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I am trying to simulate a call center with chatting and in this scenario, a customer service representative can serve multiple customer chats at the same time, depending on their capabilities
I started nby creating an Employee agent and build on this, but I could not simulate a scenario in which one “Employee agent” can serve several client “chat” agents at the same time based on their total capacity, as in a real chat call center ...
Please advise how I can configure the logic so that several agents can capture / delay one resource. Or create a block in which the employee agent will bypass each chat and check if he can release it.
Thanks in advance
This is a more advanced question and not that easy to answer in detail without building a lot of logic and functionality.
Overall I can suggest the following design, but depending on your level of expertise in AnyLogic (And Java) this might not be the best design and I am curious to see if anyone will venture any other options. But as for a moderate user (and use case), this design will be sufficient
Since there is no way to do what you asked with a standard resource pool I would suggest to setup a resource pool inside a new agent type and then either as a population or graphically (as per my design) you can send chats to these agents. Since each agent has a resource pools inside of them you can define the number of chats an agent can handle in the parameters of the agent which defines the resources in the resource pool
You can then have a function that takes a chat from the queue and gives it to the first available agent that has capacity.
And you call this function whenever something arrives in the queue as well as when something leaves a chat agent and also when a agent gets a new chat as multiple chats might arrive at the same time and we only send the first one.
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Some context:
I have little experience with ci/CD and manage a fast paced growing application since it saw the light of the day for the first time. It is composed by several microservices at different environments. Devs are constantly pushing new code to DEV , but they frequently forget about sending new values from their local .env ove to the openshift cloud, regardless of this being a brand new environment or existing ones.
The outcome? Services that fail because they lack to have their secrets updated.
I understand the underlying issue is lack of communication between both us DevOps staff and devs themselves. But I've been trying to figure out some sort of process that would make sure we are not missing anything. Maybe something like a "before takeoff checklist" (yes, like the ones pilots do in a real flight preparation): if the chack fails then the aircraft is not ready to takeoff.
So the question is for everyone out there that practices DevOps. How do you guys deal with this?
Does anyone automates this within Openshift/kubernetes, for example? From your perspective and experience, would you suggest any tools for that, or simply enforce communication?
Guess no checklist or communication would work for team that ...frequently forget about sending new values from their local .env ove..., which you must have already done.
Your step in the pipeline should check for service availability before proceeding to next step, eg. does the service has endpoint registered within acceptable time, no endpoint means the backing pod(s) did not enter readiness state as expected. In such case, rollback and send notification to the team responsible for the service/application and exit cleanly.
There's no fix formula for CI/CD, especially human error. Check & balance at every step is the least you can do to trigger early warning and avoid a disastrous deployment.
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I am building a mobile app using Flutter. All user's data is stored online in a MySQL database, so the app needs an internet connection for almost every user interaction (there is a backend REST API).
Users have to be able to create some lists of tasks, update and delete every task and list, and so on. But from the user's perspective, the need for an internet connection for every simple operation like adding or deleting a task is a bad experience. I need a way to support these operations even without connection with the backend and to apply these changes later when it is possible. But what is the best practice to handle this case?
How to keep the app behaving like normal even without an internet connection and sync all changes that the user has done with the backend when the internet is available again?
For example, if the user creates a new list the app expects to receive the new list's object (with id) from the backend. Later this id is used for every backend call about this list like adding a task in it.
What you can do is use a state management approaches like
Providers, Bloc etc and have a local state of your database or the needed list inside them and apply all the changes on them when offline and implement all these on to the server when connected to internet.
Read here about flutter state Management
also you can check when the device is connected to internet with this connectivity and data_connection_checker packages
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I have 20 Rest API's build using Jersey and Apache Client.I want to know the max TPS my server can withstand, using JMeter tool.what is the best way to achieve such kind of performance scenario goal.
First of all build a Test Plan. I believe it should have at least 20 HTTP Request samplers to cover all your endpoints and a HTTP Header Manager to send correct Content-Type header. See Testing SOAP/REST Web Services Using JMeter article for details.
Once you have the Test Plan - run it with 1-2 virtual users to check that it does what it supposed to be doing. Inspect requests and responses details using View Results Tree listener. Modify requests if needed.
Configure your Thread Group(s) so load is increased gradually, i.e. provide reasonable Ramp-Up time
Once you're happy with your test behaviour disable the View Results Tree listener and run your test in non-GUI mode
Analyze the results using i.e. HTML Reporting Dashboard. The value which interests you lives in Hits Per Second graph
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I need to build a Statistics System but I don't know if MongoDB would be the best solution. The system needs to track couple of things and than display the information. For example of a similar thing - a site, and every user that first visits the site adds a row with information about him. The system needs to store the data as fast as possible, and, for example, it creats a chart of the growth of users viewing the page using Google Chrome. Also, if a user visits again, a field in the users's already row is updated (say a field called "Days").
The system needs to handle 200,000 new visits a day (new records), 20,000,000 users visits again (updates) a day, and 800,000,000 DB records. It needs also to output the data fast - for example, creating a chart of how much users visits each day from England, using Google Chrome, etc.
So what would be the best DB to handle this data? Would MongoDB handle this fine?
Thanks!
Mongodb allows atomic updates and scales very well. That's exactly what it's designed for. But keep in mind two things: beware the disk space, it may run out very quickly and if you need quick stats (like region coverage, traffic sources, etc.), you have to precompute them. The fastest way is to build a simple daemon for this that would keep all numbers in memory and save it hourly/daily.
Redis is a very good choice for it, provided you have a lot of RAM, or a strategy to shard the data over multiple nodes. it's good because:
it is in memory, so you can do real time analytics (I think bit.ly's real time stats use it). in fact, it was originally created for that.
it is very very fast, can do hundreds of thousands of updates a seconds with ease.
it has atomic operations.
it has sorted sets which are great for time series.
RDM Workgroup is a database management system for desktop and server environments and allows in-memory speed as well.
You can also use its persistence feature; where you manage data in-memory and then transfer that data on-disk when the application shuts down so there is no data loss.
It is based on the network model with an intuitive interface so its scalability is top-notch and will be able to handle the large load of new visitors that you will be expecting.
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I want to implement a simple in-house table that tracks user page views on my website. Without targeting some specific hypothesis, what is useful data to store? Eventually I'll use it to build graphs or decision trees to better learn about our user base. This is static (no javascript).
Things I can think of:
URL accessed
HTTP refer[r]er
HTTP Accept Language
Browser-agent
Session id
User id (if logged in)
Time visited
It depends on how public your site is. If your site requires authentication you can have more controlled statistics because you can trace the user (visitors) history. In the case the user does not require authentication you are limited to the information provided by the SERVER VARIABLES: HTTP_USER_AGENT; REMOTE_USER; REMOTE_ADDR; REMOTE_HOST; REMOTE_PORT; HTTP_COOKIE; HTTP_USER_AGENT.
I have implemented something like this for some non-public site each time the user logs on to the site, the information I'm storing looks like:
User Key
Remote host IP
Date Logon
Last Request Datetime
Total time connected (minutes)
Last Request Minutes
Event/Action performed
Sounds like a good start,
I'd be inclined to store visitor IP address, and derived from that via a geo ip lookup the location of the visitor.
Also you could consider reverse dns'ing the IP to get an idea of the isp you're user is on, you might never use it but then again it could be useful if you have a report of downstream caching causing problems.