observability solutions

"Thank you for the new pricing changes. This makes it easier to explain to people."

"These new plans look great. It makes so much sense. Storage is cheap and network/compute is expensive. Counting events vs GB, you want users to stuff all the data into their events so they can get the most out of it."

"Congrats! It’s really awesome how this solves the “it’s hard to predict how many GB I’ll send”, “It’s hard to find out what’s sending too much”, “It’s hard to predict how much retention I’ll get”, problems in one fell swoop!"

"The best thing about the simplified pricing is that it reduces the number of volume metrics we had to think about from two (GB ingest per month and GB storage) to one measure (events per month). Events per month is something we can monitor usage of much more easily than GB ingest (which could sometimes blow up and be difficult to troubleshoot why), and thanks to Honeycomb's support for per-event sample rates, we can collect just the information that gives us incremental value, none that doesn't, and make much more efficient use of our volume metric."

"The Usage page is A LOT simpler, and the daily event traffic graph is very clearly showing I’m sending more than what I need to be. The per-dataset breakdowns very clearly show me which dataset is getting all the [mh]oney so I know who to talk to!"

"The big thing that I’m excited about is having 60 days of retention: we were keeping our retention VERY small to meet our budget before, and now we can get a lot more value in looking back at our previous data. I’m also excited about burst protection: we ran into a couple of days where we were eating up ingest bandwidth for a day or two and did not understand why."

"The new Usage page is exceptionally clean and informative. Being able to differentiate event traffic by dataset allows us to understand our enterprise consumption quickly and accurately. We have not encountered rate limits nor burst protection yet, but having this detail available to us will be valuable during peak periods."