Coverage
Azure cost optimisation across 15 service families
Cerberus Cloud runs 275+ automated finders across 15 Azure service families. Each finder ties a technical signal to real billing data, so findings arrive with an estimated recoverable value and are ranked by impact, effort and risk across every client tenant.
Azure Kubernetes Service (AKS)
42 findersNode pools, autoscaling, requests and limits, spot and off-hours capacity.
AKS cost optimisation- Modernise
- Rightsizing
- Scaling
- Off-hours schedules
Integration and messaging
26 findersLogic Apps, API Management, Event Grid, Data Factory, Service Bus and Event Hubs.
Azure integration and messaging cost optimisation- Modernise
- Remove unused
- Rightsizing
- Scaling
Data and analytics
23 findersMicrosoft Fabric, Databricks, Synapse, AI Search, Redis, PostgreSQL and MySQL.
Azure data and analytics cost optimisation- Commitments
- Modernise
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Networking
19 findersPublic IPs, gateways, firewalls, Front Door, ExpressRoute and load balancers.
Azure networking cost optimisation- Modernise
- Remove unused
- Rightsizing
Virtual machines and commitments
18 findersIdle and oversized VMs, scale sets, schedules, reservations and savings plans.
Azure VM cost optimisation- Commitments
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Storage
18 findersStorage accounts, blob tiers, file shares, managed disks and snapshots.
Azure Storage cost optimisation- Modernise
- Remove unused
- Rightsizing
- Off-hours schedules
Azure Machine Learning
18 findersCompute instances, clusters, and online and batch endpoints.
Azure Machine Learning cost optimisation- Modernise
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Azure OpenAI and AI services
18 findersModel deployments, provisioned throughput, AI services and Foundry projects.
Azure OpenAI and AI services cost optimisation- Modernise
- Remove unused
- Rightsizing
- Scaling
Azure SQL
17 findersDatabases, elastic pools, managed instances, serverless and backup retention.
Azure SQL cost optimisation- Deallocate
- Remove unused
- Rightsizing
- Off-hours schedules
Governance
17 findersKey Vault, backup vaults, tagging, Azure Hybrid Benefit, regions, and exposed or orphaned resources.
Azure governance cost optimisation- Commitments
- Modernise
- Remove unused
- Rightsizing
Azure Cosmos DB
16 findersThroughput, indexing, partitioning, consistency and regions.
Cosmos DB cost optimisation- Remove unused
- Rightsizing
- Off-hours schedules
App Service
13 findersApp Service plans, tiers, scaling and app consolidation.
App Service cost optimisation- Modernise
- Remove unused
- Rightsizing
- Scaling
- Off-hours schedules
Monitoring
13 findersLog Analytics ingestion and retention, Application Insights sampling and verbosity.
Azure Monitor and Log Analytics cost optimisation- Remove unused
- Rightsizing
Azure Functions
10 findersHosting plans, always-ready capacity and deployment slots.
Azure Functions cost optimisation- Modernise
- Remove unused
- Scaling
Azure Container Apps
9 findersReplicas, workload profiles, revisions and jobs.
Azure Container Apps cost optimisation- Modernise
- Remove unused
- Rightsizing
- Scaling
Finder counts as of . Coverage grows as new finders ship.
Types of fix
Every finder falls into one of these categories, so your team knows what kind of change a finding asks for before opening it.
- Remove unused
- Delete resources that no longer serve a workload but are still billed.
- Deallocate
- Release compute that is paid for while it sits stopped.
- Off-hours schedules
- Stop or scale down non-production resources outside working hours.
- Rightsizing
- Move to a smaller or cheaper size that still fits the measured load.
- Modernise
- Move to a newer generation, tier or hosting model that costs less for the same job.
- Commitments
- Cover steady usage with reservations or savings plans.
- Scaling
- Fix autoscale settings so capacity follows demand.
See the findings on a sample Azure portfolio
A 15-minute walkthrough: tenant connection, prioritised findings across these families, remediation scripts and savings history.