mkdev.me
@mkdev_me
Boosting productivity & reducing costs with Cloud Native, DevOps and AI. Consulting, audits, workshops. Client-focused, tailored solutions 🇩🇪🇪🇸🇺🇦
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#mkdevWeeklyHighlight Most famous use case for RDS Proxy is probably still "Lambdas", so it's nice to see a bit more traditional usage of this proxy, at scale: zurl.co/Dzk00
In the 80th mkdev dispatch Kirill talks about the recent AWS outage and the bigger implications of our over-reliance on the cloud providers for the whole web. Also inside: Terraform Cloud token abuse, the infinite sadness of migrations, hashing and more! zurl.co/BOeon
#mkdevWeeklyHighlight Numbers are impressive - the question is when we can get this as a default config, so that we don't need to activate this mode ourselves: zurl.co/SfwRN
We’ve seen every kind of infra and team setup—many we’ve designed or tuned. There’s always room to level up. We know what “great” looks like and can get you there. Book a call: mkdev.me/b/audits
#mkdevWeeklyHighlight This is smart: use S3 to transfer big amounts of data between A and B, due to the way S3 is priced. Definitely useful for big migrations that would otherwise cost a lot of data egress fees: zurl.co/MHeGK
In the 79th mkdev dispatch, Pablo talks about the last days of “being a developer” being a thing. Also inside: cross-account and cross-region log centralization in CloudWatch, Terraform Optimization Guide, CloudFlare Radar AI Insights and more! zurl.co/B0Vy7
#mkdevWeeklyHighlight As always, major Postgres releases bring a load of new features and improvements. Tudor Golubenco from Xata does a great job of giving us an overview together with practical examples: zurl.co/XoJBC
Dockerless course is now available in full on our website! Follow the full course for free, starting with Introduction: zurl.co/ZqEhR Re-explore containers from open standards perspective: learn all about OCI and how to see containers for what they really are.
From Public Cloud to IaC, from Data Engineering to AI Literacy, from Pipelines to Platform Engineering: check out the full list of mkdev Consultancies and schedule a call with us: mkdev.me/b/consulting Innovate faster with zero compromises
Why are the reasoning models currently the default? They are too slow! More on how our brain interacts with Chat GPT and others in episode 64 of DevOps Accents with Paul Larsen: zurl.co/iT0zx
#mkdevWeeklyHighlight This is great, we don’t need to make everyone install extra tooling required to open up console sessions to our containers: zurl.co/EtwsS
“Human in the loop” sounds smart—until it’s just approvals. Paul Larsen says: if your error budget allows, run it like a production ML system—with telemetry, thresholds, and audits. Hear more on DevOps Accents—get it wherever you get your podcast! zurl.co/Wa3g6
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AI Literacy, Humans In The Loop and Machine Learning Evaluation
How to assess your error budget for core cognitive abilities? In episode 64 of DevOps Accents, Paul Larsen, our Head of Data & AI, is back to discuss with Leo recent studies from Microsoft and MIT about ChatGPT and critical thinking: zurl.co/AGTPf
In the 78th mkdev dispatch Leo talks about his frustrations with European data protection laws. Also inside: understanding and remediating cold starts, HTTP/2, the Dockerless Course conclusion and more! zurl.co/fqpv3
#mkdevWeeklyHighlight This is seriously cool stuff that will simplify certificate management a lot and remove at least one component from your K8s clusters: zurl.co/1ToXB
97% of your org are data consumers. Only ~3% are data engineers or data scientists. Suzanne El-Moursi explains that the real challenge isn’t building more charts, it’s serving the 97% of employees who rely on data to make decisions every day. Full episode: mkdev.me/posts/data-sci…
Prompt engineering is the new English. Words = interface to AI. Now language skills matter more than ever when working with models and agents. In this #DevOpsAccents episode with Suzanne EL-Moursi we unpack Data Science 2.0: mkdev.me/posts/data-sci… #DataScience #AI #DevOps
#mkdevWeeklyHighlight What does it take to crawl 1 billion pages in 2025? On AWS, following the architecture the author came up with: 25 hours; $500 and 12 EC2 instances. Check out the full article to see how: zurl.co/fVEeX
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