CerberusByte
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Services

What CerberusByte does

Practical consulting for infrastructure, security and delivery systems across cloud and on-prem environments.

Cloud & Hybrid Infrastructure

Architecture, modernization and operational clarity across AWS, Azure, GCP and on-prem environments.

  • Multi-cloud and hybrid cloud architecture design
  • Cloud migration planning and execution support
  • Cost optimization and resource governance
  • Infrastructure as Code (Terraform, Pulumi, Ansible)
  • Kubernetes cluster design and management
  • Network architecture and security group design

→ Your cloud and on-prem systems are inconsistent, costly to operate or difficult to reason about.

DevSecOps & Security

Security-first delivery, secrets management and platform hardening for teams that need reliability without improvisation.

  • DevSecOps pipeline integration and shift-left security
  • Secrets management (Vault, AWS Secrets Manager, SOPS)
  • Container and workload security hardening
  • IAM design and least-privilege enforcement
  • Vulnerability scanning and SAST/DAST integration
  • Security policy as code (OPA, Kyverno)

→ Security feels like a bottleneck or an afterthought — not something integrated into how your team ships.

Platform Engineering & CI/CD

Delivery foundations that reduce friction, standardize environments and make engineering teams faster with less chaos.

  • Internal developer platform design and implementation
  • CI/CD pipeline design (GitHub Actions, GitLab CI, Jenkins)
  • GitOps workflows (ArgoCD, Flux)
  • Environment standardization and developer tooling
  • Deployment strategies (blue/green, canary, feature flags)
  • Build performance and pipeline optimization

→ Deployments are manual, fragile or inconsistent across environments.

Observability & Reliability

Monitoring, telemetry and incident-readiness for systems that cannot afford blind spots in production.

  • Observability stack design (Prometheus, Grafana, OpenTelemetry)
  • Distributed tracing (Jaeger, Tempo)
  • Log aggregation and structured logging (Loki, ELK)
  • SLO/SLA definition and error budget management
  • Incident response process design and runbooks
  • On-call rotation and escalation policy design

→ You react to incidents instead of detecting them — visibility gaps make production unpredictable.

AI/ML Infrastructure

Infrastructure patterns for AI workloads: GPU node pools, model serving, data pipelines and MLOps integration.

  • GPU cluster design and node pool management
  • Model serving infrastructure (Triton, TorchServe, vLLM)
  • ML pipeline orchestration (Kubeflow, MLflow, Airflow)
  • Vector database infrastructure and RAG patterns
  • Cost management for GPU workloads
  • Model versioning and rollback strategies

→ ML models work in notebooks but fail at scale or cost too much to serve reliably.

Discovery & Architecture Reviews

Structured audit of your current state — infrastructure, tooling, team workflows and failure patterns — with written findings in priority order.

  • Current-state infrastructure audit and documentation
  • Architecture review against operational requirements
  • Bottleneck and risk identification
  • Prioritized findings report with actionable next steps
  • Technology stack evaluation and recommendations
  • Team capability assessment

→ You need clarity on where the real problem is before investing in the wrong layer.

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Not sure which service applies to your situation?

Most engagements start with a discovery conversation — not a sales call. Describe what you are dealing with and we will figure out together whether CerberusByte can help.

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