Thoras.ai

We predict Kubernetes traffic before it happens. We see the spikes coming, scale before they hit, and save you money while we’re at it. Built by SREs, for SREs.

[Thoras.ai @thorasai]

A Thorassian isn’t built for comfort.

Early on, our founding team took the time to define what that actually means because culture is a conscious, intentional effort. Otherwise, it becomes accidental.

It’s something we hire for, onboard around, and embody every day.

[Thoras.ai @thorasai]

Most teams can see their Kubernetes costs, but visibility alone doesn’t stop waste.

What matters is taking action to reclaim it while keeping workloads stable. Thoras predicts where costs are heading and adjusts in real time.

Here's how ⬇️ https://t.co/zLJunH5ROq

[Thoras.ai @thorasai]

☝️ Stop guessing pod sizes.

Thoras predicts what your pods actually need and adjusts CPU and memory before demand shifts. Unnecessary restarts, ooms and overprovisioning are an entirely outdated. Modern workloads deserve better.

Check this out 👇️

https://t.co/TVkozsPUQP

[Thoras.ai @thorasai]

🎙️ On the TestGuild podcast, our COO Jennifer Rahmani breaks down the classic Kubernetes autoscaling tradeoff: cost vs. performance.

Then explains why it doesn’t have to exist and how we’re getting both, faster.

 Take a look 👇️ https://t.co/tBgQWVS6nq

[Thoras.ai @thorasai]

🤝 Thoras is partnering with Agiletek to help federal agencies deploy secure, scalable infrastructure faster and with less waste.

This is about making AI adoption practical, reliable, and mission-ready 🇺🇸

More here 👇

https://t.co/iEpjY08044

[Thoras.ai @thorasai]

Most scaling issues are timing issues.

@MuxHQ was reacting with HPA until traffic spikes made that too late.

With Thoras:
✔️ 0 incidents
✔️ 38% less compute
✔️ No more babysitting

Take a closer look: https://t.co/WrrBcUrsVa

[Thoras.ai @thorasai]

“Spend less money.”
Sounds simple. It can also be dangerous.

In a recent conversation with Aaron Rice, CIO of Vorboss — and a Thoras customer, he shared why cost-cutting fails when it’s disconnected from workloads, and why that’s exactly where most tools fall short.

[Thoras.ai @thorasai]

🔥 Part 1 of our Engineering Hot Takes Series

We asked our customer — Joey Espinosa, Director of Platform Engineering at Gametime — to rate common industry practices. The results? Spicy. 🌶️

[Thoras.ai @thorasai]

Everyone’s selling cost savings.

We’re selling peace of mind.

Reliability comes first, always.

Because downtime costs more than any cloud bill ever could.

Watch the full conversation with Nilo Rahmani on Front Lines Media: https://t.co/55rxUmYecW

#SRE #DevOps #FinOps

[Thoras.ai @thorasai]

AI won’t replace reliability engineers. It’ll just make their lives less painful. That’s what we talked about with Front Lines Media: https://t.co/xj0oVLBO4K

[Thoras.ai @thorasai]

Amid yesterday’s large-scale outage, our CEO Nilo Rahmani shared thoughts on why the best reliability teams don’t just react — they proactively prevent chaos.

(That car beep mid-video wasn’t planned, but it did make a great metaphor for unexpected chaos.)

[Thoras.ai @thorasai]

We’re heading to #KubeCon in Atlanta. Come find us at booth 1471 and see how AI can predict scaling needs before they happen.

Need a ticket? Message us for 20% off. Reliability’s about to get smarter.

#Kubernetes #DevOps #SRE #AIOps #CloudNativeCon

[Thoras.ai @thorasai]

That “aha” moment that started it all. While studying interactive intelligence and machine learning at Georgia Tech, Nilo realized something obvious yet overlooked: every other industry was already using ML, except reliability. Why should SREs be the last to get intelligence?

[Thoras.ai @thorasai]

Burning money on overprovisioned compute? Someone’s holding the hot potato… and you don't want it to be you.

[Thoras.ai @thorasai]

Nothing to see here… except Nilo Rahmani casually sharing how a customer saved $2–3M in the time it takes to make coffee.

[Thoras.ai @thorasai]

SOC 2: ✅
Predictive autoscaling: ✅
Overpriced monitoring bills: ❌

Thoras is officially certified. The system scales itself and behaves itself.

[Nilo Rahmani @SheDevOps]

Overlooking idle compute is irresponsible as an engineering or finance leader, but diverting focus to build a homegrown solution isn’t the answer either.

[Thoras.ai @thorasai]

That’s exactly why we built Thoras: predictive autoscaling.

[Thoras.ai @thorasai]

The 2025 DORA report is out. Key takeaway: AI isn’t just for fixing faster. It’s for predicting and preventing issues before they hit production.

[Thoras.ai @thorasai]

This shift, from reactive to proactive, is the real promise of AI in engineering.