I am building microservices architecture for the first time and despite I have read a lot of articles I am still confused how to correctly implement circuit breaker.
Let's suppose that I have several microservices that call each other. So I implemented circuit breaker into each of them as an request interceptor and it works. But I dont like it.
Firstly each service now needs to hit the fail threshold separately before the breaker open. Secondly I write the same functionality for each service over and over again.
So my first thought was to create circuit breaker as stand alone service but I can not find any pattern describing such a functionality. How it would works? Every service before making request calls circuit breaker service firs if target circuit is closed. If so it sends request and when request is finished then reports back to circuit breaker service whether the request was successful or failed?
Or how should be circuit breaker correctly put into microservices architecture?
When you are talking about real micro services architecture circuit breaking is a cross-cutting-concern
You should not implement it by yourself. First of all I should say please be careful of creating spaghetti between your micro services, It's too dangerous and anti-pattern.
Although its an anti-pattern I highly recommend you to use cloud native platforms to deploy your micro-services like Kubernetes or mabye Docker.
There are lots of useful tools like Envoy-implemented side-cars, service mesh implementations using Istio (not recommended), Consul and other Hashicorp products.
You can improve your service discovery, observability, monitoring, circuit-breaking, logging, side-micro-service-communication and other useful concepts using cloud native tools.
Hint: I highly recommend you to use grpc instead of http requests between your services (To reduce latency based on http3 and tcp connections)
Secondly I write the same functionality for each service over and
over again.
One of ways to address this issue in the world of microservices is (as you correctly noticed) to have this functionality moved away of your service. Circuit breaking is just one element, there is many many more other aspects, related to inter-service communication, that you'd have to take care of, such as: handling retries, failovers, authentication and authorization, tracing, monitoring etc.
If you were to handle it in all services separately, you'd end up writing the same code (or configuring various frameworks/plugins) over and over again.
The solution that emerged from that need is a service mesh. You can think of it as a middle-man that intercept all the communication between your services and taking care of all above mentioned aspects.
There are various solutions. You can check https://github.com/cncf/landscape to find out what is now "hot" and considered a standard.
I'd however recommend you getting familiar with the https://istio.io/latest/about/service-mesh/ as it's really mature and powerful.
Related
gRPC is a modern open source high performance RPC framework that can
run in any environment. It can efficiently connect services in and
across data centers with pluggable support for load balancing,
tracing, health checking and authentication. It is also applicable in
last mile of distributed computing to connect devices, mobile
applications and browsers to backend services.
I'm finding GRPC is becoming increasingly more pertinent in backend infrastructure, and would've liked to have it in my favorite language/tsdb kdb+/q.
I was surprised to find that kdb+ does not have a grpc implementation. Obviously, the (https://code.kx.com/q/interfaces/protobuf/)
package doesn't support the parsing of rpc's, is there anything quantitatively preventing there being a KDB+ implementation of the rpc requests/services etc. found in grpc?
Why would one not want to implement rpc's (grpc) in kdb+ and would it be a good idea to wrap a c++/c implemetation therin inorder to achieve this functionality.
Thanks for your advice.
Interesting post:
https://zimarev.com/blog/event-sourcing/myth-busting/2020-07-09-overselling-event-sourcing/
outlines event sourcing, which I think might be a better fit for kdb?
What is the main issue with services using RPC calls to exchange information? Well, it’s the high degree of coupling introduced by RPC by its nature. The whole group of services or even the whole system can go down if only one of the services stops working. This approach diminishes the whole idea of independent components.
In my practice I hardly encounter any need to use RPC for inter-service communication. Partially because I often use Event Sourcing, more about it later. But we always use asynchronous communication and exchange information between services using events, even without Event Sourcing.
For example, an order microservice in an e-commerce system needs customer data from the customer microservice. These dependencies between microservices are not ideal. Other microservices can go down and synchronous RESTful requests over https do not scale well due to their blocking nature. If there was a way to completely eliminate dependencies between microservices completely the result would be a more robust architecture with less bottlenecks.
You don’t need Event Sourcing to fix this issue. Event-driven systems are perfectly capable of doing that. Event Sourcing can eliminate some of the associated issues like two-phase commits, but again, not a requirement to remove the temporal coupling from your system.
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.
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.
We are designing a reporting system using microservice architecture. All the services are supposed to be subscribers to the event bus and they communicate by raising events. We also decided to expose each of our services using REST api. Now the question is , is it a good idea to create our services as web api [RESTful] applications which are also subscribers to the event bus? so basically there are 2 ponits of entry to each service - api and events. I have a feeling that we should separate out these 2 as these are 2 different concerns. Any ideas?
Since Microservices architecture are Un-opinionated software design. So you may get different answers on this questions.
Yes, REST and Event based are two different things but sometime both combined gives design to achieve better flexibility.
Answering to your concerns, I don't see any harm if REST APIs also subscribe to a queue as long as you can maintain both of them i.e changes to message does not have any impact of APIs and you have proper fallback and Eventual consistency mechanism in place. you can check discussion . There are already few project which tried it such as nakadi and ponte.
So It all depends on your service's communication behaviour to choose between REST APIs and Event-Based design Or Both.
What you do is based on your requirement you can choose REST APIs where you see synchronous behaviour between services
and go with Event based design where you find services needs asynchronous behaviour, there is no harm combining both also.
Ideally for inter-process communication protocol it is better to go with messaging and for client-service REST APIs are best fitted.
Check the Communication style in microservices.io
REST based Architecture
Advantage
Request/Response is easy and best fitted when you need synchronous environments.
Simpler system since there in no intermediate broker
Promotes orchestration i.e Service can take action based on response of other service.
Drawback
Services needs to discover locations of service instances.
One to one Mapping between services.
Rest used HTTP which is general purpose protocol built on top of TCP/IP which adds enormous amount of overhead when using it to pass messages.
Event Driven Architecture
Advantage
Event-driven architectures are appealing to API developers because they function very well in asynchronous environments.
Loose coupling since it decouples services as on a event of once service multiple services can take action based on application requirement. it is easy to plug-in any new consumer to producer.
Improved availability since the message broker buffers messages until the consumer is able to process them.
Drawback
Additional complexity of message broker, which must be highly available
Debugging an event request is not that easy.
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.