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Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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OpenStack: host aggregates, flavors, and availability zones
2016-02-03 · via Datadog | The Monitor blog

When discussing OpenStack, correct word choice is essential. OpenStack uses many familiar terms in unfamiliar ways, which can lead to confusing conversations.

Host aggregates (or simply aggregates), are commonly confused with the more-familiar term availability zones—however the two are not identical. Customers using OpenStack as a service never see host aggregates; administrators use them to group hardware according to various properties. Most commonly, host aggregates are used to differentiate between physical host configurations. For example, you can have an aggregate composed of machines with 2GB of RAM and another aggregate composed of machines with 64GB of RAM. This highlights the typical use case of aggregates: defining static hardware profiles.

Once an aggregate is created, administrators can then define specific public flavors from which clients can choose to run their virtual machines (the same concept as EC2 instance types on AWS). Flavors are used by customers and clients to choose the type of hardware that will host their instance.

Contrast aggregates with availability zones (AZ) in OpenStack, which are customer-facing and usually partitioned geographically. To cement the concept, think of availability zones and flavors as customer-accessible subsets of host aggregates.

As you can see, host aggregates can span across availability zones.
Host aggregates and availability zones in OpenStack
As you can see, host aggregates can span across availability zones.

Host aggregates or availability zones?

As an OpenStack end user, you don’t really have a choice. Only administrators can create host aggregates, so you will be using availability zones and flavors defined by your cloud administrator.

OpenStack admins, on the other hand, should carefully consider the subtle distinction between the two when planning their deployments. Hosts separated geographically should be segregated with availability zones, while hosts sharing the same specs should be grouped with host aggregates.

Conclusion

You should now have a better sense of the differences between host aggregates, flavors, and availability zones. More information on host aggregates and availability zones is available in the OpenStack documentation. Additional terms and definitions can be found in the OpenStack glossary.

Check out our 3-part series about how to monitor and collect OpenStack Nova performance metrics. Also, be sure to take a look at our piece on How Lithium monitors OpenStack.