I'm trying to audit work that was done this year and have found that stories from back in January-March are missing. I'm able to see some of the releases for the later part of that period (Feb-March), but no stories. I've searched all of ADO for all of the story numbers from the releases we performed during this time and they are completely missing.
So, that leads me to my question. Do user stories have a retention period? Will they be removed after a certain period of time? If so, where is that setting?
Related
i have a project on Google Cloud Platform, using the Youtube Data V3 API. Everything was going well, earlier this month after receiving several emails alerting that I had to do an Audit, the queries for the day stopped completely. they were completely zeroed.
I followed the link to perform the Audit, and i successfully completed all the changes that were told to me in my application, strictly following the regulations. The audit went well. No further changes were required from me.
But the issue is that the queries per day remain at zero. I can't edit. It occurred to me that maybe using the Google Cloud Trial there could be some change. Negative. I'm still unable to increase the limits, not even using the balance they give you as a gift.
The project used approximately a margin of about 25,000 to 300,000 queries / day. I have requested 500.000 queries / day filling in the quota expansion form to have a little more margin.
Meanwhile the project has been stopped for almost a month. If anyone knows something or how I should proceed about it,
Thank you very much.
Have a nice day,
My team works in a 2 week timebox and they indicate how many hrs each PBI, Task, or Bug will take via effort (if PBI) and remaining effort (if Task), and both if a bug.
As they progress through the Sprint they update their hrs. to show progress of effort.
For example, it's July 24 and John knows that updating a module will take 20 hrs. To complete and as he progresses through the Sprint he updates that number to 15, 10, 5, and then eventually 0. My goal is to show a report with that trail to verify that the 20 hrs. committed to the task was completed. I did some research and could not find much help, but perhaps I'm not stating my question right. Any advice regarding this issue would be much appreciated.
What you are looking for is more like a time tracker and generated report to verify or reflect it.
We do not have this kind of build-in feature or report in TFS server. However, as a workaround, there is a number of applications/add-on out there that expose TFS time tracking/time sheet capability.
They offer different levels of integration with TFS depending on your specific workflows/requirements. They pick up your TFS data entries and provide dashboards for operational reports as well as API to get data loaded to your systems.
Some 3rd-party extension for your referenceļ¼
7pace time tracker
SSW Time Pro
We use Jira for issues bugs estimates and timesheets.
I've seen 2 approaches to using Jira and I want to hear what other people are doing.
Approach 1:
Log one feature, such as "Allow user to save as CSV". The task is assigned to a Developer and the workflow progresses from Not started, In Progress, Complete. Once done it's assigned to a Tester and they change workflow to Testing, then to Tested/Completed.
Approach 2:
Log a task/user story called "Allow user to save as CSV". Then developer logs subtasks such as, Front end, Backend and tester logs tasks such as create test plan, test right clicking. Once all dev and test sub-tasks are complete, someone marks the task as completed.
I prefer the first way, I've heard the second way is better for tracking time. It seems harder to manage what's going on with a sea of issues in Jira.
My company does first approach. This seems to be working so far ( about a year now ). With either approach I really love how everything seems to be logged in JIRA for history tracking.
I recommend using sub-tasks when you need to have work proceed in parallel. Or if the parent task is really large and the sub-tasks are around a few days each. But don't create sub-tasks unless they are needed.
Is there a way in JIRA to run a report to see how many issues were "resolved" by what users and how quickly since the issue was reported? It needs to be per user
Thanks
You can build arbitrary reports yourself with a Report Plugin Module, but my experience is that it's quite a hassle. Note that plugins will only work in self-hosted Jira installations, not in Atlassians hosted service.
Another way would be to leverage the REST API in order to fetch worklogs and process them externally.
Your requirement needs some clarifications I think. It seems you want to see the number of issues that were moved from some status to another status, or perhaps the last time the resolution field was set to a value (any value?). Then group those results by JIRA user.
A second requirement is to track the time from issue creation to the last time the resolution field was set. Again grouping by user.
I'd try using the Vertygo SLA plugin from Valiantsys to do this. It lets you define custom fields to track the time between two JIRA events such as a field updated or a status changed. I believe it can sum those fields and display grouped results in the JIRA statistics and two-dimensional gadgets.
Reports that group by user often become quite large as the number of users increases.
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.