Pluralsight will acquire GitPrime for $170M
techcrunch.com
techcrunch.com
It’s a highly repeatable pattern. There should be a GitPrime for every industry.
- This is only true if the security controls that your team, application, infrastructure has in place is matches the major cloud providers (i.e. Salesforce, Google, AWS, Microsoft). Even then, spreading your data around to 1,000 different SaaS vendors increases the surface area for attack/loss by 1000x.
"Trying to build a vertical analytics offering on top of OSS increases the level of difficulty by 100x"
- 100x is hyperbole, it significantly harder before OSS was focused on operations, but now there is an HA Helm chart, or even an K8s operator for most of the popular OSS components. It might still be slightly harder today, but organizations that want to pull insights from THEIR data often value the proprietary nature of that data.
If you look at his comment history, you'll notice he mentions Snowflake at every single opportunity. Snowflake raised $450M last October (~$1B valuation), so they have a nice warchest for strategic acquisitions.
[1] https://techcrunch.com/2019/02/19/google-acquires-cloud-migr...
[2] https://technical.ly/philly/2018/11/07/stitch-acquired-by-ta...
How do you measure 100x? How come it isn't 90x or 112x?
Does that mean what one engineer can do with a commercial database, you would need 100 people do the the same thing with OSS in the same time frame?
If you used a phrase like "difficulty on another level" or something descriptive like that instead, I'm sure people would be more interested to hear what you have to say.
- The pricing structures don't tend to be amenable to this operating model. Most of the newer SaaS ETL services like Fivetran and Alooma tend to structure their pricing discrimination/tiering to favor a higher volume of throughput through a low number of individual connectors/sources. At least the last time I was sourcing one of these solutions, trying to follow the above pattern (a high volume of individual connections with potentially low volume of events from each source) was almost impossible to negotiate without a substantial increase in cost for any given volume of events.
- The pricing structures also tend to be unfriendly to unpredictable and unknown event volume, particularly at the pre-launch phase. While that's not a problem if you're aiming towards the enterprise space or have investment capital to burn, it's a non-starter for people looking to bootstrap an idea that may or may not gain any market adoption. Industry- and domain-specific BI tools are inherently niche, and tend to have a market discovery phase as you align with that industry. Committing to minimal annual event volume for your data pipelines before you've even attempted to go to market pushes you towards rolling your own pipelines and away from using any of the tools like Fivetran that would have simplified the go to market process in the first place.
- Data security and legal compliance. It's quite possibly more of an issue with my current environment and client pool, which skews more towards the enterprise. But my current job is infinitely more difficult because leveraging SaaS-based ETL tools like Fivetran, Alooma, Funnel.io, Supermetrics, etc are all absolute non-starters. Between GDPR, the new California privacy laws, and all of the press on data leaks over the last few years, any solution that includes "sending internal data to external companies" or "providing credentials for internal data sources to external parties" triggers instant lawyer and IT security review. And that includes going all the way down the rabbit hole - if we try to use a vendor, then we need to know and audit who all they give access to, etc. Which basically means we have to roll our own pipelines and keep them internal or on a client's own cloud account. At least for a lot of interesting use cases for domain-specific BI tools, I could see that same caginess coming into play.
The security reviews when there are 3 parties are a pain. It can be overcome, the benefit of getting the data infrastructure automated just has to justify the extra sales effort.
Encourages frequent small commits with low "churn". Trivial to game if you write a script to split your commits and artifically remove "churn" by making sure you don't touch your changes more than once. Also penalizes you for high "impact" commits. Adding a bunch of docs, renaming packages, or even running auto format penalizes you in metrics.
It's completely blind to the language. Doesn't understand the code one bit. Doesn't tell you anything about code quality or if your "rockstar" only writes so much code because he copy pasted everything. Not kidding, almost all the code our "top coder", per git prime, wrote had to be redone after he got canned. He was copy pasting trash everywhere.
I'm not against metrics but what it measures largely isn't meaningful. Ex. It's well known that lines of code across different languages are not equivalent.
Not sure why they thought it was a purchase that helped them in their mission.
I do miss it though, and am hoping to see another 50% off Black Friday special.
Where do you find the best content?
Probably because they spent all their money on GitPrime.
It started with custom courses, certifications, training journeys and completion scores and I believe the intention here is to tie that towards project velocity and code productivity.
It is fairly expensive, however. Starts at around $10k/year which can make it a tough budgetary sell.
I wonder if they'll price it in with Pluralsight as a package or keep it independant.
Overall, I thought they handled the "you can't make metrics for developers" type objections fairly well. To get everyone on the dev team engaged and thinking about their metrics seemed like too big of a hurdle given the cost per seat of GitPrime.
It would chart if an engineer made a large number of "churn" diffs vs new code vs "legacy/refactoring" which was modifying code that was last touched a long time ago.
While the acquisition price is public, would love to learn more about revenue or # of customers. They must have had some serious revenue/traction to be bought for $170M.
Not exactly. I was at a startup that was only doing about $15M in annual revenue that got picked up for $350M. A lot of common PE values in tech are well past 25x in public stocks which seems (oddly) "normal" these days.
- opportunity to easily cross-sell to a new swath of the market - continuing to grow the acquired business - realize economies of scale that the acquired business were working towards
"Pluralsight will acquire GitPrime for a total purchase price of $170 million to be paid in cash. This amount represents a multiple of approximately 5 times to 6 times expected 2020 billings."
That puts 2020 projected revenue at $28-34 million. During the Q&A portion of the call, Pluralsight's CEO mentioned that "they [GitPrime] only have a few hundred customers".
[1] https://finance.yahoo.com/news/pluralsight-inc-ps-q1-2019-01...
It tells you what the reality in Git is - how many commits, how many lines of code changed, how much refactoring etc., so there's nothing really wrong with it. If that's what you're interested in, that's what you get.
Wow
Sure, you could have a team of people running those git commands against every repository you have and compiling an excel spreadsheet to create data visualizations for each and every engineer you've got on a team, and you might end up with something roughly where GitPrime was 3 years ago, and taking hours to do what it does in seconds.
Now scale it to 2,000 engineers for reports the CTO of Walmart can look at. Scale it to give insight at the team level.
You've basically said "oh AWS isn't anything special, you can do all of that with KVM."