Tool Reviews
Honest, in-depth reviews of infrastructure tools and platforms. Find the right tools for your enterprise needs.
Grafana
Open-source analytics and visualization platform for metrics, logs, and traces.
Pricing: Open Source free; Grafana Cloud from free tier; Enterprise pricing varies
Pros
- + Extensive data source support
- + Beautiful visualizations
Cons
- - Dashboard sprawl risk
- - Performance at scale
Kubernetes
Production-grade container orchestration for automating deployment, scaling, and management.
Pricing: Free, Open Source (Apache 2.0); Managed options vary by provider
Pros
- + Industry standard
- + Extensive ecosystem
Cons
- - Operational complexity
- - Learning curve
Prometheus
Open-source monitoring and alerting toolkit designed for reliability and scalability.
Pricing: Free, Open Source (Apache 2.0)
Pros
- + Powerful query language
- + Excellent Kubernetes integration
Cons
- - Requires separate long-term storage
- - High cardinality challenges
Terraform
Infrastructure as Code tool for building, changing, and versioning infrastructure safely and efficiently.
Pricing: Open Source free; Terraform Cloud from $20/user/month
Pros
- + Extensive provider ecosystem
- + Clear plan/apply workflow
Cons
- - Limited programming constructs
- - State management complexity
ArgoCD
Declarative GitOps continuous delivery tool for Kubernetes.
Pricing: Free, Open Source (Apache 2.0)
Pros
- + Pure GitOps model
- + Excellent UI
Cons
- - Kubernetes-only
- - Secret management
vLLM
vLLM is a high-throughput, memory-efficient inference and serving engine for large language models (LLMs). It’s open-source and designed to make LLM inference faster and more cost-effective by maximizing GPU utilization and throughput, using techniques like PagedAttention and dynamic batching to reduce memory overhead and serve many requests on the same hardware. Developed originally in an academic setting and now maintained by a community of contributors, vLLM is used at scale to serve LLM inference workloads efficiently without relying on proprietary cloud inference APIs.
Pricing: Free to use and deploy
Pros
- + Significantly improves GPU utilization for LLM inference
- + Reduces memory fragmentation through PagedAttention
Cons
- - Requires GPU infrastructure to be useful
- - Not beginner-friendly compared to managed AI APIs