I was at Atlassian during the OpsGenie acquisition and part of that process. Honestly, the biggest surprise to me was how long it took to shut down OpsGenie as a standalone product.
The broader trend here is the shift from unbundling to consolidation. Over the past decade, many “features” were created as standalone SaaS products, but that era is winding down. We’re now seeing the pendulum swing back, with more consolidation across the industry.
In my opinion, OpsGenie should have been a built-in feature of Jira Service Management from day one of the acquisition.
It’s a tricky balance. It would be easy for Atlassian to add settings. But every setting adds complexity. And I think we can all agree that we don’t want Jira to be more complex.
It takes a short time to adjust to UI changes, but settings live on forever.
The brand also becomes a reinforcing moat in an interesting way when you become a household name. When your employees think to themselves "I want to send a quick video update to team X" and they instantly default to downloading Loom, IT's decision for which vendor to buy a solution like this from is practically made for them.
The product suite differs significantly from 2015. Put aside new and acquired products like Trello and OpsGenie, the existing products have significantly expanded their capabilities and added Premium and Enterprise tiers.
Revenue in 2015 was $320M,
In 2021 it was $2B. That kind of growth requires growth in Supporting functions and infrastructure teams, not just in product.
> Funny thing is jira is such a mess Atlassian introduced jira service desk more focused on tickets while the former can also do that.
Not quite. Service Desk (aka Service Management today) has a number of capabilities that differ quite significantly from Jira Software. The most obvious is the end-user facing help portal. But how users are managed is quite different, it has SLAs, different reporting, a knowledge base, etc. Just like Jira Software is flexible but tailored to software teams with boards, backlogs and sprints, Jira Service Management is tailored to IT teams and requirements specific to that market.
Great take. I worked on Confluence for a few years and have a bit of insight.
Search has been an area of focus on and off for the most part of the last 15 years. It actually has gotten a lot better and Atlassian has an entire team focused on improving the search experience across their suite of products (they started with Confluence). And from what I hear, they are focusing on all the right things.
To your point, no search system can be a good fit for every possible use-case. Confluence has a number of different use-cases, but let's just pick "documentation" and "intranet" as an example here.
Intranets are, to a large degree, about keeping up with what's new in a company. Therefore recent content is likely more relevant than older content.
When used for documentation, recency doesn't matter at all. If a document was written 2 years ago, but the content is still accurate, it's just as relevant as it was on day one.
That means no single relevance configuration will work well for all use-cases. Leveraging ML is essential. But even a single ML model across an entire Confluence instance is not going to work as different spaces are used for different use-cases. What's really required here is to build different models for different spaces to create a tailored relevancy for each space. It's not an easy problem to solve, but I'm confident they will get there with time.
Seeing the challenges with Search at Atlassian, despite having a large, dedicated team of engineers working on the problem, is what motivated me to join http://sajari.com. We've been doing a lot of work on reinforcement learning and Neural Search. Our focus right now is on public content websites and e-commerce, but eventually we will get around to enable products like Confluence to create a great search experience without the need for an entire team. Search is a hard problem, but there is so much opportunity to improve the experiences that are available today. Exciting times.
It may be depressing to be on the Confluence “search” team. But wouldn’t it be MORE depressing to be on their “editing” team? Or how about their “performance” team? :-(
I was the head of product for the developer tools at Atlassian in 2012. We thought long and hard about taking Bitbucket cloud and packaging it in a VM (which is what GitHub did at the time) or leveraging the platforms we’ve already built for Confluence and Jira that would give us access control and a plug-in system from day 1. It was a tough call.
Ultimately we’ve decided to build on top of our server platforms and target companies with 1000+ employees from day one. That decision had a huge impact on how we approached performance and what features we prioritised. The hierarchy of projects and permissions associated with them as well as the way we designed Pull Requests are good examples of that.
It was the right decision at the time, even if the product happened to be different in cloud and server, which did lead to some confusion. But Stash customers were really happy with the product.
Neural search in combination with learning algorithms and traditional keyword searches are clearly the future. They vastly outperform traditional search engines.
At sajari.com we have been working on an experiment that uses a 1 cpu machine on cloud run to serve a neural network generated, hash based index of an old BestBuy catalog (25k products). Retrieval uses an approximate nearest neighbour (ANN) look up which typically takes ~1msec. Speed and relevancy are already pretty good.
But we have also learned that there is no one silver bullet and we have seen the best results when combining neural search with traditional keyword search and reinforcement learning.
The broader trend here is the shift from unbundling to consolidation. Over the past decade, many “features” were created as standalone SaaS products, but that era is winding down. We’re now seeing the pendulum swing back, with more consolidation across the industry.
In my opinion, OpsGenie should have been a built-in feature of Jira Service Management from day one of the acquisition.