At OVHCloud, we are open sourcing our “Agility Telemetry” project. Jerem, as our data collector, is the main component of this project. Jerem scrapes our JIRA at regular intervals, and extracts specific metrics for each project. It then forwards them to our long-time storage application, the OVHCloud Metrics Data Platform.
Agility concepts from a developer’s point of view
To help you understand our goals for Jerem, we need to explain some Agility concepts we will be using. First, we will establish a technical quarterly roadmap for a product, which sets out all features we plan to release every three months. This is what we call an epic.
For each epic, we identify the tasks that will need to be completed. For all of those tasks, we then evaluate the complexity of tasks using story points, during a team preparation session. A story point reflects the effort required to complete the specific JIRA task.
Then, to advance our roadmap, we will conduct regular sprints that correspond to a period of ten days, during which the team will onboard several tasks. The amount of story points taken in a sprint should match, or be close to, the team velocity. In other words, the average number of story points that the team is able to complete each day.
However, other urgent tasks may arise unexpectedly during sprints. That’s what we call an impediment. We might, for example, need to factor in helping customers, bug fixes, or urgent infrastructure tasks.
How Jerem works
At OVH we use JIRA to track our activity. Our Jerem bot scraps our projects from JIRA and exports all necessary data to our OVHCloud Metrics Data Platform. Jerem can also push data to any Warp 10 compatible database. In Grafana, you simply query the Metrics platform (using Warp10 datasource) with for example our program management dashboard. All your KPI are now available in a nice dashboard!
Discover Jerem metrics
Now that we have an overview of the main Agility concepts involved, let’s dive into Jerem! How do we convert those Agility concepts into metrics? First of all, we’ll retrieve all metrics related to epics (i.e. new features). Then, we will have a deep look at the sprint metrics.
To explain Jerem epic metrics, we’ll start by creating a new one. In this example, we called it
Agile Telemetry. We add a Q2-20 label, which means that we plan to release it for Q2. To record an epic with Jerem, you need to set a quarter for the final delivery! Next, we’ll simply add four tasks, as shown below:
To get the metrics, we need to evaluate each individual task. We we’ll do this together during preparation sessions. In this example, we have custom story points for each task. For example, we estimated the
write a BlogPost about Jerem task as being a 3.
As a result, Jerem now has everything it needs to start collecting epic metrics. This example provides five metrics:
jerem.jira.epic.storypoint: the total number of story points needed to complete this epic. The value here is 14 (the sum of all the epic story points). This metric will evolve whenever as the epic is updated by adding or removing tasks.
jerem.jira.epic.storypoint.done: the number of completed tasks. In our example, we have already completed the
Write Jerem botand
Deploy Jerem Bot, so we have already completed eight story points.
jerem.jira.epic.storypoint.inprogress: the number of ‘in progress’ tasks, such as
Write a BlogPost about Jerem.
jerem.jira.epic.unestimated: the number of unestimated tasks, shown as
Unestimated Taskin our example.
jerem.jira.epic.dependency: the number of tasks that have dependency labels, indicating that they are mandatory for other epics or projects.
This way, for each epic in a project, Jerem collects five unique metrics.
To complete epic tasks, we work using a sprint process. When doing sprints, we want to provide a lot of insights into our achievements. That’s why Jerem collects sprint data too!
So let’s open a new sprint in JIRA and start working on our task. This gives us the following JIRA view:
Jerem collects the following metrics for each sprint:
jerem.jira.sprint.storypoint.total: the total number of story points onboarded into a sprint.
jerem.jira.sprint.storypoint.inprogress: the story points currently in progress within a sprint.
jerem.jira.sprint.storypoint.done: the number of story points currently completed within a sprint.
jerem.jira.sprint.events: the ‘start’ and of the ‘end’ dates of sprint events, recorded as Warp10 string values.
As you can see in the Metrics view above, we will record every sprint metric twice. We do this to provide a quick view of the active sprint, which is why we use the ‘current’ label’. This also enables us to query past sprints, using the real sprint name. Of course, an active sprint can also be queried using its name.
Starting a sprint means you need to know all the tasks you will have to work on over the next few days. But how can we track and measure unplanned tasks? For example, the very urgent one for your manager, or the teammate that needs a bit of help?
We can add special tickets on JIRA to keep track of those task. That’s what we call an ‘impediment’. They are labelled according their nature. If, for example, the production requires your attention, then it’s an ‘Infra’ impediment. You will also retrieve metrics for the ‘Total’ (all kinds of impediments), ‘Excess’ (the unplanned tasks), ‘Support’ (helping teammates), and ‘Bug fixes or other’ (for all other kinds of impediment).
Each impediment belongs to the active sprint it was closed in. To close an impediment, you only have to flag it as ‘Done’ or ‘Closed’.
We also retrieve metrics like:
jerem.jira.impediment.TYPE.count: the number of impediments that occurred during a sprint.
jerem.jira.impediment.TYPE.timespent: the amount of time spent on impediments during a sprint.
TYPE corresponds to the kind of recorded impediment. As we didn’t open any actual impediments, Jerem collects only the
To start recording impediments, we simply create a new JIRA task, in which we add an ‘impediment’ label. We we also set its nature, and the actual time spent on it.
For the impediment, we’ll we also retrieve the global metrics that Jerem always records:
jerem.jira.impediment.total.created: the time spent from the creation date to complete an impediment. This allows us to retrieve a total impediment count. We can also record all impediment actions, even outside sprints.
For a single Jira project, like our example, you can expect around 300 metrics. This might increase depending on the epic you create and flag on Jira, and the one you close.
We love building Grafana dashboards! They provide both the team and the manager a lot of insights into KPIs. The best part of it for me, as a developer, is that I see why it’s nice to fill a JIRA task!
In our first Grafana dashboard, you will retrieve all the best program management KPIs. Let’s start with the global overview:
Quarter data overview
Here, you will find the current epic in progress. You will also find the global team KPIs, such as the predictability, the velocity, and the impediment stats. It’s here where the magic happens! When filled correctly, this dashboard will show you exactly what your team should deliver in the current quarter. This means you have quick access to all important current subjects. You will also be able to see if your team is expected to deliver on too many subjects, so you can quickly take action and delay some of the new features.
Active sprint data
The active sprint data panel is often a great support during our daily meetings. In this panel, we get a quick overview of the team’s achievements, and can establish the time spent on parallel tasks.
The last part provides more detailed data. Using the epic Grafana variable, we can check specific epics, along with the completion of more global projects. You have also a
velocity chart, which plots the past sprint, and compares the expected story points to the ones actually completed.
The Grafana dashboard is directly availble in the Jerem project. You can import it directly in Grafana, provided you have a valid Warp 10 datasource configured.
To make the dashboard work as required, you have to configure the Grafana project variable in the form of a WarpScript list
[ 'SAN' 'OTHER-PROJECT' ]. If our program manager can do it, I am sure you can! 😉
Setting up Jerem and automatically loading program management data give us a lot of insights. As a developer, I really enjoy it and I’ve quickly become used to tracking a lot more events in JIRA than I did before. You are able to directly see the impact of your tasks. For example, you see how quickly the roadmap is advancing, and you become able to identify any bottlenecks that are causing impediments. Those bottlenecks then become epics. In other words, once we start to use Jerem, we just auto-fill it! I hope you will enjoy it too! If you have any feedback, we would love to hear it.
Software Developer on the OVHcloud Metrics Data Platform and data lover!