I have configured one-inch aggregation APIs in my dapp for swapping. And I’m able to perform swapping also. But they have not given anything to configure swapping.
So I have configured one more transaction after swapping transactions, dedicatedly for the commission.
But this is charging the gas fee twice from the user (The first time the gas fee was paid for swapping and the second time for paying the commission fee)
So I’m looking for any efficient solution to doing this without paying an extra gas fee
Related
If you set up a OAuth for Youtube within your app that allows users to upload videos, does each video cost towards your 10,000pt quota?
I run a personal uploading bot and it does 3ish uploads per day within the 10,000 point quota but if I was to scale out as an app this wouldn't work since 5 users would max it out.
So if a user approves your app for upload permissions, would this cost toward your clients 10,000pts or is it 10,000 points per user per day?
Also how easy is YouTube's quota expansion form process if it is the former?
https://support.google.com/youtube/contact/yt_api_form?hl=en
By checking the quota calculator you will be able to see what each call costs. The vido.insert call for example costs 1600 quota.
If you check the google developer console and check your quota it might look something like this.
As you can see one of them states "per user" while the other does not.
Queries per day 10,000 is a project based quota. while Queries per minute per user is a user based quota.
It sounds like you should be applying for a quota extension if the 10,000 limit is not enough for your needs.
Also how easy is YouTube's quota expansion form process if it is the former?
Its a long process google says it takes twenty days my experience is three to six months average. You need to be prepared to get a NO. You also need to be prepared to have your quota shut down suddenly because they detect something they identity as spam or a violation. In the event of a shutdown you will need to apply for a new extension. Which again will take time.
I have standard ASP.NET MVC project and I need to calculate application availability to find out our SLA level. So, I need to get something like this for our web application.
Information from my hosting provider
System Availability: 99.9860%
Total Uptime: 30d 10h:22m:44s
Total Downtime: 0d 0h:6m:9s
Total Reboots: 3
Mean Time Between Reboots: 10.15 days
But I need to calculate availability for application. So, the question is
How to calculate ASP.NET MVC application availability in proper way?
Maybe someone has already implemented that, or any suggestion how to do that, any help will be appreciated.
Where to start?
The first point what I think that is Application Insights and availability test. The problem is that the minimum value of test frequency is 5 minutes. I need more precise measurements.
Next, create a some tool that will call my app every second and collect information. Result: a very large number of requests.
Also, get some perf counters from IIS or something like that. Need to investigate if it is possible.
I know that the question possible is too broad, but I didn't find any info about implementation of application availability. What do you think about that?
It would take to long if I was to explain all parts that can be done, so I'll keep it short.
Usually you define all these details in a Service Level Agreement where you also define the availability target (i.e. 99 %) that also include planned downtime. A 99 % availability target is to have the app running and its functionality as described in the document with at most approx. 87.6 h per year. Here is a SLA uptime calculator.
The normal interval is 5 minutes as you say, but it you can prove by using an external site / service that the suppliers are not meeting the requirements, you calculate your loss (revenue loss, labor costs etc) and claim the money from them. You already have a Business Impact Analysis (BIA) I guess otherwise you should do it.
Ok, now to the programming / DevOps part. I usually develop applications / services with this in mind and report its status to a third party service like NewRelic, Uptrends or similar. As an example I also use a self-made service for this because accurate requirements for delivering data at least once a second with a hard deadline. In my solution I use WebSockets to send data in both directions following a schedule, event or when needed. A benefit with that is that you can send status (good or bad) let say every 500 ms and you will know within one second if the app has failed (≈ 499 ms + 500 ms).
Using a service like this you can measure the uptime, custom events of interest and possible errors within a second and a ton of other metrics. Usually within 5-100 ms but WCET/WCRT is hard to estimate.
To answer your question, you cannot calculate application availability with so few measure points, once every 5 min is covering approx. 12 seconds per hour and you cannot have any reliable calculation from that. You can assume everything was ok between the measure points but that is called guessing. I have made implementations that have 14 400 measure points per hour in order to provide 500 ms accuracy (Banks).
I hope you got an answer that helps you with your problem.
I would like to understand the CloudKit free usage calculation, but I can't.
Could anyone describe what 40 requests per seconds (10 per 100.000 users) are? I couldn't find any definition what a request is. If I had 2 apps and every app would ping my CloudKit server at the same time, would it result in two requests per second (for the described moment)? How do I know how to limit the request in my apps and how to queue the requests so they can be done later when the time comes where the limit is not reached at the CloudKit server?
What about the 2GB data transfer (50 mb per user)? How should I understand these 50 mb, per second, per day for the eternity? What will happen if one user for one of my apps used 50 mb traffic?
How do I limit my app and still have a good clint server communication? Will I get an error when the limit is reached and won't automatically charged by Apple?
I do really like the programming ease of CloudKit but I'm kinda scared that it could go all way wrong and I will get charged for misunderstanding.
It is really hard for me to imagine how it is calculated.
I think your biggest concern will be quelled by knowing that you can set usage limits on these services. If you've hit this limit then the service will return an error and you can handle that in your app.
40 requests per second is across all users and devices. If you have 3600 users and they all pinged the server once per hour, that would average out to about 1/second. While that won't be enough to build a service like facebook, instagram, or twitter, it would probably be sufficient for getting weather data, a daily schedule, or food truck locations. For up to 4,000,000 users, the free tier will cover each user checking at most once every three hours with an even distribution.
2GB data transfer is for all of your users. Since the scaling doesn't take effect until you have 100,000 users, 2GB of data transfer is a pretty good amount to get you off the ground. Since it scales at 50MB per user, it's easy to figure out how much you can trust your app to communicate with the server. If just one user goes over but you're still under the total usage then you won't get charged. If you do go over, it's $0.10/GB of data transfer.
You could limit your app to only communicate so much until the user needs to pay for a premium service. If you allowed 50MB/user/month of Data Transfer and let the user know when they approached this limit that they'd have to pay then you'd never go over. You could also have ads on the device that essentially pay for the service to scale thus allowing users who use the app more to have more privileges than passive users but still allowing everyone to have a base usage.
The prices are at the bottom of this page and are fairly reasonable. You can definitely get a cheaper rate if you build things yourself and use AWS, but you'd need to be in the millions of users and/or have high demands for that to be a better option.
40 requests per second is across all users and devices. If you have
3600 users and they all pinged the server once per hour, that would
average out to about 1/second. While that won't be enough to build a
service like facebook, instagram, or twitter, it would probably be
sufficient for getting weather data, a daily schedule, or food truck
locations. For up to 4,000,000 users, the free tier will cover each
user checking at most once every three hours with an even
distribution.
Just about the 40 requests / second limit:
If this is correct, I sincerely don't understand why so many people in the forums says this is more than enough. For certain apps it might be enough to sync once per hour but if you want to keep save-game files synchronized between devices then 40 request /second is ridiculous. A weather app? don't make me laugh. On 90% of the apps out there you are going need to to insert, update, and delete, I wonder how many requests a simple update it is... I hope just 1, but I seriously doubt it.
On Firebase there is not a request limit like this one and the upload is FREE. They just charge you for the downloads.
I might be missing something about this CloudKit thing because I don't get that ridiculous limit.
What is the role of BPM (BussinessProcessManagement) in a realtime application?
I mean in which cases or where is BPM actually used?
I could get the documentation from the net, but where actually is it used?
One definition of BPM is that is combines workflow management (humans interacting) with enterprise application integration (EAI, systems interacting). You can get applications and tools for those applications - sometime embedded - which you can use to define you business process. Then, in a staging process, you can roll out the business process to that system or a set of applications. To execute a business process (BP) you can use a business process engine (e.g. jBPM), and each step of a business process can be represented by a user interaction, a user task, a system task or variations of these. You can have parallel business steps that only once all of these complete can go to the next business process step. And there is much more to that.
Once you have rolled out a business process you can monitor it and collect data for a number of parameters. Often you will be interested how long a business process took and what the limiting factors are, e.g. how many manual steps are required. Then you can go back to the designer tool and modify the process. With data taken from the production system you can then simulate whether your changes are actually an improvement. And if they are you roll it out replacing the previous version.
On a smaller scale you can workflow designer or business process designers to allow user changing a particular part of a process. Often applications have hard-coded business process support with only limited parameterization/configuration. Take an approval process. Which purchases need approval? By whom? Could multiple people approve in parallel thus shortening the purchasing process? You application may offer your users to design the approval process as needed. It would no longer be hard-coded and allow for much better adaptation to the needs of your customer.
These are just a few thought and definitely not a full coverage of this subject. But maybe it already gives some idea.
BPM can be used in Health care application for integrating various systems and in banking field for loans aplication processing where human involvement is involved in different steps for loans approval, and in health care industry it is used mostly used for bundle of claims which we receive every day for cliams processing and for business state in which state to know.
and in The airline Reservation System for ticket booking process how the process moves one one level to another ex: adding passenger to flight.
My organization is building a new version of our ticketing site and is looking for the best way to build an online waiting room when the number of users in our purchase path exceeds a certain limit. The best version of this queue would let new users in after existing users have either completed their purchase or have exceeded a timeout limit after entering the path.
I'm trying to get an idea of how this has been implemented by other organizations. Has anyone out there done something similar or have any experience with this? We have some ideas, but I'd like to get a sense of what solutions have been tried and what problems those solutions have run up against.
Just to be complete, this site is being built in Ruby on Rails, though I'd love to hear about how people have solved this regardless of platform.
Edit: To clarify: The need for the queue is not primarily to reduce load, but to limit the speed at which the web is purchasing tickets relative to people buying in other ways, like over the phone.
Before I outline one method for this, I want to point out that what you want to do doesn't make a lot of sense. Services on the web aren't like a physical store, where I can walk up and see that it's crowded and decide to stay or not. Queueing people on your site strikes me as shifting the blame from you (unable or unwilling to adequately provision resources) to me (punishing me for trying to use your site).
If you're selling something like show tickets, where quantity is limited and each item is tied to a seat, I think it's better to reserve items and time out those reservations if they aren't paid for in a timely manner. Ticketmaster does this, and I think it's a much better solution than blocking people at the door.
If you still want to go down this path, then I'd design the system like this:
As customers come to your site, record their arrival time. As they interact with the site, record a "last seen" time. "Last seen" will be used to determine activeness. You'll need a background job running very frequently to expire sessions quickly.
Once your limit is hit, you have an ordered queue of people who are blocked. As customers complete their transaction or time out, you'll mark the next person in the queue for entry into the purchase path.
For queued users, their browsers will make a request on a regular basis, checking to see if you've let them in yet. If yes, they proceed to the purchase path. If no, they continue to wait.
The purchase path needs a mechanism to check if someone is trying to circumvent your waiting area, and sends them back.
You might find the Online queuing for ticketing guide helpful. Check their repository at GitHub.
They've integration with Ruby On Rails, PHP, .NET, iOS, Android and similar platforms.
Queue-it enables you to gain control of website overload during extreme traffic peaks by offloading end users into an online queue.
When a peak traffic event occurs on a website, the online queue system sends users to the virtual waiting room environment where the users wait and are redirected back to the website at a rate it can handle.