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r/mlops is a subreddit with 18k members. Its distinguishing qualities are that the community is large in size.
The landing zone for anything MLOps - beginners and pros welcome. Vendors behave!
Popular Themes in r/mlops
#1
Advice Requests
: "Would you find a blog/video series on building ML pipelines useful?"
9 posts
#2
Solution Requests
: "What are some really good and widely used MLOps tools that are used by companies currently, and will be used in 2025?"
7 posts
#3
Ideas
: "Brand naming suggestion?"
1 post
#4
Self-Promotion
: "🚀 Launching OpenLIT: Open source dashboard for AI engineering & LLM data
"
1 post
Popular Topics in r/mlops
#1
Mlops
: "I started with 0 AI knowledge on the 2nd of Jan 2024 and blogged and studied it for 365 days. I realised I love Mlops. Here is a summary."
60 posts
#2
Model
: "Serving encoder Models to many users efficiently"
11 posts
#3
Ai
: "🚀 Launching OpenLIT: Open source dashboard for Ai engineering & LLM data
"
11 posts
#4
Inference
: "Why is everyone building their own orchestration queuing system for Inference workloads when we have tools like Run.AI?"
5 posts
#5
Llm
5 posts
#6
Kubernetes
5 posts
#7
Models
: "Tensor and Fully Sharded Data Parallelism - How Trillion Parameter Models Are Trained"
5 posts
#8
Tools
: "What other MLOps Tools can I add to make this project better?"
4 posts
#9
Sagemaker
: "Why do we need MLOps engineers when we have platforms like Sagemaker or Vertex AI that does everything for you?"
4 posts
#10
Aws
: "Guide: Easiest way to run any vLLM model on Aws with autoscaling (scale down to 0)"
4 posts
Member Growth in r/mlops
Daily
+35 members(0.2%)
Monthly
+835 members(4.9%)
Yearly
+8k members(73.3%)
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