in wso2am we can use message mediations in incoming requests and responses to process messages for different purposes. After I read micro integrator documentation, I believe that I can do whatever micro integrator is doing with its mediation sequences by the help of API manager mediations and it's confusing me because I don't know what is relationship between API manager and micro integrator. Are they two independent products? or API manager 4 has micro integrator inside?
I would really appreciate helping me with any of my questions.
APIM and MI both have mediation capabilities.
APIM has limited mediation capabilities compared to that of MI.
We use APIM (Gateway) to deploy light-weight mediations which are used in request/response transformations, processing etc. More complex mediations including service chaining, service orchestration, message stores/message processors, scheduled tasks, etc are kept with MI.
MI functions as an intermediate layer between the APIM gateway and backend server performing various complex mediation logics which cannot be performed by the APIM's mediation capability.
We expose rest apis from MI which are used as the backend endpoint in the APIM gateway through which we chain the request to the actual backend through the MI layer.
Consider an example of generating a response for an API request aggregating response from multiple backends. This can be achieved using the MI's complex mediation capabilities.
[1] https://medium.com/think-integration/wso2-micro-integrator-weds-wso2-api-manager-26d4349d750f
[2] https://ei.docs.wso2.com/en/7.2.0/micro-integrator/references/mediators/about-mediators/
[3] https://wso2.com/blogs/cloud/the-power-of-mediators-api-call-transformation-and-orchestration/
Related
I need to monitor HTTP traffic within my Kubernetes cluster. Specifically, I need response times, status codes, etc.
Currently, I am using a service mesh (Open Service Mesh) for this purpose. But, is there a lightweight solution that only allows monitoring (without security layer etc.) ?
Thanks for all ideas!
I can recommend you ELK stack (Elasticsearch, Fluent-bit and Kibana), one of the popular monitoring system suites on top of Kubernetes.
Fluent-bit has built-in parsers for logs of popular Web servers (apache, nginx).
Fluent Bit is a super fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data for lightning fast search, fine‑tuned relevancy, and powerful analytics that scale with ease.
Kibana
Kibana is a free and open user interface that lets you visualize your Elasticsearch data and navigate the Elastic Stack. Do anything from tracking query load to understanding the way requests flow through your apps.
There's an IIB HTTP SOAP service exposed to multiple channels - the service has 4 operations and one of them is being consumed very frequently by a particular channel (less than 1 transaction per second).
Is there any way within IBM Integration Bus (broker or service level) to limit number of HTTP requests per channel (IP address) to 1 or n transactions per second?
You could implement it manually using the standard facilities of IIB, but rate-limiting is an API management feature and best implemented using out-of-the-box features of IBM API Connect. It works well with IIB, btw.
As already suggested above, this kind of logic should be done outside of IIB if you need it globaly.
On IIB level, you can configure many things, like the maximum amount of connection, but there's no logic to have this kind of pool for each users.
The best solution, in my opinion, is to use a network component specialized in this kind of logic. On my side, I've decided to implement this rule on the load balancer I have in front of my IIB server. A proxy could probably also do it.
For your specific case, if it is the only case where you need this logic, you can also consider creating different entry point for each application. If this is SOAP, and that the users currently calls /kimbertService/, you can consider having multiple SOAP Input node, with the following routes instead : /kimbertService/App1, /kimbertService/App2, /kimbertService/App3, and then you'll be sure that App1 will never block App2 ...
IIB has a feature of throttling by limiting the number of messages processed through a given message flow per second.
For example, to set the maximumRateMsgsPerSec property for a message flow included in an application, you can use the following sample code:
mqsiapplybaroverride –b BARfile -k applicationName -m sampleFlow#maximumRateMsgsPerSec=100
You can also do it through workload management policies by using the IIB web user interface.
Below is the link:
https://www.ibm.com/support/knowledgecenter/en/SSMKHH_9.0.0/com.ibm.etools.mft.doc/bj58270_.htm
A WORK-A-ROUND SOLUTION
The ideal solution, as others have mentioned, would be to have a API management gateway sitting in front of IIB to manage your API.
Now, a work-around solution could be following:
1) Have your main service flow duplicated, making them two different message flows. These two are your back-end flows performing the same thing but on one of them you can enable throttling.
2) Build a new router IIB flow which takes HTTP requests from consumers. This flow identifies the requester and routes it to the back-end flows accordingly.
Hope this helps.
A little background.
Very big monolithic Django application. All components use the same database. We need to separate services so we can independently upgrade some parts of the system without affecting the rest.
We use RabbitMQ as a broker to Celery.
Right now we have two options:
HTTP Services using a REST interface.
JSONRPC over AMQP to a event loop service
My team is leaning towards HTTP because that's what they are familiar with but I think the advantages of using RPC over AMQP far outweigh it.
AMQP provides us with the capabilities to easily add in load balancing, and high availability, with guaranteed message deliveries.
Whereas with HTTP we have to create client HTTP wrappers to work with the REST interfaces, we have to put in a load balancer and set up that infrastructure in order to have HA etc.
With AMQP I can just spawn another instance of the service, it will connect to the same queue as the other instances and bam, HA and load balancing.
Am I missing something with my thoughts on AMQP?
At first,
REST, RPC - architecture patterns, AMQP - wire-level and HTTP - application protocol which run on top of TCP/IP
AMQP is a specific protocol when HTTP - general-purpose protocol, thus, HTTP has damn high overhead comparing to AMQP
AMQP nature is asynchronous where HTTP nature is synchronous
both REST and RPC use data serialization, which format is up to you and it depends of infrastructure. If you are using python everywhere I think you can use python native serialization - pickle which should be faster than JSON or any other formats.
both HTTP+REST and AMQP+RPC can run in heterogeneous and/or distributed environment
So if you are choosing what to use: HTTP+REST or AMQP+RPC, the answer is really subject of infrastructure complexity and resource usage. Without any specific requirements both solution will work fine, but i would rather make some abstraction to be able switch between them transparently.
You told that your team familiar with HTTP but not with AMQP. If development time is an important time you got an answer.
If you want to build HA infrastructure with minimal complexity I guess AMQP protocol is what you want.
I had an experience with both of them and advantages of RESTful services are:
they well-mapped on web interface
people are familiar with them
easy to debug (due to general purpose of HTTP)
easy provide API to third-party services.
Advantages of AMQP-based solution:
damn fast
flexible
cost-effective (in resources usage meaning)
Note, that you can provide RESTful API to third-party services on top of your AMQP-based API while REST is not a protocol but rather paradigm, but you should think about it building your AQMP RPC api. I have done it in this way to provide API to external third-party services and provide access to API on those part of infrastructure which run on old codebase or where it is not possible to add AMQP support.
If I am right your question is about how to better organize communication between different parts of your software, not how to provide an API to end-users.
If you have a high-load project RabbitMQ is damn good piece of software and you can easily add any number of workers which run on different machines. Also it has mirroring and clustering out of the box. And one more thing, RabbitMQ is build on top of Erlang OTP, which is high-reliable,stable platform ... (bla-bla-bla), it is good not only for marketing but for engineers too. I had an issue with RabbitMQ only once when nginx logs took all disc space on the same partition where RabbitMQ run.
UPD (May 2018):
Saurabh Bhoomkar posted a link to the MQ vs. HTTP article written by Arnold Shoon on June 7th, 2012, here's a copy of it:
I was going through my old files and came across my notes on MQ and thought I’d share some reasons to use MQ vs. HTTP:
If your consumer processes at a fixed rate (i.e. can’t handle floods to the HTTP server [bursts]) then using MQ provides the flexibility for the service to buffer the other requests vs. bogging it down.
Time independent processing and messaging exchange patterns — if the thread is performing a fire-and-forget, then MQ is better suited for that pattern vs. HTTP.
Long-lived processes are better suited for MQ as you can send a request and have a seperate thread listening for responses (note WS-Addressing allows HTTP to process in this manner but requires both endpoints to support that capability).
Loose coupling where one process can continue to do work even if the other process is not available vs. HTTP having to retry.
Request prioritization where more important messages can jump to the front of the queue.
XA transactions – MQ is fully XA compliant – HTTP is not.
Fault tolerance – MQ messages survive server or network failures – HTTP does not.
MQ provides for ‘assured’ delivery of messages once and only once, http does not.
MQ provides the ability to do message segmentation and message grouping for large messages – HTTP does not have that ability as it treats each transaction seperately.
MQ provides a pub/sub interface where-as HTTP is point-to-point.
UPD (Dec 2018):
As noticed by #Kevin in comments below, it's questionable that RabbitMQ scales better then RESTful servies. My original answer was based on simply adding more workers, which is just a part of scaling and as long as single AMQP broker capacity not exceeded, it is true, though after that it requires more advanced techniques like Highly Available (Mirrored) Queues which makes both HTTP and AMQP-based services have some non-trivial complexity to scale at infrastructure level.
After careful thinking I also removed that maintaining AMQP broker (RabbitMQ) is simpler than any HTTP server: original answer was written in Jun 2013 and a lot of changed since that time, but the main change was that I get more insight in both of approaches, so the best I can say now that "your mileage may vary".
Also note, that comparing both HTTP and AMQP is apple to oranges to some extent, so please, do not interpret this answer as the ultimate guidance to base your decision on but rather take it as one of sources or as a reference for your further researches to find out what exact solution will match your particular case.
The irony of the solution OP had to accept is, AMQP or other MQ solutions are often used to insulate callers from the inherent unreliability of HTTP-only services -- to provide some level of timeout & retry logic and message persistence so the caller doesn't have to implement its own HTTP insulation code. A very thin HTTP gateway or adapter layer over a reliable AMQP core, with option to go straight to AMQP using a more reliable client protocol like JSONRPC would often be the best solution for this scenario.
Your thoughts on AMQP are spot on!
Furthermore, since you are transitioning from a monolithic to a more distributed architecture, then adopting AMQP for communication between the services is more ideal for your use case. Here is why…
Communication via a REST interface and by extension HTTP is synchronous in nature — this synchronous nature of HTTP makes it a not-so-great option as the pattern of communication in a distributed architecture like the one you talk about. Why?
Imagine you have two services, service A and service B in that your Django application that communicate via REST API calls. This API calls usually play out this way: service A makes an http request to service B, waits idly for the response, and only proceeds to the next task after getting a response from service B. In essence, service A is blocked until it receives a response from service B.
This is problematic because one of the goals with microservices is to build small autonomous services that would always be available even if one or more services are down– No single point of failure. The fact that service A connects directly to service B and in fact, waits for some response, introduces a level of coupling that detracts from the intended autonomy of each service.
AMQP on the other hand is asynchronous in nature — this asynchronous nature of AMQP makes it great for use in your scenario and other like it.
If you go down the AMQP route, instead of service A making requests to service B directly, you can introduce an AMQP based MQ between these two services. Service A will add requests to the Message Queue. Service B then picks up the request and processes it at its own pace.
This approach decouples the two services and, by extension, makes them autonomous. This is true because:
If service B fails unexpectedly, service A will keep accepting requests and adding them to the queue as though nothing happened. The requests would always be in the queue for service B to process them when it’s back online.
If service A experiences a spike in traffic, service B won’t even notice because it only picks up requests from the Message Queues at its own pace
This approach also has the added benefit of being easy to scale— you can add more queues or create copies of service B to process more requests.
Lastly, service A does not have to wait for a response from service B, the end users don’t also have to wait for long— this leads to improved performance and, by extension, a better user experience.
Just in case you are considering moving from HTTP to AMQP in your distributed architecture and you are just not sure how to go about it, you can checkout this 7 parts beginner guide on message queues and microservices. It shows you how to use a message queue in a distributed architecture by walking you through a demo project.
What's the difference between an RPC System, like Twitter's Finagle, and an Enterprise Service Bus, like Mule? What kind of problems are each of them good at solving?
I will try to answer this as a soft explanation, rather than a technical breakdown of features:
One may say that Finagle is a asynchronous messaging library that allows services to connect to one another freely (not tightly tied to architectural system integration standards) while supporting multiple protocols.
From the Finagle website:
Finagle is a network stack for the JVM that you can use to build asynchronous Remote Procedure Call (RPC) clients and servers in Java, Scala, or any JVM-hosted language. Finagle provides a rich set of protocol-independent tools.
An enterprise service bus (ESB), on the other hand, is a asynchronous messaging architecture which typically adheres to industry standards and protocols. An ESB promotes a system where message flow is controlled and routed between systems, and where servers can register their service and clients can register what messages they are interested in. The services offered by servers can be registered and versioned.
You will typically find Finagle being used somewhere between a website and backend services. But, you will typically find an ESB inside a large corporate, where it's responsible to integrating systems like finance, support, sales, etc.
Both solutions offer asynchronous messaging and buffering to various extends, but are not designed to solve the same problem. For ESB, you would probably think 'strict, enterprise', but for Finagle you would probably think 'flexible, web'.
Hope this helps
Update:
Not quite related, but if you are exploring this space, I would look at Kafka these days.
RPC and ESB are two architectural patterns. While RPC is usually a request-reply and synchronous in nature, an ESB works on the concept of messaging (simplified explanation) and of asynchronous in nature. ESB is the foundation for any SOA implementation. ESB enables loose coupling thus promoting true agility. A simplified example from implementation perspective is as follows:
A web service is a typical RPC. The consumer is tightly bound to the producer and any change in the contract on the producer side, will require changes on the consumer side.
In ESB, the service consumer doesn't invoke the service producer directly. It just puts the message in the bus and based on the rules (mediator), appropriate service producer will handle it. If the service consumer and service producer talk in different formats, ESB provides the facility to do the transformation (like formatting the zipcode as xxxxx-xxxx, splitting the name into first name and last name, etc.).
This is just simplified explanation. For more information, please check the following links:
Why do developers need an Enterprise Service Bus?
Enterprise Service Bus
Both solve completely different problems:
An ESB is an intermediation middleware that provides message transformation and routing, protocol adaptation and other value-add operations (like orchestration, guaranteed delivery, idempotent filtering...). It sits in-between your service consumers and providers and transparently (ie without any change in consumer or provider) provides its different features.
An RPC system provides client and server technologies for performing RPC operations.
I've read of an ESB being used as a SOA approach. What are some other approaches?
This is a very broad question, you may want to focus is.
If you are asking regarding approaches that are instead of ESB, then you may consider using direct access to services, instead of using a service bus.
This approach is often used with a directory or lookup service like UDDI to look up service end point location.
When using an ESB, you send the message to the ESB, who 's responsible to route it to the service provider.
When using direct access the client should know in advance the address of the service provider, and he sends the message directly to him.
When using a lookup service, you first query the address of the service provider (like using DNS to lookup IP addresses), and using this address you send the message to the service provider.
Beyond addressing and routing, the ESB may provide other functions that you loose (or have to implement in other way) if you use the direct access approach.
multi cast routing - sending the request to more then one service provider
context based routing - deciding to which service provider we should send the request, based on the content of the request
central logging
central policy enforcement
load balancing \ fault tolerance
format or protocol translation
buffering and asynchronous service invocation
First.... ask yourself which SOA philosophy are you adhering to. If you are in the IBM camp, then there are 4 different products that provide ESB functionality. Each product is optimized for a different scenarios but basically each one does similar functions.
Think.... SOA == a car. IBM is one manufacturer. Different products == different type of cars for different type of drivers.