I built Vigiles because production teams keep starting from zero after every incident.
The postmortem gets written.
The root cause gets documented.
It gets filed somewhere, it will never be read.
And then the next incident happens.
Same scramble.
Same war room.
Same questions, nobody has answers to.
So I built something that remembers.
Every incident closes with an AI postmortem automatically.
No manual write-up.
No chasing people for notes.
Just answers, ready before the next one hits.
The longer your team uses it, the smarter it gets. Free plan at https://t.co/ZuaVzAIuVu no credit card.
People laugh when someone says they can feel another person's energy through a video call.
Maybe it's not "energy" in the mystical sense. Maybe it's stress, pain, anxiety, exhaustion, or emotions that words don't reveal.
Sometimes after a call, you don't feel drained because of what was said. You feel drained because of what was carried.
The hard part is when you care deeply about that person. Your intuition says, "Give them space," but your heart says, "Don't leave them alone."
Still learning that loving someone doesn't always mean reaching out more. Sometimes it means praying for them, sending good intentions, and trusting that their healing isn't your responsibility to control.
Has anyone else felt this?
People are still chasing the same things.
Happiness. Certainty. Control.
Nothing has really changed, just the tools.
That is why understanding human behavior matters more than predicting the future.
Same as Ever
The recording of my OpenSearchCon China 2026 talk is now live.
I spoke about FinOps for Observability, specifically how teams can stop treating their observability stack as an unlimited budget line and start making intentional cost decisions without sacrificing visibility. OpenSearch sits at the center of that conversation, and the audience in Shanghai had some sharp questions that pushed the topic further than I expected.
If you are running logs, traces, or metrics on OpenSearch, or evaluating whether it makes sense for your stack, this talk covers the trade-offs that most vendors do not want you to think about.
The full recording is here: https://t.co/XLNNBZKJDe.
A genuine thank you to the @OpenSearchProj team for putting together an exceptional event and for building a project that gives the community something real to rally around. And to everyone in the OpenSearch community who showed up in Shanghai and engaged so openly, that energy is exactly why this ecosystem keeps growing.
#OpenSearch #FinOps #Observability #OpenSearchCon #CloudCost #AWS #AlibabaCloud #OpenSourceSearch
Just finished presenting at OpenSearchCon China 2026 in Shanghai.
The talk was called “FinOps for Observability” and the core argument is simple: most teams believe they face a binary choice between retaining all their observability data and controlling costs. That choice is false. Intelligent tiering gives you both full retention and dramatically lower spend at the same time.
We covered tiered storage on OpenSearch, ISM policies that automate the entire data lifecycle from ingestion to deletion, pipeline filtering with Data Prepper, right-sizing fundamentals, and a real case study that went from $15,200 to $4,100 per month with zero data deleted and zero visibility lost.
The slides are attached. The ISM policy from slide 6 is ready to copy and deploy into any OpenSearch cluster today.
If you are running observability workloads on AWS OpenSearch or Alibaba Cloud and your storage costs keep climbing, slide 5 is where to start. Everything else follows from that one architectural decision.
You can find the full interactive guides and the 60-day OpenSearch learning series at https://t.co/SGbCfleqr1.
Happy to answer questions in the comments especially if you are working through warm tier configuration on Alibaba Cloud or trying to get ISM and rollover set up for the first time.
https://t.co/ANwSjlwQNH
#OpenSearch #FinOps #Observability #OpenSearchCon #AWS #AlibabaCloud #CloudCostOptimization #SRE #DevOps
Speaking at OpenSearchCon China 2026 in Shanghai this Tuesday.
Topic: FinOps for Observability. How to cut OpenSearch costs without losing visibility.
Real strategies, real implementations. No fluff.
#OpenSearchCon#OpenSearch#FinOps
Day 11 of From Zero to OpenSearch Hero
Your cluster starts with a question every node asks: "Who else is out there?"
Discovery, bootstrapping, quorum voting, cluster manager task throttling. The internals that keep your cluster alive and prevent split-brain.
Most common production mistake? A mismatched node name in the bootstrap config. Case-sensitive. Character-exact. One wrong character and the cluster never forms.
Full post at https://t.co/YpGifMq92V
Interactive guide at https://t.co/8JAhapYaBF
#OpenSearch #DistributedSystems #SplitBrain #ClusterManagement #SearchEngineering #DevOps #AWS #AlibabaCloud #CloudArchitecture #OpenSource
Day 10 of From Zero to OpenSearch Hero is live.
This one covers migration and upgrade strategies because choosing the wrong path when you cannot downgrade a node is not a mistake you want to make in production.
Four strategies explained from rolling upgrades to the Migration Assistant, a version compatibility breakdown, Elasticsearch migration paths, and a full hands-on lab where you snapshot from OpenSearch 2.11 and restore on 2.17 using Docker.
The decision framework alone will save you hours of guessing.
Read it on https://t.co/pBmdPlHeXO and explore the interactive guide at https://t.co/bWf7W2BZur
#OpenSearch #Migration #AWS #AlibabaCloud #SearchEngineering #FromZeroToOpenSearchHero
First time in my life I journaled for 31 consecutive days.
Not because an app kept nudging me but because it made journaling effortless.
No distractions, just focused entries.
Truly love One Year app
Your chatbot confidently told a customer the wrong return policy. Made up dates. Invented percentages. Sounded completely sure.
This is the LLM hallucination problem.
RAG fixes it. Instead of asking the AI to remember everything, you give it a search engine. It reads your actual data before answering.
OpenSearch handles the entire pipeline natively.
One API call does retrieval and generation.
No glue code.
Full tutorial: https://t.co/7VQ1hzlGxs
Interactive guide: https://t.co/HRzCQZfyHo
#OpenSearch #RAG #GenAI #LLM #AWS #MachineLearning
OpenSearch is not magic.
It is a web server. Port 9200. HTTP requests. JSON responses.
Every fancy feature. Every complex query. Every advanced operation. All just HTTP.
GET to read. POST to add. PUT to create. DELETE to remove.
Learn the pattern once. Use it forever.
Terminal demo: https://t.co/JqIgxjP9UI
Full guide: https://t.co/c3p7gEO1j2
#OpenSearch #REST
A beautiful learning today. It is not the stars that make light, but light that makes stars.
The same is true for us. We do not need to become something bright. We already are. Our healing, our growth, our quiet courage. These are not journeys toward light.
They are light, becoming visible.
From the journey of turning scars into stars.
#HealingJourney #SelfDiscovery #InnerLight
Spent an afternoon debugging why OpenSearch would not start with Podman.
The password looked strong. Bash kept saying "event not found."
Turns out,
- OpenSearch 3.x uses zxcvbn to reject "weak" passwords
- Bash interprets ! as history expansion
- Single quotes fix everything
Watch me set it up: https://t.co/wgXjCt7ajq
Full writeup: https://t.co/rgJYCxeRMy
#OpenSearch #Podman #DevOps
Sometimes you just need someone beside you. Not to fix things. Just to be there.
I built Beside, a quiet space to sit with what you’re feeling.
No accounts. No data stored. Just you and a gentle guide to help name what’s heavy.
Try it: https://t.co/E63w8pEQdV
Would love your feedback 🙏 - still the work in progress :)
A good search retrieves documents. Great search retrieves the RIGHT documents first.
The difference? Reranking.
Two-stage retrieval:
- Stage 1: Fast search gets 100 candidates
- Stage 2: Cross-encoder picks the best 10
A cross-encoder sees query + document together. It understands context that embeddings miss.
Real example: Query: "What is the capital of the United States?"
Before reranking: Correct answer at #3
After reranking: Correct answer at #1 (98% confidence)
If you are building RAG, your LLM needs the RIGHT context. Reranking delivers it.
Day 6 of 60 - From Zero to OpenSearch Hero https://t.co/yP2H2PZ4i7
https://t.co/e9kHOrcpmy
#OpenSearch #AI #RAG #Search
A person who doesn’t know what the universe is, doesn’t know where they are.
A person who doesn’t know their purpose in life doesn’t know who they are or what the universe is.
A person who doesn’t know any one of these things doesn’t know why they are here.
So what to make of people who seek or avoid the praise of those who have no knowledge of where or who they are?” —MARCUS AURELIUS, MEDITATIONS, 8.52
Semantic search understands what you mean, not just the words you type.
I show you how embedding models work, which providers to use, and the exact steps to build it in @OpenSearchProj.
https://t.co/mQSWyyFF35
#opensearch#devops#searchengine