Kubernetes with Naveen 🇮🇳

@NaveenS16 · India 🇮🇳 · joined 10 Aug 2012

Bad-ass Kubernetes'Cluster Whisperer, Platform Thinker, Cloud Architect, Principal Engineer & Founder at @Themesfinity

10 972Followers

439Following

80 081Posts total

758Views on collected posts

Latest posts

Kubernetes with Naveen 🇮🇳@NaveenS1622 Sep

Running #EKS on #Fargate in regulated environments? Coz Fargate abstracts node management, injecting corporate egress proxies into pods can be tricky. Learn how to use #Kyverno to automate proxy injection across your workloads without modifying manifests https://t.co/F1xLrotUT4 155 views · 2 likes · 0 reposts · 0 replies Open on X →

Kubernetes with Naveen 🇮🇳@NaveenS1622 Sep

Scaling #AI models shouldn't mean drowning in #GPU infrastructure overhead. Learn how @tryramp streamlined their GPU #ML inference by adopting #ECS Managed Instances—eliminating custom AMI patching, manual ASGs, and launch template maintenance: https://t.co/UuCNC5LqPP #AWS 91 views · 0 likes · 0 reposts · 0 replies Open on X →

Kubernetes with Naveen 🇮🇳@NaveenS1622 Sep

@NaveenS16 Whether it helps comes down to lookup cost against the origin cost you avoid, weighted by hit rate. Below some hit rate you are adding latency to every request to save it on a few. Worth computing that threshold before adding the hop. 5 views · 0 likes · 0 reposts · 0 replies Open on X →

Kubernetes with Naveen 🇮🇳@NaveenS1622 Sep

Adding #Redis to #API doesn't automatically guarantee speed. Network overhead, unnecessary serialization, poor design,, caching data that rarely gets hit can slow down endpoints. Understand your query bottlenecks before adding cache layer: https://t.co/RJ94mbixyX #Database https

296 views · 5 likes · 2 reposts · 1 replies Open on X →

Kubernetes with Naveen 🇮🇳@NaveenS1622 Sep

You can speed up bad code, but a sluggish architecture will still choke your app every time. Standardize the blueprint first—tuning individual lines won't save a broken foundation. 211 views · 0 likes · 0 reposts · 0 replies Open on X →

Kubernetes with Naveen 🇮🇳@NaveenS165 Dec 2020

🧵 M E G A T H R E A D Check out all of my amazing threads that cover various topics like #JavaScript, #React, my favourite podcasts and many more... 👇#100DaysOfCode #CodeNewbie 0 views · 97 likes · 49 reposts · 13 replies Open on X →

Against accounts of the same size

5 posts from the last 90 days, next to the 10K–100K follower range. reaches fewer people than peers of the same size.

Median views155this account924median for 10K–100K

Reach, %1.41%this account3.62%median for 10K–100K

Engagement, %0.00%this account1.52%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	155	924	0.17×
Reach (views ÷ followers)	1.41%	3.62%	0.39×
Engagement rate	0.00%	1.52%	0.00×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

21122 Sep

296

155

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.00%22 Sep

2.70%

0.00%

1.29%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes63.6%7 in total

Reposts18.2%2 in total

Replies9.1%1 in total

Bookmarks9.1%1 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

Against accounts of the same size

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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