BitBucket is celebrating an important milestone – 10 million registered users. With 28 million repositories and 3.5 million build minutes every week, BitBucket is a vital tool for many teams.
I am (and have been) a member of several teams and projects, which heavily rely on BitBucket (and BitBucket pipelines) for their day-to-day operation.
Happy 10 million milestone, BitBucket! Keep it the great work!
One thing that I like about the modern world is that large technology companies are a lot more open than they were in the previous century. Many of them contribute to the Open Source ecosystem and frequently share their wisdom on how to use and not to use a particular technology.
Have a look at the recent post from Bitbucket blog: Searching DynamoDB: An indexer sidecar for Elasticsearch, for example.
It’s not your usual marketing nonsense about introducing a new needless service or self-praising review of a product. It’s a rather deep dive into a technical topic that has been getting a lot of attention for the last few years – NoSQL databases. Not only the blog post itself is interesting, but it provides plenty of useful links to other resources. Like this one, which covers database partitioning in depth. Or this one, which lists some of the best practices for designing and using partition keys effectively.
I wish more companies shared their technical insights like this.
sr.ht – pronounced “sir hat” – is a new competitor in the world of GitHub, BitBucket, and GitLab. Much like all of these, you can either self-hosted it or use a managed service. It might not yet be as fancy, polished, and cool (I think they need a better name and the domain) as its competitors, but there are a couple of reasons that might make a difference when making a choice:
BitBucket blog announces the support for scheduled Bitbucket Pipelines. Â This is super cool and has been on the wishlist for a while now. Â Here are a few examples of how this feature is useful:
- Nightly builds that take longer to run
- Daily or weekly deployments to a test environment
- Data validation and backups
- Load tests and tracking performance over time
- Jobs and tasks that aren’t coupled to code changes
