|
Hi friends, If you had asked me about the future of DevOps / infrastructure a few years ago, I would’ve pointed straight to serverless. I don’t think that anymore. After this week’s Kubecon in Paris (amazing event by the way!), here’s a collection of thoughts and prediction on the future of tech. While serverless was a big deal, the rise of container technology and Kubernetes has been astonishing, even the biggest advocates of the technology did not expect this much adoption. Serverless, as a function-based solution, seem to be stagnating. It’s driven by practical issues like cost, complexity, and the developer experience. Plus, Amazon’s shift from Lambda to a monolith earlier this year alongside DDH’s take on it, shedding even more light on the subject, did not contribute. Looking ahead, I see a trend towards automated solutions that simplify using cloud services from providers like AWS, Azure, Hetzner, or OVH. This approach is “somewhat serverless” but leans more towards using containers. Let me explain. Examples like Heroku, Netlify, Vercel, and AWS Amplify are making it easier for developers by reducing complexity, and automating DevOps tasks. These platforms are mainly for smaller projects right now, but I believe bigger operations will soon catch on. They realize these automated solutions can take over much of the DevOps workload, especially with a bit of AI integration. I predict that such solutions like these could meet the needs of about 80% of businesses. The remaining 20% might find the cost too high or the solutions not fitting their unique needs. There’s also a wave of new technologies making cloud services faster, more efficient, and cheaper—like faster Docker builds with deopt, better microVMs with KraftCloud, and enhanced object storage (Minio), or even better block storage with SimplyBlock. It’s clear that user-friendly, integrated deployment solutions are becoming more common, promising lower costs and better performance. I’m excited to watch how this evolves and am even considering creating something myself in this space. For now, these are the trends shaping our industry’s future. |
Every once in a while I send hand picked things I've learned. Kind of like your filter to the tech internet. No spam, I promise!
Stop Using Elasticsearch. Use Postgres Instead This issue is brought to you by: Postgres for sensor and machine data Factories, wells, grids, and fleets run on live machine data. Tiger Data keeps it performant and scalable in one Postgres. Get started with Text Search on TigerData→ Do you still need Elasticsearch? I wanted to test that properly, so I put Postgres in Docker, loaded it with thousands of support tickets, and checked how far the same BM25 relevance search used by dedicated search...
Somehow, Atuin Just Got EVEN Better This issue is brought to you by: Give your AI agents memory Learn how Oracle Agent Memory handles persistent context with custom extraction, hybrid search, filtering, and more control over what your agents remember. Read the developer guide → There aren't many terminal utilities I'd take with me anywhere. But if I had to pick just one, Atuin may very well be it. I've been using it for a few years now, and somehow the magic turtle keeps getting better. It...
You’ve Never Seen a Shell Like Xonsh This issue is brought to you by: Redis Iris: Your agents should be getting smarter Unreliable agents fail in production. Redis Iris is a unified, real-time context engine that delivers fresh, relevant context so agents perform at scale. Try for FREE Tell me if this sounds familiar:You start with a quick shell script. Then one step gets annoying, so you call Python. Then Python needs to shell out again. Then you’re parsing strings, juggling quoting, and...