a10y is not a monolithic product. It is a composition of best-of-breed open source components — each chosen for a specific reason. This page explains the trade-offs behind those choices.
OpenObserve excels at what it does: storing and querying logs, metrics, and traces with extreme storage efficiency. But observability data and alert management are fundamentally different problems.
| Capability | OpenObserve | Keep |
|---|---|---|
| Log / Metric / Trace storage | Excellent | Out of scope |
| SQL / PromQL query | Native | N/A |
| Threshold-based alerting | Basic | Advanced (multi-source) |
| Alert deduplication | No | Built-in |
| Cross-source correlation | No | AI-powered grouping |
| Recovery alert handling | No | Tracks resolved vs. active |
| Remediation workflows | No | Declarative YAML |
| Multi-tool integration | Limited | 110+ bidirectional |
OpenObserve answers "what happened?" — Keep answers "what is the problem, and what remains?"
Without Keep, operators must mentally correlate alerts from raw telemetry, track which issues have been resolved, and manually trigger remediation. This is the gap that prevents achieving TMF L3+ autonomy.
Datadog is a powerful, mature platform. But for autonomous network operations in telecom, it introduces fundamental constraints.
| Datadog | a10y (OpenObserve + Keep) | |
|---|---|---|
| Deployment | SaaS only | Self-hosted / Air-gapped |
| Data sovereignty | Data leaves your network | All data stays on-premise |
| Cost model | Per-host + per-GB ingestion | Infrastructure cost only |
| Telecom-scale log volume | Expensive at high volume | 140x lower storage cost |
| Custom AI / LLM integration | Locked to Datadog AI | Bring your own model |
| Closed-loop automation | Workflow Automation (limited) | Keep workflows + correlation-engine |
| Network protocol support | Agent-based, IT-centric | Syslog, SNMP, gNMI, custom VRL |
| Source code access | Proprietary | Full OSS |
Datadog is built for IT/cloud monitoring. a10y is built for telecom autonomous operations.
Telecom operators require data sovereignty, air-gap deployability, telecom-native protocol support, and cost predictability at petabyte-scale log volumes. These are not optional — they are regulatory and operational requirements.
a10y provides the cognitive core — the ability to observe, understand, and act on network events. But autonomous operations require more than intelligence. They require an operational platform.
a10y produces insights and actions. Aether Platform presents them in context — topology views, incident timelines, and natural-language interaction. Without this layer, operators must navigate multiple dashboards and mentally stitch information together.
active-inventory maintains a live graph of network devices, links, and services. This is critical for blast radius estimation ("if this router fails, which services are affected?") and impact-aware remediation ("reroute traffic before replacing the card"). a10y's correlation-engine uses this context, but it doesn't own it.
Helm charts handle Kubernetes deployment, resource management, secret injection, and upgrade strategies. Moving from "it works on my laptop" to "it runs in a carrier network" requires infrastructure engineering that is separate from the intelligence layer.
True closed-loop automation requires a feedback path: Act → Verify → Adjust. Aether Platform closes this loop by connecting remediation actions back to observability data, confirming recovery, and escalating when automated fixes fail.
a10y is the brain. Aether Platform is the body.
Intelligence without operational context is just analysis. Autonomous operations require both — the ability to understand what is happening and the infrastructure to act on that understanding safely, at scale, in production.
The TM Forum defines six levels of network autonomy (L0–L5). Different tooling choices land you at different levels. Here is where each approach realistically places you.
Most networks are stuck at L1–L2. The jump to L3 requires more than better dashboards — it requires alert intelligence (Keep), topological context (active-inventory), and AI reasoning (correlation-engine) working together.
The jump from L3 to L4 requires trust — trust built through transparent AI decisions, verifiable outcomes, and gradual expansion of autonomous scope. a10y is designed to earn that trust incrementally.
| Question | Answer |
|---|---|
| Why not OpenObserve alone? | It stores telemetry but cannot deduplicate, correlate, or remediate alerts. Keep fills this gap. OpenObserve alone keeps you at L2. |
| Why not Datadog? | SaaS-only, no data sovereignty, cost-prohibitive at telecom scale, locked AI, limited telecom protocol support. Also L2 — with a bigger bill. |
| Why not a10y alone? | a10y is the cognitive core. Aether Platform provides the operator interface, topology awareness, and production infrastructure needed to reach L3 and progress toward L4. |