Using microservices to turn the noisy data that's constantly emitted by agile software development tools into actionable information that lets development teams work more effectively can be a boon to boosting developer productivity and improving the developer experience. Enter Hakkiri, a startup who are doing just that with their Continuous Clarity platform. We spoke with Hakkiri co-founders Robert Orefice and James Smith to learn more about how Hakkiri is using MongoDB to power their platform.
How does MongoDB help your Continuous Clarity platform?
Hakkiri’s platform helps Agile software teams run their process with deeper insights and greater transparency. We like to equate it to a fitness tracker for your Agile teams. Attach it to your tools, enter in your planned deliverables, and the rest is taken care of for you. We’ve already thought of what to measure, how to measure it, curated how to visualize it, and added automated feedback to keep you tracking towards your goals.
MongoDB helps us solve our technical problems in a few ways:
- We needed the ability to design and implement an extensible schema that would be easy to evolve over time. Our product roadmap includes incorporating more data entities from the delivery toolchain (ex: build, test, and deployment) and MongoDB’s powerful document data model gives us confidence that we’ll be able to iterate effectively.
- Our platform pulls all the data together into a set of dashboards that enable teams to track their work more easily than ever before (ex: see Cumulative flow across teams). As such, we do a lot of business intelligence and analytics, and MongoDB makes this easy and scalable with aggregation pipelines.
- MongoDB Atlas, the fully managed database service, gives us a trusted, secure, and encrypted database environment to store data. We don’t need to spin our wheels doing database administration work.
- And finally, we needed a database that could effectively manage time-series data. Our application processes event streams coming from delivery tools such as Jira.
- Again, an extensible schema that’s easy to evolve over time is invaluable
- Our data needs to be aggregated at multiple levels. MongoDB enables flexible and fast calculations of summaries at multiple levels, which comes in handy when a change at the lowest level requires recalculations up the chain
- MongoDB also provides efficient storage of time-series data for all the entities we track and perform analytics on