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Akamas Insights now GA

Optimize reliability, performance, and costs

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Akamas is the autonomous optimization platform that unites developers, SREs, and platform engineers around one goal: delivering reliable, efficient services. By connecting directly to your observability data, Akamas detects optimization opportunities, estimates their impact on cost and reliability, and recommends or applies safe, validated optimizations across the full stack - from applications to clusters.

HN · launched Nov 10, 2025 · 16 upvotes (top 37%) · 0 views

Niche: cloud infrastructure and development platforms · 74 launches, 6 in the last 7 days · Explore this niche →

Category and tags

  • Horizontal
  • Observability & eval
  • B2B
  • AI-native
  • Commercial product

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Could you build this?

No Autonomous full-stack Kubernetes and cloud performance/cost optimization requires complex mathematical modeling, reinforcement learning or Bayesian optimization algorithms, and deep systems engineering integrated across real-time telemetry pipelines.

What it would actually take: A production implementation requires an agentic or telemetry-ingestion pipeline tapping into Prometheus, Datadog, or cloud metrics, paired with an optimization engine executing multivariable black-box tuning (e.g., Gaussian processes, Bayesian optimization). It also needs an automated execution layer that safely modifies Kubernetes manifests, JVM flags, or cloud VM allocations without risking SLA violations. This demands specialized expertise in cloud operations, reliability engineering, and advanced machine learning for systems optimization.

Discussion

12 comments analyzed.

Competitors

Other products that read as similar to this one : 58 launches clear the similarity bar, closest 8 shown.

Attention rank: #23 of 59 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 12 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.