Our project involves containerisation of services / application and later they will be deployed on Kuberentes. My job is to do performance testing using Jmeter after the services are hosted on Kubernetes.
I am relatively new to Performance testing and have basic experience on Jmeter that I gained from working on it. I have understood how the app is load / perf tested using basic URLs or APIs but I want to know how I should go about handling performance testing for Docker containers hosted on Kubernetes.
How could I handle the above scenario?
JMeter doesn't know anything about the underlying technologies used at the backend, it just sends requests via Samplers, waits for responses and measures the elapsed time of the request and some other performance metrics. Later on you can generate HTML Reporting Dashboard to visualize the results
So your goal is to:
Identify the business use cases you need to implement for the performance testing
Identify network protocols which are being used under the hood of these business use cases
Create a JMeter Test Plan to precisely mimic the real user (or other application) accessing your system and doing what it supposed to be doing
I'm thinking about moving my DAL which uses DocumentDb and Azure Table Storage to a separate Web API and host it as a cloud service on Azure.
The primary purpose of doing this is to make sure that I keep a high performance DAL that can scale up easily and independently of my front-end application -- currently ASP.NET MVC 5 running as a cloud service on Azure but I'll definitely add mobile apps as well. With DocumentDb and Azure Table Storage, I'm finding myself doing a lot of data handling in my C# code, therefore, I think it would be a good idea to keep that separate from my front-end application.
However, I'm very concerned about latency issues introduced by HTTP calls from one cloud service to another which would defeat the purpose of separating DAL into its own application/cloud service.
What is the best way to separate my DAL from my front-end application without introducing any latency issues?
I think the trade off between scaling-out/partitioning resources and network latency is unavoidable. That being said, you may find the trade-off well worth it for many reasons (i.e. enabling parallel execution of application tasks, increased reliability, etc.) when working w/ large-scale systems.
Here are some general tips to help you minimize the hit on network latency:
Use caching to avoid cross-service calls whenever possible.
Batch cross-service calls and re-use connections whenever possible to minimize the cost associated w/ traversing the NAT out of one cloud service and through the load balancer into another. Note - your application must also be able to handle dropped connections (inevitable in cloud architecture).
Monitor performance metrics as much as possible to take measurements and identify bottlenecks.
Co-locate your applications layers within the same datacenter to keep cross-service latency to a minimum.
You may also find the following literature useful: http://azure.microsoft.com/en-us/documentation/articles/best-practices-performance/
I recently split out my DAL to a WebAPI that serves data from DocumentDB for both the MVC website and mobile applications for the same reasons stated by the questioner.
The statements from aliuy are valid performance considerations generally accepted as good practice.
But more specifically - in order to call Web API from MVC without latency using Azure cloud services, one should specify same affinity group for each resource (websites, cloud services, etc).
Affinity groups are a way you can group your cloud services by
proximity to each other in the Azure datacenter in order to achieve
optimal performance. When you create an affinity group, it lets Azure
know to keep all of the services that belong to your affinity group as
physically close to each other as possible.
https://azure.microsoft.com/en-us/documentation/articles/virtual-networks-migrate-to-regional-vnet/
I'm working to port some data access to dynamo DB in a high-traffic app. A bit of background - the app collects a very high volume of data, and some specific tables were causing performance issues in a traditional DB. So with a bit of re-design and some changes to the data layout we have been able to make them fit the DynamoDB niche nicely.
My question is around the use/creation of the client object. The SDK docs suggest it is better to create one client and share it amongst multiple threads, so in my repository implementation I have the client defined as a lazy singleton. This means it will be created once and all requests will share the same client (currently around 4000 requests per minute, but likely to grow massively as we come out of beta and start promoting the product).
Does anyone have any experience of making the AWS SDK scale?
Thanks
Sam
When you create one client and share it with multiple threads, only one thread can use the client at one point of time in some SDK.
Definitely if you create separate clients for different threads, it is going to slow down the process.
So I would suggest you to take a middle approach here,
Maximize the HTTP connection pooling size, so that more number of clients are allowed to be created.
And then you follow the sharing of client objects.
Batch operation can be used for .Net aws sdk
http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/BatchOperationsORM.html
I am planning to use vaadin to develop internal application, which will be used in high volume and accessed from offices spread around globe. The choice of vaadin stems out from the fact that it would make development of application easier and I don't need to worry about frontend coding. However, I am a little concerned that since all events are sent to the application server, and since the users would be accessing from globe, so can the network latency be a big issue in the responsiveness of application to support high volume throughput. The application is going to be used in high volume by 100-500 users per day. Any insights from previous deployments/experience?
There's a study made by Vaadin about the scalability. I hope these links will help you make the decision.
https://vaadin.com/blog/-/blogs/vaadin-scalability-study-quicktickets
http://www.slideshare.net/codento/vaadin-scalabilityslides
I use vaadin over the Internet but my server is in the same country. So I can't tell you how the application behaves over the globe, but I can say that vaadin is super fast within my connection. No difference between local / Internet!
What, at a minimum, should an application health-monitoring system do for you (the developer) and/or your boss (the IT Manager) and/or the operations (on-call) staff?
What else should it do above the minimum requirements?
Is monitoring the 'infrastructure' applications (ms-exchange, apache, etc.) sufficient or do individual user applications, web sites, and databases also need to be monitored?
if the latter, what do you need to know about them?
ADDENDUM: thanks for the input, i was really looking for application-level monitoring not infrastructure monitoring, but it is good to know about both
Whether the application is running.
Unusual cpu/memory/network usage.
Report any unhandled exceptions.
Status of various modules (if applicable).
Status of external components (databases, webservices, fileservers, etc.)
Number of pending background tasks (if applicable).
Maybe track usage of the application and report statistics on most/less used functionalities so you know where optimizations are most beneficial.
The answer is 'it depends'. Why do you need to monitor? How large is your operations staff? Do you need reporting? What is the application environment? Who cares if the application fails? Who cares if an exception happens? Are any of the errors recoverable? I could ask questions like these for a long time.
Great question.
We've been looking for some application-level monitoring solution for our needs some time ago without any luck. Popular monitoring solution are mostly addressed to monitor infrastrcture and - in my opinion - they are too complicated for a requirements of most of small and mid-sized companies.
We required (mainly) following features:
alerts - we wanted to know about
incident as fast as possible
painless management - hosted service wouldbe
the best
visualizations - it's good to know what is going on and take some knowledge from the data
Because we didn't find suitable solution we started to write our own. Finally we've ended with up-and-running service called AlertGrid. (You can check it for free of course.)
The idea behind it is to provide an easy way to handle custom monitoring scenarios. Integration API is very simple (one function with two required parameters). At the momment we and others are using it for:
monitor scheduled tasks (cron jobs)
monitor entire application logic execution
alert on errors in applications
we are also working on examples of basic infrastructure monitoring using AlertGrid
This is such an open ended question, but I would start with physical measurements.
1. Are all the machines I think are hosting this site pingable?
2. Are all the machines which should be serving content actually serving some content? (Ideally this would be hit from an external network.)
3. Is each expected service on each machine running?
3a. Have those services run recently?
4. Does each machine have hard drive space left? (Don't forget the db)
5. Have these machines been backed up? When was the last time?
Once one lays out the physical monitoring of the systems, one can address those specific to a system?
1. Can an automated script log in? How long did it take?
2. How many users are live? Have there been a million fake accounts added?
...
These sorts of questions get more nebulous, and can be very system specific. They also usually can be derived reactively when responding to phsyical measurements. Hard drive fill up, maybe the web server logs got filled up because a bunch of agents created too many fake users. That kind of thing.
While plan A shouldn't necessarily be reactive, it is the way many a site setup a monitoring system.
Minimum: make sure it is running :)
However, some other stuff would be very useful. For example, the CPU load, RAM usage and (in multiuser systems) which user is running what. Also, for applications that access network, a list of network connections for each app. And (if you have access to client computer(s)) it would be cool to be able to see the 'window title' of the app - maybe check each 2-3 minutes if it changed and save it. Also, a list of files open by the application could be very useful, but it is not a must.
I think this is fairly simple - monitor so that you can be warned early enough before something goes wrong. That means monitor dependencies and the application itself.
It's really hard to provide specifics if you're not going to give details on the application you're monitoring, so I'd say use that as a general rule.
At a minimum you want to know that the system is healthy. This is subjective in what defines your system is healthy. Is it computers are up, the needed resources exist, the data is flowing through the system, the data is properly producing results, etc, etc.
In my project we do monitoring of most of this and then some. It really comes down to what is the highest level that you can use to analyze that everything is working. In our case we need to know down to the data output. If you just need to know down to the are these machines up it saves you on trying to show an inexperienced end user what is wrong.
There are also "off the shelf" tools that will do a lot of the hard work for you if you are just looking too hard into data results. I particularly liked Nagios when I was looking around but we needed more than it could easily show so I wrote our own monitoring system. Basically we also watch for "peculiarities" in the system, memory / cpu spikes, etc...
thanks everyone for the input, i was really looking for application-level monitoring not infrastructure monitoring, but it is good to know about both
the difference is:
infrastructure monitoring would be servers plus MS Exchange Server, Apache, IIS, and so forth
application monitoring would be user machines and the specific programs that they use to do their jobs, and/or servers plus the data-moving/backend applications that they run to keep the data flowing
sometimes it's hard to draw the line - an oversimplified definition might be "if your team wrote it, it's an application; if you bought it, it's infrastructure"
i think in practice it is best to monitor both
What you need to do is to break down the business process of the application and then have the software emit events at major business components. In addition, you'll need to create end to end synthetic transactions (eg. emulating end users clicking on a website). All that data would be fed into an monitoring tool. In the past, I've done JMX for applications of which flowed into Tivoli Monitoring's JMX Adapter and then I've done scripts that implement a "fake user" and then pipe in the results into Tivoli Monitoring's Script Adapter. Tivoli Monitoring takes the data and then creates application health and performance charts from that raw data.