5 Aug 2026, 10:42 UTC495 views2 reactionsread 7 August 2026 Running a self-hosted LLM in Kubernetes with vLLM 👨💼
With the rise of cost for the LLMs and the privacy concerns more and more enterprises opt to run local models(and I am experimenting with them myself). Grab a guy how to setup an open-source LLM with Kubernetes!
#llm #cloud #devops #architecture
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4 Aug 2026, 11:25 UTC596 views4 reactionsread 7 August 2026 SOC2 demystified
We recently obtained SOC2 certification for Supplied. Our customers frequently ask how secure their data is with us. Answering this very question in the detailed post
#security #soc2
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30 Jul 2026, 07:04 UTC≈1,050 viewsread 7 August 2026 We became so faster writing code, but do we ship more?
Talking with Baruch Sadogursky
about what exactly prevents us from unlocking true productivity, and it's not better agents. 👇
https://youtu.be/a_Kq18ufZzU
22 Jul 2026, 06:05 UTC≈1,260 viewsread 7 August 2026 Photo
Clustering Billions of Products for Agentic Commerce with Catalog API 🤓
Shopify Catalog groups billions of listings without a common schema. It first matches products inside each store, then connects them across stores with a Universal Product Identifier (UPI). LLMs assign a structured label to every product. This enables consistent grouping, high precision, and better recall. AI searches based on Catalog data conve…
21 Jul 2026, 16:38 UTC≈1,080 views2 reactionsread 7 August 2026 The State of Streaming to Apache Iceberg in July 2026: Every Path, Its Latency, and What to Do When Seconds Are Not Fast Enough 👨💼
In mid-2026, teams no longer ask, “Should we use Iceberg?” They ask, “How current can our Iceberg tables be?”. And this is where the main tradeoff relies dictating your data architecture and tools to go with. From tuned Flink to Kafka connect latency numbers varies from 30 seconds to 15…
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Architecture Weekly pinned «Most “AI agents” are workflows with an LLM inside. The real difference: who controls the flow? In my new video, I break down the five parts of a real agent—prompt, tools, state, memory and loop—plus the production essentials: tracing, guardrails and evals.…»
17 Jul 2026, 14:33 UTC≈1,150 views7 reactionsread 7 August 2026 Most “AI agents” are workflows with an LLM inside.
The real difference: who controls the flow?
In my new video, I break down the five parts of a real agent—prompt, tools, state, memory and loop—plus the production essentials: tracing, guardrails and evals. Here's the link:
https://youtu.be/SmSv_6bI5QM
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14 Jul 2026, 12:39 UTC≈1,290 views7 reactionsread 7 August 2026 I bought a setup for running local LLMs. Grab the unpacking video!
https://www.youtube.com/shorts/xcbmp1p06jM
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2 Jul 2026, 05:57 UTC≈1,580 views2 reactionsread 7 August 2026 People go to the technical conferences and the only value they get are free snacks and some talks missing the true purpose of such events.
I published a guide how to actually prepare the conferences and what to do there depending on your career aspirations.
https://open.substack.com/pub/softwarearchitectureweekly/p/capturing-value-out-of-technical?r=1m9i62&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
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29 Jun 2026, 06:46 UTC≈1,410 views1 reactionsread 7 August 2026 Stragglers, Not Failures: How Adaptive Hedged Requests Reduce p99 Latency by 74 Percent 🤓
In fan-out microservice architectures, the dominant cause of high p99 latency is stragglers — slow-completing requests rather than failures — because one straggler in a fan-out blocks the entire composite response. While retries are a solution for failed requests, the stragglers require a parallel request if slow response is de…
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24 Jun 2026, 09:37 UTC≈1,360 views2 reactionsread 7 August 2026 The Inference Paradox: How Split-Brain LLMs Are Killing Your GPU ROI 🤓
LLM inference has a structural hardware mismatch: the prefill phase is compute-bound (processing all input tokens in a single forward pass) while decode is memory-bandwidth-bound (reading the full KV cache to emit one token per step), so coupling both phases on the same GPU means each permanently starves the other. Kubex's enterprise audits surfa…
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2 Jun 2026, 19:15 UTC≈1,550 viewsread 7 August 2026 https://open.substack.com/pub/softwarearchitectureweekly/p/building-a-stripe-app-for-data-sync?r=1m9i62&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
Showing the 12 most recent of 20 posts we hold for @architectureweekly. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.