Cloud Cost Engineering and Open Source FinOps
Notes from the team building C3X. Cost estimation for Terraform, the economics of cloud infrastructure, and how to ship FinOps tooling without a SaaS gate.
Managed PostgreSQL cost compared: RDS vs Cloud SQL vs Azure Flexible Server
AWS RDS, GCP Cloud SQL, and Azure Database for PostgreSQL Flexible Server price managed Postgres similarly, compute per vCPU and memory, storage, and high-availability options. The cost drivers and levers are shared. This compares them.
AWS t4g vs t3 cost: Graviton burstable instances are ~20% cheaper
t4g (Graviton, ARM) burstable instances cost about 20% less than t3 (Intel) for comparable size, often with better performance per dollar. The catch is ARM compatibility. Here is the comparison and when the switch is free money.
AWS instance families explained: matching the family to the workload
AWS instance families (general purpose, compute, memory, storage, and accelerated) target different workloads, and using the wrong family over-pays for resources you do not need. This is a practical guide to choosing the cost-effective family.
AWS i4i vs i3 cost: newer storage-optimized instances, better value
i4i storage-optimized instances offer faster NVMe local storage and better price-performance than the older i3 generation. For high-IOPS, low-latency local-disk workloads, the newer generation is usually the cost-effective choice. Here is the comparison.
Block storage cost compared: EBS vs Managed Disks vs Persistent Disk
AWS EBS, Azure Managed Disks, and GCP Persistent Disk price block storage similarly, by provisioned capacity and performance tier, with the fastest tiers charging for provisioned IOPS. This compares them and shows the shared optimization levers.
Managed Kubernetes cost compared: EKS vs AKS vs GKE
EKS, AKS, and GKE all charge for the worker nodes; the difference is the control-plane fee (EKS and GKE charge per cluster-hour, AKS's standard tier is free) and autopilot-style options. This compares them and where the real cost lives.
Event-driven vs polling: the cost of asking versus being told
Polling burns compute and requests asking for changes that usually have not happened; event-driven architectures do work only when something occurs. For infrequent events, event-driven is dramatically cheaper. Here is the cost tradeoff.
Message queue cost compared: SQS vs Pub/Sub vs Service Bus
SQS, Google Pub/Sub, and Azure Service Bus price messaging differently, SQS per request, Pub/Sub per TiB of throughput, Service Bus per operation or messaging unit. This compares the models and the surprises in each.
Compression to reduce cloud cost: fewer bytes, lower bills
Compression shrinks the bytes you store, transfer, and scan, and cloud bills those bytes. Compressing data can cut storage, egress, and query cost at once, for a little CPU. Here is where compression pays and where it does not.
Tiered storage strategy: matching data temperature to storage cost
Most data cools over time: hot when new, cold within weeks, rarely touched within months. A tiered storage strategy moves data through cheaper tiers as it ages, cutting storage cost without losing access. Here is how to design one.
Cloud cost anomaly alerting: catch the spike before the invoice
A cost anomaly, a runaway resource, a misconfigured loop, a leaked key, can add thousands before the monthly bill reveals it. Anomaly alerting detects unusual spend as it happens. Here is how it works and how it complements pre-deploy estimation.
Cloud budget alerts: simple thresholds that prevent bill shock
Budget alerts fire when spend crosses a threshold you set, giving early warning before a bill balloons. They are simple, free, and the first line of cost defense. Here is how to set effective budgets and where they fit alongside estimation.
Spot fleet diversification: capturing the discount without the drops
Spot instances are cheap but reclaimable, and concentrating a fleet in one instance type risks a mass interruption. Diversifying across types and zones smooths that risk, letting you run more of a workload on Spot safely. Here is how.
AWS Elemental MediaConvert cost: per minute of output, by settings
MediaConvert bills per minute of output video, priced by resolution, frame rate, and features like HDR or advanced codecs. Encoding more than you need, in higher tiers than required, drives the bill. Here is how the per-minute model works.
AWS IoT Core cost: messages, connection minutes, and rules
IoT Core bills connectivity per million connection-minutes, messaging per million messages, and rules-engine actions, plus device shadow and registry operations. Chatty devices and heavy rule fan-out drive the bill. Here is the model.
AWS Managed Prometheus cost: per sample ingested and stored
Amazon Managed Service for Prometheus bills per metric sample ingested, per query processed, and for storage. High-cardinality metrics and short scrape intervals drive ingestion cost. Here is how the model works and how to control cardinality.
AWS Managed Grafana cost: per active user, by role
Amazon Managed Grafana bills per active user per month, by role (editor or viewer), plus optional add-ons. Cost scales with your user base, not dashboards or data. Here is how the per-user model works and how to keep it lean.
AWS Keyspaces cost: serverless Cassandra billed per request and GB
Keyspaces (managed Cassandra) bills read and write request units, storage per GB-month, and optional features, with on-demand and provisioned capacity modes. It scales to zero with no clusters to manage. Here is how it prices versus self-managed Cassandra.
Azure Container Instances cost: per-second vCPU and memory, no cluster
Azure Container Instances bills per vCPU-second and memory-GB-second while a container runs, with no cluster to manage or idle. It suits bursty and short-lived containers; steady workloads are cheaper on AKS. Here is the model.
Azure Machine Learning cost: compute is the bill, not the workspace
Azure ML's workspace is low-cost; the bill is the compute it runs, training clusters, compute instances, and managed online endpoints, plus associated storage. Idle compute instances and always-on endpoints are the classic waste. Here is the model.
Azure Data Lake Storage cost: blob tiers plus transaction charges
Data Lake Storage Gen2 prices like blob storage, hot, cool, cold, and archive tiers plus transaction and data-retrieval charges, with a hierarchical namespace. Matching tier to access frequency and minimizing transactions are the levers. Here is the model.
GCP Apigee cost: an always-on platform priced by tier and calls
Apigee is a full API management platform priced by subscription tier (or pay-as-you-go per API call), with a significant baseline for the standard tiers. It is powerful but not cheap. Here is how it prices and when a lighter gateway suffices.
GCP Batch cost: free service, you pay for the compute it schedules
GCP Batch adds no charge of its own; you pay for the Compute Engine VMs it runs your jobs on, including Spot. Spot workers, right-sized machines, and jobs that scale to zero are the levers. Here is how to run batch cheaply.
Object storage cost compared: S3 vs Cloud Storage vs Blob
S3, Google Cloud Storage, and Azure Blob price object storage similarly, tiered storage, request charges, and egress, but the details and egress rates differ. This compares the three and shows why egress, not storage, usually decides the bill.