I know Integration tests are supposed to test multiple components working together, but is it fine to test behavior of one component(which has side-effects) using an unrelated component.
So, I have one microservice (Service A) which fetches data, does some processing and put it in another data store. (Basically, its task is to load the data in the DB)
There is another microservice (Service B) written to perform transactional queries on the data store.
Now while writing integration tests for Service A, is it fine that I use the read operations of Service B to verify that the data has loaded correctly?
By the way Service A does not use Service B to load the data into the data store.
I think that it will increase the coupling between the two services but at the same time directly querying the databases has its own challenges (integrating test environment with the database).
Related
A simple question about scalability. I have been studying about scalability and I think I understand the basic concept behind it. You use an orchestrator like Kubernetes to manage the automatic scalability of a system. So in that way, as a particular microservice gets an increase demand of calls, the orchestrator will create new instances of it, to deal with the requirement of the demand. Now, in our case, we are building a microservice structure similar to the example one at Microsoft's "eShop On Containers":
Now, here each microservice has its own database to manage just like in our application. My question is: When upscaling this system, by creating new instances of a certain microservice, let's say "Ordering microservice" in the example above, wouldn't that create a new set of databases? In the case of our application, we are using SQLite, so each microservice has its own copy of the database. I would asume that in order to be able to upscale such a system would require that each microservice connects to an external SQL Server. But if that was the case, wouldn't that be a bottle neck? I mean, having multiple instances of a microservice to attend more demand of a particular service BUT with all those instances still accessing a single database server?
In the case of our application, we are using SQLite, so each microservice has its own copy of the database.
One of the most important aspects of services that scale-out is that they are stateless - services on Kubernetes should be designed according to the 12-factor principles. This means that service-instances cannot have its own copy of the database, unless it is a cache.
I would asume that in order to be able to upscale such a system would require that each microservice connects to an external SQL Server.
yes, if you want to be able to scale-out, you need to use a database that are outside the instances and shared between the instances.
But if that was the case, wouldn't that be a bottle neck?
This depend very much on how you design your system. Comparing microservices to monoliths; when using a monolith, the whole thing typically used one big database, but with microservices it is easier to use multiple different databases, so it should be much easier to scale-out the database this way.
I mean, having multiple instances of a microservice to attend more demand of a particular service BUT with all those instances still accessing a single database server?
There are many ways to scale a database system as well, e.g. caching read-operations (but be careful). But this is a large topic in itself and depends very much on what and how you do things.
Is there a testing framework or solution to test and assert collaboration on shared data in a webapplication?
The client-side mainly focus on changing the structure of a large collection of ordered objects. Basic operations like insert, delete and reordering the structure. To prevent stale data, operations from other users are synchronized with bi-directional communication.
This collection can be edited by two or more users concurrently. All edits are pessimistic in such a way that the server determines the right outcome to prevent conflicts. The server transforms two concurrent operations (from the same state) and broadcast the changes.
Unit testing the transformation on the server works just fine. But is there a solution to create some sort of automated test that covers the complete flow with two concurrent users? Like simulating that two clients sending a concurrent operation and assert that the result on both clients will be eventual consistent - after applying both changes?
Or is the only solution to write tests for the server and the client fully isolated from each other, without any 'real' collaboration testing?
I have two systems:
REST web application which return data in xml
Windows service which daily gets data from 1st web app and sync it wit its database.
Question: how to make integration testing for this applications (check whether data is sunchronised corectly)? Is it possible to automate such testing?
If I were you, I would send a request from 2 and validate my database data at 2. This forms a whole journey (E2E) there by interacting with as many other systems involved. You may also need to consider different scenarios/paths so that as much interaction is covered.
How should we best handle code that is part of a single Rails app, but is used in several different "modes"?
We have several different cases of an app that is driven from the same data sources (MySQL, MongoDB, SOLR) and shares core logic, assets, etc. across multiple different uses.
Background/details:
HTML vs REST API
A common scenario is that we have HTML and REST interfaces. These differences are handled through routing (e.g. /api/v1/user/new vs /user/new) -- with minor differences they provide the same functions. This seems reasonably clean to me.
Multi-tenant
Another common scenario is that the app is "multi-tenant", determined mainly by subdomain of the URL, e.g. partner1.example.com and partner2.example.com (or query-string parameter for API customers) -- each has a number of features or properties that differ. This is handled by a filter ApplicationController using data largely stored in a set of tenant-specific database tables with tenant-specific functionality encapsulated by methods. This also seems reasonably clean to me.
Offline Tasks
One scenario is that a great deal of the data is acquired through a very large number of tasks, running pretty much continuously: feed loaders, scrapers, crawlers, and other tasks of this sort ... the kinds of things you would find in a search engine, which is a large part of what we do. These tasks are launched on idle server instances and run periodically ... but are just rake tasks that are part of the app.
These tasks are characteristically different than our front-end code -- they update data, run calculations, do maintenance tasks and so on -- some tasks run for days (e.g. update 30M documents from an external web service). In the end, these tasks create and keep fresh the core data that our front end app uses.
This one doesn't seem as clean to me, in particular, in some cases, these tasks are running and doing data updates at the same time as our application is using them, so occasionally need to defer to the front-end app when we're under peak loads.
Major Variants of the App
This last case is clearly wrong -- we have made major customizations of our app -- 15% or 20% different, by making branches and then running as an entirely separate app, sharing some of the core data sometimes, but using some of its own data other times. We have mostly fixed this now, as it was, of course, untenable.
OK, there's a question in here somewhere, right?
So in particular for the offline tasks I feel like the app really needs to be launched in a "mode" or perhaps "sub-environment". But we still have normal development, test, qa, demo, pre_release, production environments that have their own isolated data and other configuration parameters. For each of these, we want to be able to run, develop, test and deploy the various "modes" of the application.
Can anyone suggest an appropriate architecture that is similar to the declarative notions of standard Rails environments?
If the number of modes is ever-increasing:
Perhaps the offline tasks could be separated from the main app, into their own application (or a parent abstract task with actual tasks inheriting from it and deployed individually).
If the number of modes is relatively small and won't be changing often:
You could put the per-mode configuration into a config file, logically separate from the rest of the code. Then during the deployments, you would be able to provide a combination of (environment, mode, set of hosts) and get a good level of control of your environments while using the same codebase.
I am currently working on a project with specific requirements. A brief overview of these are as follows:
Data is retrieved from external webservices
Data is stored in SQL 2005
Data is manipulated via a web GUI
The windows service that communicates with the web services has no coupling with our internal web UI, except via the database.
Communication with the web services needs to be both time-based, and triggered via user intervention on the web UI.
The current (pre-pre-production) model for web service communication triggering is via a database table that stores trigger requests generated from the manual intervention. I do not really want to have multiple trigger mechanisms, but would like to be able to populate the database table with triggers based upon the time of the call. As I see it there are two ways to accomplish this.
1) Adapt the trigger table to store two extra parameters. One being "Is this time-based or manually added?" and a nullable field to store the timing details (exact format to be determined). If it is a manaully created trigger, mark it as processed when the trigger has been fired, but not if it is a timed trigger.
or
2) Create a second windows service that creates the triggers on-the-fly at timed intervals.
The second option seems like a fudge to me, but the management of option 1 could easily turn into a programming nightmare (how do you know if the last poll of the table returned the event that needs to fire, and how do you then stop it re-triggering on the next poll)
I'd appreciate it if anyone could spare a few minutes to help me decide which route (one of these two, or possibly a third, unlisted one) to take.
Why not use a SQL Job instead of the Windows Service? You can encapsulate all of you db "trigger" code in Stored Procedures. Then your UI and SQL Job can call the same Stored Procedures and create the triggers the same way whether it's manually or at a time interval.
The way I see it is this.
You have a Windows Service, which is playing the role of a scheduler and in it there are some classes which simply call the webservices and put the data in your databases.
So, you can use these classes directly from the WebUI as well and import the data based on the WebUI trigger.
I don't like the idea of storing a user generated action as a flag (trigger) in the database where some service will poll it (at an interval which is not under the user's control) to execute that action.
You could even convert the whole code into an exe which you can then schedule using the Windows Scheduler. And call the same exe whenever the user triggers the action from the Web UI.
#Vaibhav
Unfortunately, the physical architecture of the solution will not allow any direct communication between the components, other than Web UI to Database, and database to service (which can then call out to the web services). I do, however, agree that re-use of the communication classes would be the ideal here - I just can't do it within the confines of our business*
*Isn't it always the way that a technically "better" solution is stymied by external factors?