preeti_dewani's profile picture. Product | Software Engg | Postgres | Statistics | Poems | Chai

Preeti Dewani

@preeti_dewani

Product | Software Engg | Postgres | Statistics | Poems | Chai

Joined May 2022
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Preeti Dewani Reposted

As a managed SaaS partner, we're obsessed with reducing monitoring costs for our customers. In that endeavor, we built an 'auto-discovery' tool to improve monitoring coverage for our customers. @preeti_dewani writes 👇

last9io's tweet image. As a managed SaaS partner, we're obsessed with reducing monitoring costs for our customers.

In that endeavor, we built an 'auto-discovery' tool to improve monitoring coverage for our customers.

@preeti_dewani writes 👇

Preeti Dewani Reposted

@PreetiDewani 's talk has solid, useful takeaways. She has built a tool by interacting with multiple customers and understanding how opaque the cardinality view of metrics is. Listen to the talk and try out the tool - github.com/pree-dew/metri…

Emitting lots of metrics from services often lead to high cardinality issues & increased resource utilization for time series databases - using apt tools to analyze system states, identify cardinality issues & optimize instrumentation code helps your observability stack's uptime.

rootconf's tweet image. Emitting lots of metrics from services often lead to high cardinality issues & increased resource utilization for time series databases - using apt tools to analyze system states, identify cardinality issues & optimize instrumentation code helps your observability stack's uptime.
rootconf's tweet image. Emitting lots of metrics from services often lead to high cardinality issues & increased resource utilization for time series databases - using apt tools to analyze system states, identify cardinality issues & optimize instrumentation code helps your observability stack's uptime.


Starting writing about concepts that I found interesting to learn and share. As a big Postgres fan, this journey will begin with this: preetidewani.substack.com/p/postgres-the… #PostgreSQL


MLP vs MVP There is a thin line between MLP & MVP that differentiates viable and lovable products. It takes the extra mile & better prioritisation to make a feature/solution/product lovable instead of only viable. At @last9io, we're obsessed with creating MLPs.


The journey from “hoping” to “knowing” about new improvements in the product is sometimes exciting, fulfilling, tiring and shattering. But, for sure is great learning. We @last9io are ready to have that experience for our customers.


Reducing the gap between expected and experienced behaviour makes a product more usable. We at @last9io are trying to take a small step in that direction daily.


As a PM, What are the 3 common questions we ask repeatedly? 1. What problem am I trying to solve (work backwards)? 2. What am I trying to optimise (when the solution is time-consuming)? 3. What is the % contribution of any change in the big picture? Learnings @last9io #PMStories


Sometimes putting, the most unlikely people who have a pinch of naivety on what it takes to win and succeed are the ones that drive the most significant impact. Learning this every day @last9io #PMStories


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