From Telco Cloud to Autonomous Networks, Are We There Yet?

(A quick conversation between 𝙈𝙚 and 𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶)

𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶:
Mohamed, we keep hearing terms like Telco Cloud, zero-touch, and autonomous networks…
But in real deployments — is this actually happening or just marketing noise?

𝙈𝙚 (𝙈𝙤𝙝𝙖𝙢𝙚𝙙):
Great question — and I’ve asked myself that many times in the field.
Let’s take it step by step.

🔹 Telco Cloud was the starting point: moving from hardware-defined networks to virtualized and software-defined infrastructure.
We started with VNFs (Virtual Network Functions) — like vMMEs or vPGWs — on OpenStack.
Then came CNFs (Cloud-Native Functions) on Kubernetes — especially in the 5G Core and SBA architecture.

But cloud is just infrastructure.
👉 Autonomous networks are about self-operating logic layered on top.

𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶:So cloud is the engine… but autonomy is the driver?

𝙈𝙚 (𝙈𝙤𝙝𝙖𝙢𝙚𝙙): Exactly. Here’s a breakdown:

1️⃣ Virtualization = software replaces hardware
2️⃣ Cloud-native = microservices, elastic, scalable
3️⃣ Automation = playbooks, scripts, templates
4️⃣ Autonomous = closed loops that monitor, decide, act, adapt

In one project I led, we migrated a regional packet core to a telco cloud stack.
That reduced the footprint and OPEX — but real autonomy only came after we added telemetry + ML models + policy engines.

𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶:Where does AI fit into this?

𝙈𝙚 (𝙈𝙤𝙝𝙖𝙢𝙚𝙙):It’s the brain of the system.
Autonomous networks need AI to process real-time data at scale.

Here’s what advanced operators are doing:

• 📶 Predictive scaling — up/down capacity based on traffic
• ⚡ Energy saving — sleep cells, AI-controlled radio states
• 🔁 Closed-loop assurance — auto rollback if KPIs degrade
• 🛠 Root cause isolation — AI detects issues before alarms trigger

The key? NWDAF — the Network Data Analytics Function introduced in 5GC.
It allows inference models to run inside the core network.

𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶:What’s the gap between today and true autonomy?

𝙈𝙚 (𝙈𝙤𝙝𝙖𝙢𝙚𝙙): Here are the 4 biggest roadblocks I’ve seen:

• 🧱 Data silos — OSS, RAN, Core are disconnected
• 👥 Skill gaps — not enough ML Ops or policy expertise
• 🔒 Vendor lock-in — many automation tools are closed
• ❌ Intent translation — most systems focus on how, not what

In a recent workshop with an African MNO, we mapped SLA intents (like ultra-low jitter) into automated slice config and QoS triggers — across 4 layers.
So yes — it’s happening, but it needs architecture + mindset shift.

𝙏𝙚𝙘𝙝 𝙀𝙭𝙥𝙡𝙤𝙧𝙚𝙧 📶:
So how do we get started?

𝙈𝙚 (𝙈𝙤𝙝𝙖𝙢𝙚𝙙):
Here’s a short operator playbook:

1️⃣ ✅ Cloudify key domains — core, OSS, transport on telco-grade Kubernetes
2️⃣ ✅ Unify telemetry — break data silos
3️⃣ ✅ Run closed-loop pilots — SLA assurance, healing, auto-scaling
4️⃣ ✅ Train teams — intent modeling, data analytics, not just CLI

📌 Most important: Start small.
Don’t aim for Level 4 automation on day one.
Autonomous doesn’t mean “no humans” — it means humans define the intent, and the system executes it.

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