway , the normal approach that is followed to ensure consumers do not end up calling multiple microservices and also provides a layer of abstraction?
This seems to be orchestration more than choreography - though I am not hung up on the theoretical aspects , I would like to understand the different solutions that are pursued for this problem statement in an enterprise world.
The Benefits of Microservices
Deploy & Scale Independently
Easier to 'Reason About'
Separation of Concerns
Single Responsibility
(Micro)Service-Oriented Architecture
I would suggest splitting your services based on domain. This is a logical and efficient approach which makes it an easy starting point. Your monolithic package structure may already be organized in this manner, which simplifies the refactoring even more.
API Gateway
The typical Spring Cloud approach for this would be to use a Zuul Proxy on the edge of your network which receives the requests from your clients (web, mobile, etc.) and routes them to the microservices located behind your firewall. The client only interfaces with a single domain, and it handles CORS out of the box.
Resources:
API Gateway Pattern
Routing and Filtering

SOA and APIs - are the APIs endpoint services or they require a distinct service?

I'm designing a RESTful Service Oriented Architecture web application to make it scale as good as possible and put different kind of services on different machines (separating resource intensive operations from other services).
I also want users to be able to access their data to make their own applications.
I'm not sure if I have to design these services to be opened to the world, so it's just a matter of make them listen on a web domain (like AWS) or create another service to handle API requests.
It makes sense to me to have secure opened webservices, but it does add a lot of complexity to the architecture itself because each service becomes a client that has to be recognized (trust) by other services in the same suite, just as well as I have to recognize 3rd party applications trying to access their own data.
Is this a right SOA approach? What I want to be sure is that I'm not mixing wrong concepts designing a wrong service oriented architecture.
All services have crud interfaces so they could be queried using REST principles.
Depending on the nature of your system, it may be viable to have unsecured webservices, so they can all talk to each other without the security overheads. To make the services available to 3rd parties, you could then use a Service Perimeter Guard as the only mechanism for accessing the services externally and apply security at this layer. This has the benefit of providing consistent security across all of your services, however if the perimeter is compromised then access to all of the services is obtained.
This approach may not be viable for all services. For instance information that is considered "personal-in-confidence" (e.g., employee data such as home addresses, emergency contact details, health data, etc), will need to be secured so that unauthorised staff cannot access it.
Regarding your comment of putting different services on different machines, this will result in under-utilised resources on some machines and possibly over-utilised resources on others. To avoid this, deploy all services to all machines and use a load-balancer. This will provide more optimal resource usage and simplify deployments (e.g., using Chef or Puppet) as all of the nodes are the same. As the resource usage increases, you can then simply add more nodes. Similarly if the resource usage is low, you can remove nodes.
Regarding your last sentence, there is a whole lot more to REST than CRUD (such as HATEOAS).

Resources