Hybrid deployment
Hybrid deployment is an arrangement that coordinates applications, workloads, data, or processing across multiple environments, such as on-premises infrastructure and cloud services.
Kafka for Architects
A hybrid approach combines on-premises infrastructure with cloud-based services in one solution.
- How it is used
- Supports on-premises operational systems while making selected data available to cloud analytics and other services.
- How deep it goes
- Explains dual-cluster replication, replicator placement, lag, and cost trade-offs without providing configuration steps.
- Examples
- Uses a local-to-cloud replication diagram and a Customer 360 operational data store deployment decision.
- What you can do after
- Evaluate/understand whether dual-cluster replication fits latency, cost, operational, and compliance constraints.
Think Like a CTO
A cloud environment that combines private-cloud and public-cloud resources and allows workloads or capacity to span them.
- How it is used
- Positions hybrid deployment as a capacity strategy for organizations with substantial existing hardware.
- How deep it goes
- Defines the private–public combination and capacity augmentation, but does not provide deployment steps.
- Examples
- Illustrates public-cloud resources transparently covering a shortfall when private-cloud capacity is exhausted.
- What you can do after
- Evaluate/understand whether existing hardware, management resources, and capacity needs make a hybrid approach appropriate.
Architecting an Apache Iceberg Lakehouse
A hybrid cloud deployment combines infrastructure operated on premises with services or storage provided by public clouds.
- How it is used
- Connects regulated on-premises data with cloud-native analytics when scaling legacy infrastructure is difficult.
- How deep it goes
- Explains residency, storage interfaces, federation, and operational tradeoffs but stops short of detailed deployment configurations.
- Examples
- Uses regulated banking data, EU on-premises storage, cloud analytics, Trino federation, and archival tiering as concrete examples.
- What you can do after
- Apply it via Trino to query distributed on-premises and cloud data while preserving infrastructure and residency constraints.
Read how Architecting an Apache Iceberg Lakehouse explains hybrid deployment →
Google Anthos in Action
A hybrid cloud deployment operates a platform across a public cloud and one or more on-premises data centers.
- How it is used
- Deploys and operates a consistent application platform across Google Cloud and on-premises environments.
- How deep it goes
- Explains placement, connectivity, routing, and migration patterns, but does not detail complete production configuration procedures.
- Examples
- Uses Anthos across GCP and data centers, Dedicated Interconnect, and traffic splitting between on-premises and cloud services.
- What you can do after
- Configure and operate platform connectivity, routing, and migration across cloud and on-premises environments.
Read how Google Anthos in Action explains hybrid deployment →
Building Reliable AI Systems
A hybrid deployment architecture combines multiple deployment approaches or environments within one system.
- How it is used
- Balances model capability, cost, and control when deploying LLM services in production.
- How deep it goes
- Explains routing, fallback, and traffic adjustment, while identifying keyword matching as a simplification.
- Examples
- Routes short factual questions locally, nuanced or risky queries to hosted models, and failed or overloaded requests to API fallback.
- What you can do after
- Build a router that selects local or hosted models for queries and falls back when local models fail or are overloaded.
Read how Building Reliable AI Systems explains hybrid deployment →
Authorization in Action
A hybrid deployment combines locally running authorization evaluation with remotely managed policy or entity storage.
- How it is used
- Combines local authorization decisions with remotely managed policy and entity storage across on-premises and cloud deployments.
- How deep it goes
- Explains the architecture, synchronization model, benefits, tradeoffs, and deployment contrast without detailing synchronization implementation.
- Examples
- Uses ACME’s on-premises Customer Collaboration deployments, AWS-hosted SaaS instances, shared Cedar policy code, and synchronized updates.
- What you can do after
- Operate/configure local and managed authorization environments while preserving centralized policy management and low-latency evaluation.
Read how Authorization in Action explains hybrid deployment →
Microsoft Azure in Action
An architecture that combines on-premises infrastructure with Azure resources so workloads and data can operate across both environments.
- How it is used
- Combines on-premises services with Azure resources when an organization is not ready to move entirely to the cloud.
- How deep it goes
- Defines the deployment model and works through file synchronization, but stops short of broader hybrid network configuration.
- Examples
- Uses synchronized on-premises file servers, Azure file shares, File Sync agents, Entra Cloud Sync, and Azure backups.
- What you can do after
- Apply it via Azure File Sync to synchronize files, support cloud and local access, and reduce additional storage hardware.
Read how Microsoft Azure in Action explains hybrid deployment →
Related concepts
- cloud computingkind of · Cloud computing is the on-demand delivery of computing resources and services over a network from remotely managed infrastructure.
- cloud storageuses · Cloud storage is remotely managed storage delivered as a network-accessible service for persistently storing and retrieving data.
- self-hostinguses · Self-hosting is deploying and operating software or services on computing infrastructure controlled or managed by the user or organization.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.