What is IT infrastructure orchestration?

Rather than managing individual components separately, orchestration creates automated self-service workflows that provision resources, deploy applications, configure networks and maintain systems according to predefined rules and policies. These workflows handle interdependent tasks, executing them in the correct sequence while handling dependencies and potential failures.

Modern enterprises run applications across hybrid and multicloud environments—from on-premises data centers to public clouds (for example, AWS, Microsoft Azure, IBM Cloud®, Google Cloud Platform), to edge locations. Without orchestration, IT teams face growing complexity in managing thousands of interdependent resources. As cloud platforms, microservices and containerized applications proliferate, managing and coordinating these systems becomes impossible.

Consider a financial services organization deploying a new mobile banking application. The process involves provisioning cloud infrastructure and configuring security policies. Teams must deploy services and apps, set up databases, establish network connections and implement monitoring systems. IT infrastructure orchestration automates these interdependent tasks, executing them in the correct sequence while handling dependencies and potential failures.

As more organizations face similar deployment challenges, orchestration has become essential. According to Coherent Market Insights, the global cloud orchestration market is expected to grow at a compound annual growth rate of 20.6% between 2025–2032, reaching USD 75.39 billion.¹ This reflects organizations’ increasing need for sophisticated orchestration capabilities to manage complex IT environments at scale.

While often used interchangeably, infrastructure automation and infrastructure orchestration represent distinct concepts with important differences.

Infrastructure automation focuses on eliminating manual work for individual tasks. For instance, an automated workflow might provision a virtual machine (VM), create a database backup or restart a failed service without human intervention. These automated tasks work independently, executing specific functions when triggered.

A 2023 IBM Institute for Business Value (IBV) study found that 92% of executives expected their workflows to be digitized and use AI-powered automation by 2025. These expectations require advanced orchestration capabilities to manage at scale.

Infrastructure orchestration takes it a step further, coordinating multiple automated tasks into cohesive workflows that achieve broader business objectives. The system manages the sequence, timing, dependencies and error handling across diverse automation tasks.

For example, deploying a three-tier web application (for example, an e-commerce platform) requires provisioning infrastructure and configuring load balancers. Teams must deploy application code, initialize databases and set up monitoring. Automation handles each task, while orchestration coordinates the entire workflow, ensuring tasks execute in the proper order and handling scenarios where individual steps fail.

Leading organizations combine both approaches. They use automation tools to handle repetitive tasks efficiently. Orchestration ensures these automated components work together toward strategic outcomes.

Infrastructure orchestration operates through intelligent workflow engines that coordinate resources, services and IT processes across distributed environments.

Cloud orchestration has become essential to modern IT operations, with specialized tools that coordinate cloud resources across multiple cloud platforms. They manage everything from virtual machines and containers (typically Docker) to serverless functions and managed services. Kubernetes has emerged as the de facto standard for container orchestration. It automates deployment, scaling, networking and lifecycle management for containerized applications.

Infrastructure orchestration platforms deliver several essential capabilities:

• Resource provisioning and management: Orchestration systems automatically allocate computing, storage and network resources based on application requirements and organizational policies. This capability eliminates manual provisioning tasks and ensures that resources remain available when needed.

• Configuration management: These platforms consistently apply configurations across all environments, ensuring that systems maintain their wanted states over time. Configuration management prevents the drift that occurs when systems gradually diverge from their intended specifications.

• Policy enforcement: Automated compliance checks, access control and governance controls are applied uniformly across all infrastructure components to identify and remediate vulnerabilities. Organizations can define policies once and then the orchestration platform enforces them consistently without manual intervention.

• Service discovery and networking: Orchestration platforms dynamically identify and connect distributed services as they scale up or down. Services can locate and communicate with each other automatically as the infrastructure scales and evolves.

• Health monitoring and self-healing: Continuous system health checks run automatically, with orchestration systems sending notifications and triggering remediation when issues are detected. Self-healing capabilities restore service availability without requiring manual troubleshooting.

• Version control and rollback: Configuration changes are tracked systematically, giving teams the ability to revert to previous states when problems occur. This versioning capability reduces risk when deploying infrastructure updates.

• Multi-environment management: Orchestration coordinates deployments across development, staging and production environments, enabling teams to promote changes through environments systematically while maintaining consistency in infrastructure management.

• Integration capabilities: Modern orchestration platforms connect seamlessly with existing tools through application programming interfaces (APIs), including monitoring systems, security platforms and ticketing systems. These integrations create unified workflows across the entire technology stack.

Organizations adopting infrastructure orchestration realize significant benefits:

• Heightened deployment speed

• Enhanced reliability and consistency

• Improved resource utilization

• Stronger compliance and governance

• Business agility

Orchestration reduces application deployment times from weeks to minutes by automating manual processes and eliminating coordination delays. Development teams ship features faster without waiting for infrastructure provisioning or configuration activities.

Automated workflows eliminate human error and ensure consistent configurations. Every deployment follows identical processes, producing predictable results across environments.

Orchestration platforms optimize resource allocation dynamically, scaling up services during peak demand and down during low-demand periods. This elasticity reduces overprovisioning and delivers infrastructure cost savings while maintaining performance.

Infrastructure orchestration ensures that security controls, compliance requirements and corporate standards apply consistently across all infrastructure components.

Organizations respond to market opportunities faster when infrastructure adapts quickly to changing requirements. Platform engineering teams can deliver business initiatives and new services to reach customers in days rather than months.

Infrastructure orchestration delivers value across numerous IT disciplines and operational scenarios:

• DevOps and continuous integration and continuous deployment (CI/CD): Orchestration platforms form the foundation of modern DevOps practices, automating the entire software development and delivery pipeline, from code changes through testing, staging and production deployment. It ensures consistent, repeatable processes that enable development teams to ship features multiple times daily rather than monthly, accelerating innovation cycles.

• Network management: Software-defined networking (SDN) relies on orchestration to provision networks dynamically, configure routing policies and manage security controls across distributed environments. Network orchestration enables organizations to treat network infrastructure as programmable resources rather than physical equipment requiring manual configuration.

• Artificial intelligence and machine learning (AI/ML) workloads: Training artificial intelligence (AI) and machine learning (ML) models requires significant computing resources. Orchestration automates the entire AI/ML lifecycle, including data pipeline management, model training infrastructure provisioning, version control and deployment of trained models into production environments.

• Security posture: Security orchestration, automation and response (SOAR) platforms coordinate security tools, automate threat detection and response (TDR) and ensure consistent application of security policies. When threats are detected, orchestration triggers investigation workflows, isolates affected systems and implements remediation automatically.

• Edge environments: Organizations deploying applications across distributed edge environments use orchestration to manage thousands of sites consistently. It ensures that applications, configurations and security policies deploy correctly to Internet of Things (IoT) devices and other edge locations regardless of network connectivity challenges.

• Disaster recovery (DR): Orchestration automates failover processes, data replication and recovery workflows. When outages occur, orchestrated disaster recovery (DR) plans are executed systematically, reducing recovery time objectives (RTO) from hours to minutes.

The orchestration landscape includes diverse platforms and automation solutions designed for specific use cases and environments. Selecting the right tools requires understanding organizational needs, existing infrastructure and strategic objectives.

Essential orchestration tools and platforms include:

• Kubernetes

• Terraform®

• Ansible®

• Red Hat® OpenShift®

Kubernetes serves as the dominant open source container orchestration platform for organizations building cloud-native applications. It automates deployment, scaling and management of containerized applications across clusters of machines.

Major cloud service providers like AWS, IBM Cloud, Microsoft Azure and Google Cloud offer managed Kubernetes services.

Terraform by HashiCorp® enables infrastructure as code (IaC) across multiple cloud providers and on-premises environments. Teams define infrastructure in declarative configuration files and templates that Terraform uses to provision and manage resources consistently.

Ansible provides agentless automation and orchestration for configuration management, application deployment and task automation. Its simple syntax and extensive module library make it accessible for teams new to orchestration.

Red Hat OpenShift combines Kubernetes with other enterprise features—including developer tools, security capabilities and multi-cluster management—simplifying containerized applications at scale across hybrid cloud environments. The platform offers consistent operations across on-premises infrastructure and major public cloud platforms, such as IBM Cloud.

Organizations should evaluate platforms against several key criteria. Start by assessing compatibility with existing infrastructure and applications. Does the platform support current technologies and streamline integration with existing tools?

Also, consider the learning curve. Can internal teams acquire the necessary skills efficiently or do they already have relevant experience?

Scalability requirements matter significantly. The right platform must handle current workloads while accommodating future growth. Look at the vendor ecosystem and community support, as well. Robust communities provide valuable troubleshooting resources and accelerate problem resolution when challenges arise.

Security and compliance capabilities require careful evaluation, particularly for regulated industries. Furthermore, the total cost of ownership extends beyond licensing to include training, implementation and ongoing management expenses.

Many organizations find success by adopting multiple orchestration tools rather than seeking a single platform. This approach allows them to use specialized tools for specific workloads while maintaining integration between them.

Infrastructure orchestration continues evolving rapidly as enterprises move from AI experimentation to scaled production deployments. Several key trends are defining the next generation of orchestration capabilities:

• AI-driven orchestration

• Advanced observability

• Serverless and event-driven architectures

Organizations are shifting beyond traditional automation to intelligent systems that act autonomously while maintaining governance and observability. AI orchestration platforms coordinate AI agents, generative AI models and tools across enterprise environments, enabling them to work together while enforcing policy controls.

Machine learning is also transforming orchestration from reactive, rule-based systems to proactive platforms that predict and prevent issues before they occur, analyzing infrastructure patterns and anticipating resource requirements ahead of demand spikes.

Modern orchestration platforms incorporate advanced telemetry, distributed tracing and real-time analytics. This cloud-based observability provides visibility into how orchestrated systems perform and interact, enabling faster troubleshooting and more intelligent automation decisions.

Serverless computing and function-as-a-service (FaaS) require orchestration that extends beyond traditional infrastructure. These platforms coordinate ephemeral, event-driven workloads, managing applications composed of loosely coupled functions that execute on demand while handling automatic scaling and event routing.