{"id":870,"date":"2026-08-29T07:32:36","date_gmt":"2026-08-29T07:32:36","guid":{"rendered":"https:\/\/bestorthohospitals.com\/blog\/?p=870"},"modified":"2026-08-29T07:32:36","modified_gmt":"2026-08-29T07:32:36","slug":"multi-cloud-infrastructure-management-best-practices-architecture-and-tooling","status":"publish","type":"post","link":"https:\/\/bestorthohospitals.com\/blog\/multi-cloud-infrastructure-management-best-practices-architecture-and-tooling\/","title":{"rendered":"Multi-Cloud Infrastructure Management: Best Practices, Architecture, and Tooling"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

Introduction<\/h2>\n\n\n\n

Operating across multiple cloud providers has shifted from an ambitious edge-case strategy to an operational reality. Organizations routinely distribute workloads across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) to avoid vendor lock-in, meet localized compliance mandates, leverage proprietary cloud services, and increase system availability.To maintain reliability and speed, engineering organizations must move away from treating each cloud as a distinct operational silo. Modern teams require unified provisioning patterns, standardized observability, centralized policy enforcement, and consistent security controls. For teams scaling their operations across heterogeneous environments, implementing structured cloud operations<\/strong><\/a> frameworks is critical to maintaining visibility and governance.<\/p>\n\n\n\n

What is Multi-Cloud Infrastructure Management?<\/h2>\n\n\n\n

Multi-cloud infrastructure management is the practice of centrally provisioning, configuring, monitoring, securing, and maintaining IT infrastructure resources across two or more public or private cloud platforms.Unlike hybrid cloud operations\u2014which specifically bridge on-premises hardware with public cloud environments\u2014multi-cloud strategies focus on orchestrating infrastructure across multiple independent public cloud vendors.<\/p>\n\n\n\n

Core Objectives<\/h3>\n\n\n\n
    \n
  • Abstraction:<\/strong> Standardizing deployment paradigms so engineers do not need to rewrite workflow logic for individual vendors.<\/li>\n\n\n\n
  • Centralized Governance:<\/strong> Enforcing access control, compliance checks, and resource tagging consistently across all target clouds.<\/li>\n\n\n\n
  • Unified Observability:<\/strong> Aggregating metrics, traces, and logs into single-pane-of-glass platforms to establish enterprise-wide operational context.<\/li>\n\n\n\n
  • Cost Governance:<\/strong> Normalizing resource consumption data across providers to analyze and optimize cloud spend.<\/li>\n<\/ul>\n\n\n\n

    Engineering teams implement multi-cloud management frameworks to transform isolated cloud deployments into an integrated operational ecosystem.<\/p>\n\n\n\n

    How Does Multi-Cloud Infrastructure Management Work?<\/h2>\n\n\n\n

    Multi-cloud management operates by placing an orchestration, governance, and observability layer above vendor-specific APIs.<\/p>\n\n\n\n

                                   +-------------------------------------+\n                               |   Unified Management & Operations   |\n                               | (Terraform, OpenTelemetry, Vault)   |\n                               +------------------+------------------+\n                                                  |\n                     +----------------------------+----------------------------+\n                     |                            |                            |\n                     v                            v                            v\n        +-------------------------+  +-------------------------+  +-------------------------+\n        |       AWS Region        |  |      Azure Region       |  |       GCP Region        |\n        |  (VPC, EKS, IAM, S3)    |  | (VNet, AKS, Entra, Blob)|  |  (VPC, GKE, IAM, GCS)   |\n        +-------------------------+  +-------------------------+  +-------------------------+\n<\/code><\/pre>\n\n\n\n
      \n
    1. Abstraction and API Translation:<\/strong> Platform engineering teams construct Infrastructure as Code (IaC) modules using vendor-agnostic frameworks (e.g., HashiCorp Terraform or OpenTofu). These templates define baseline resources while standardizing input variables and output parameters.<\/li>\n\n\n\n
    2. Identity Federation:<\/strong> Identity Providers (IdP) integrate with AWS IAM, Azure Entra ID, and GCP IAM using OpenID Connect (OIDC) or SAML 2.0. This allows operators to authenticate using unified credentials rather than maintaining separate database accounts per platform.<\/li>\n\n\n\n
    3. Provisioning Pipeline Execution:<\/strong> Continuous Integration and Continuous Deployment (CI\/CD) pipelines execute infrastructure deployments using automated service principals, enforcing pre-flight policy evaluations (e.g., Open Policy Agent) before resources apply.<\/li>\n\n\n\n
    4. Telemetry Ingestion:<\/strong> Unified agents or native exporter pipelines collect logs, metrics, and trace streams, forwarding telemetry to a centralized observability layer.<\/li>\n<\/ol>\n\n\n\n
      Core Components of Multi-Cloud Infrastructure Management<\/h2>\n\n\n\n
      Maintaining operational control across cloud vendors requires standardizing core platform building blocks.<\/p>\n\n\n\n
      Infrastructure as Code (IaC)<\/h3>\n\n\n\n
      Declarative IaC provides the foundation for consistent multi-cloud environments. Using unified tooling allows platform engineers to maintain repeatable resource definitions, track state variations, and enforce module standards across providers.<\/p>\n\n\n\n
      Configuration Management<\/h3>\n\n\n\n
      Once virtual machines or containers are provisioned, configuration tools (e.g., Ansible, Salt Project) enforce base system configurations, package installations, and security hardening scripts across nodes regardless of hosting environment.<\/p>\n\n\n\n
      Unified Identity and Access Management (IAM)<\/h3>\n\n\n\n
      Relying on separate, local IAM users within each cloud provider scales poorly and creates access blind spots. Centralized authentication leveraging enterprise identity providers using short-lived tokens minimizes security risks across cloud boundaries.<\/p>\n\n\n\n
      Secrets Management<\/h3>\n\n\n\n
      Managing keys, certificates, and API tokens inside cloud-native key vaults creates operational silos. Standardizing on an external, cross-cloud secrets engine ensures applications fetch credentials securely without hardcoding cloud-specific SDKs.<\/p>\n\n\n\n
      Role of AWS, Azure, and GCP<\/h2>\n\n\n\n
      Each major public cloud provider handles architectural primitives differently. Managing a multi-cloud footprint requires understanding these technical distinctions.<\/p>\n\n\n\n
      Functional Area<\/strong><\/td>Amazon Web Services (AWS)<\/strong><\/td>Microsoft Azure<\/strong><\/td>Google Cloud Platform (GCP)<\/strong><\/td><\/tr><\/thead>
      Global Hierarchy<\/strong><\/td>Accounts organized under AWS Organizations OU structure<\/td>Subscriptions organized under Management Groups<\/td>Projects organized under Folders and Organization nodes<\/td><\/tr>
      Networking Scope<\/strong><\/td>Regional Virtual Private Clouds (VPCs)<\/td>Regional Virtual Networks (VNets)<\/td>Global VPCs spanning multiple regions natively<\/td><\/tr>
      Identity Core<\/strong><\/td>AWS IAM and IAM Identity Center<\/td>Azure Active Directory (Entra ID)<\/td>Google Cloud IAM linked to Google Workspace \/ Cloud Identity<\/td><\/tr>
      K8s Engine<\/strong><\/td>Elastic Kubernetes Service (EKS)<\/td>Azure Kubernetes Service (AKS)<\/td>Google Kubernetes Engine (GKE)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      Understanding these fundamental differences helps teams design control mechanisms that accommodate underlying vendor constraints while maintaining unified operating procedures.<\/p>\n\n\n\n
      Cloud Operations and Automation Considerations<\/h2>\n\n\n\n
      Effective multi-cloud infrastructure management<\/strong> relies on robust cloud infrastructure automation to replace manual provisioning with repeatable deployment pipelines.<\/p>\n\n\n\n
      Standardizing Provisioning with Terraform<\/h3>\n\n\n\n
      HashiCorp Terraform and OpenTofu allow teams to manage multi-cloud deployments via standard declarative HCL code. By modularizing infrastructure components, platform teams can expose simplified interfaces to application groups.<\/p>\n\n\n\n
      Terraform<\/p>\n\n\n\n
      # Example: Declarative pattern standardizing multi-cloud storage buckets\nmodule \"aws_storage\" {\n  source      = \".\/modules\/aws-s3\"\n  bucket_name = \"enterprise-data-aws-prod\"\n  environment = \"production\"\n}\n\nmodule \"gcp_storage\" {\n  source      = \".\/modules\/gcp-gcs\"\n  bucket_name = \"enterprise-data-gcp-prod\"\n  environment = \"production\"\n}\n<\/code><\/pre>\n\n\n\n
      Container Orchestration via Kubernetes<\/h3>\n\n\n\n
      Kubernetes serves as a critical abstraction layer for cloud management. By deploying applications to managed Kubernetes engines (EKS, AKS, GKE), operations teams decouple application runtime dependencies from provider-specific virtual machine primitives.<\/p>\n\n\n\n
      Monitoring, Observability, and Reliability<\/h2>\n\n\n\n
      Observability across multiple cloud platforms requires consolidating disparate telemetry streams into unified analytical pipelines.<\/p>\n\n\n\n
      +------------------+     +------------------+     +------------------+\n|   AWS CloudWatch |     | Azure Monitor    |     | GCP Cloud Logging|\n+--------+---------+     +--------+---------+     +--------+---------+\n         |                        |                        |\n         +------------------------+------------------------+\n                                  |\n                                  v\n                    +---------------------------+\n                    | OpenTelemetry Collector   |\n                    +-------------+-------------+\n                                  |\n                                  v\n                    +---------------------------+\n                    |  Central Observability    |\n                    | (Prometheus \/ Grafana \/   |\n                    | Datadog \/ New Relic)      |\n                    +---------------------------+\n<\/code><\/pre>\n\n\n\n
      Metrics, Logs, and Traces Standardization<\/h3>\n\n\n\n
      Relying solely on vendor-native tools (AWS CloudWatch, Azure Monitor, GCP Cloud Logging) forces engineers to context-switch across multiple interfaces during incident triage. Standardizing on open frameworks like OpenTelemetry enables applications to emit standardized traces and metrics directly to central analytical engines.<\/p>\n\n\n\n
      Service Level Objectives (SLOs) and Reliability<\/h3>\n\n\n\n
      Establishing cross-cloud Site Reliability Engineering (SRE) practices requires defining unified Service Level Indicators (SLIs) and Error Budgets. Instead of evaluating availability based on cloud-provider uptime SLA statements, operational teams measure end-to-end transaction latency and error rates across all involved platforms.<\/p>\n\n\n\n
      Security and Governance<\/h2>\n\n\n\n
      Operating multi-cloud environments expands the organizational attack surface, requiring standardized security controls across environments.<\/p>\n\n\n\n
        \n
      • Least Privilege Access:<\/strong> Implement short-lived credentials via IAM role assumption and OIDC federation to prevent static access keys from persisting within CI\/CD pipelines.<\/li>\n\n\n\n
      • Network Micro-segmentation:<\/strong> Establish unified overlay networks or mesh networks (e.g., via Cilium or HashiCorp Consul) to encrypt and control east-west traffic between clouds.<\/li>\n\n\n\n
      • Policy as Code Enforcement:<\/strong> Integrate static code analysis tools (e.g., OPA\/Rego, Checkov) into delivery pipelines to block non-compliant resource definitions prior to deployment.<\/li>\n\n\n\n
      • Unified Audit Logging:<\/strong> Route raw API access logs (AWS CloudTrail, Azure Activity Logs, GCP Audit Logs) to a centralized Security Information and Event Management (SIEM) system for centralized anomaly detection.<\/li>\n<\/ul>\n\n\n\n
        Best Practices<\/h2>\n\n\n\n
          \n
        1. Standardize Tagging and Resource Metadata:<\/strong> Enforce mandatory resource metadata (e.g., environment<\/code>, owner<\/code>, cost-center<\/code>) across all clouds using automated policy checks to maintain cost transparency and operational tracking.<\/li>\n\n\n\n
        2. Treat Infrastructure Exclusively as Code:<\/strong> Avoid manual configuration changes in cloud web consoles. Ensure every state change occurs through reviewed code repos and automated pipelines.<\/li>\n\n\n\n
        3. Establish a Centralized Platform Engineering Function:<\/strong> Build reusable internal developer portal modules so product engineering teams consume pre-approved infrastructure templates safely.<\/li>\n\n\n\n
        4. Implement Centralized Identity Federation:<\/strong> Integrate cloud IAM architectures with an enterprise Identity Provider (IdP) to centralize user lifecycle management and enforce MFA across platforms.<\/li>\n\n\n\n
        5. Decouple Applications from Proprietary Services:<\/strong> Where portability is required, favor open platforms (e.g., PostgreSQL, Kafka, Kubernetes) over cloud-exclusive databases or queue implementations to simplify workload migration.<\/li>\n\n\n\n
        6. Deploy Immutable Infrastructure Patterns:<\/strong> Build standard machine images using tools like Packer across cloud environments to maintain consistent base OS hardening and patching levels.<\/li>\n\n\n\n
        7. Automate Continuous Compliance Scanning:<\/strong> Continuously scan live cloud configurations against compliance frameworks (such as CIS Benchmarks) using central policy automation.<\/li>\n<\/ol>\n\n\n\n
          Common Mistakes<\/h2>\n\n\n\n
            \n
          • Treating Cloud Providers Identically:<\/strong> Expecting AWS, Azure, and GCP to handle networking, quota limits, and IAM identically leads to architectural anti-patterns and misconfigurations.<\/li>\n\n\n\n
          • Over-Architecting for Immediate Cloud Portability:<\/strong> Designing systems to dynamically shift workloads across clouds second-by-second introduces immense complexity. Focus on unified operations rather than seamless live workload migration.<\/li>\n\n\n\n
          • Maintaining Siloed Operational Teams:<\/strong> Organizing separate “AWS Teams” and “Azure Teams” breaks organizational alignment. Structure operations around unified discipline capabilities (e.g., Platform Engineering, Observability, SecOps).<\/li>\n\n\n\n
          • Neglecting Multi-Cloud Data Transfer Costs:<\/strong> Spanning workload architectures across multiple providers without accounting for egress charges leads to unexpected financial overhead.<\/li>\n\n\n\n
          • Relying on Cloud-Native Keys and Secrets Secrets Engines in Isolation:<\/strong> Managing secrets separately in AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager creates operational duplication and rotation errors.<\/li>\n<\/ul>\n\n\n\n
             Real-World Use Cases<\/h2>\n\n\n\n
            High Availability and Disaster Recovery (DR)<\/h3>\n\n\n\n
            Financial platforms often run primary workloads in one public cloud while maintaining warm standby instances or data backups in a secondary public cloud provider to satisfy regional regulatory resilience requirements.<\/p>\n\n\n\n
            Specialized Service Utilization<\/h3>\n\n\n\n
            Data engineering organizations frequently leverage AWS for core infrastructure workloads while streaming analytics payloads directly into GCP BigQuery to capitalize on specialized data analytics engines.<\/p>\n\n\n\n
            Geographic Footprint Expansion<\/h3>\n\n\n\n
            Enterprises expanding globally often leverage Azure for regions with strong local data residency offerings, while using AWS or GCP in other international markets to optimize network latency.<\/p>\n\n\n\n
            Challenges and Limitations<\/h2>\n\n\n\n
              \n
            • Increased Operational Complexity:<\/strong> Managing multiple control planes increases the operational load on platform engineering teams.<\/li>\n\n\n\n
            • Skill Set Fragmentation:<\/strong> Operations engineers must maintain proficiency across diverse API structures, CLI suites, and platform quirks.<\/li>\n\n\n\n
            • Tool Sprawl:<\/strong> Introducing disparate management, security, and monitoring utilities creates operational fragmentation across teams.<\/li>\n\n\n\n
            • Network Egress Costs:<\/strong> Transporting large volumes of data across cloud boundaries incurs significant network egress fees from cloud providers.<\/li>\n<\/ul>\n\n\n\n
              Step-by-Step Implementation Guide<\/h2>\n\n\n\n
              +------------------+     +------------------+     +------------------+     +------------------+\n| Step 1: Baseline | --> | Step 2: Unified  | --> | Step 3: Pipeline | --> | Step 4: Central  |\n| Identity & IAM   |     | Networking\/IaC   |     | & Policy As Code |     | Observability    |\n+------------------+     +------------------+     +------------------+     +------------------+\n<\/code><\/pre>\n\n\n\n
                \n
              1. Establish Identity Federation:<\/strong> Connect enterprise identity management (IdP) to AWS, Azure, and GCP to enforce centralized access control and SSO.<\/li>\n\n\n\n
              2. Design Standardized IP AM and Cloud Topology:<\/strong> Plan non-overlapping IP CIDR blocks across target cloud environments to enable secure inter-cloud networking without NAT collisions.<\/li>\n\n\n\n
              3. Build Core Infrastructure Modules:<\/strong> Create vetted, reusable IaC modules for standard infrastructure blueprints (VPCs, clusters, storage) across platforms.<\/li>\n\n\n\n
              4. Enforce Policy as Code:<\/strong> Configure automated guardrails in your deployment pipelines to reject non-compliant infrastructure definitions before runtime execution.<\/li>\n\n\n\n
              5. Standardize Agent-Based Observability:<\/strong> Deploy cross-cloud metric collectors and log shippers across all compute targets to centralize telemetry collection.<\/li>\n\n\n\n
              6. Implement Centralized Governance and FinOps:<\/strong> Connect cloud management tools to aggregate billing data, enforce budget alerts, and track resource compliance centrally.<\/li>\n<\/ol>\n\n\n\n
                Future Trends in Multi-Cloud Infrastructure Management<\/h2>\n\n\n\n
                The discipline of multi-cloud management continues to evolve alongside advances in platform engineering and automation paradigms:<\/p>\n\n\n\n
                  \n
                • Platform Engineering and Internal Developer Platforms (IDPs):<\/strong> Platform teams increasingly abstract multi-cloud complexity behind developer portals (such as Backstage), providing self-service interfaces that generate infrastructure templates automatically.<\/li>\n\n\n\n
                • Advanced Policy as Code Frameworks:<\/strong> Policy enforcement is moving earlier in the development lifecycle, shifting from post-deployment compliance checks to pre-commit static analysis.<\/li>\n\n\n\n
                • AIOps and Intelligent Anomaly Detection:<\/strong> Machine learning platforms are increasingly deployed to aggregate cross-cloud telemetry, helping teams identify cross-platform performance degradation and perform root-cause analysis efficiently.<\/li>\n<\/ul>\n\n\n\n
                  Frequently Asked Questions<\/h2>\n\n\n\n
                    \n
                  1. What is multi-cloud infrastructure management?<\/strong><\/li>\n<\/ol>\n\n\n\n
                    Multi-cloud infrastructure management is the practice of centrally provisioning, configuring, securing, and monitoring infrastructure resources across multiple public cloud providers using standardized tools and unified operational processes.<\/p>\n\n\n\n
                      \n
                    1. How does multi-cloud differ from hybrid cloud?<\/strong><\/li>\n<\/ol>\n\n\n\n
                      Hybrid cloud connects public cloud environments with on-premises data centers, whereas multi-cloud specifically refers to utilizing services across multiple independent public cloud vendors like AWS, Azure, and GCP.<\/p>\n\n\n\n
                        \n
                      1. Why do organizations adopt a multi-cloud infrastructure strategy?<\/strong><\/li>\n<\/ol>\n\n\n\n
                        Companies adopt multi-cloud strategies to mitigate vendor lock-in, satisfy stringent regulatory and data residency mandates, improve disaster recovery posture, and utilize best-of-breed specialized tools across cloud platforms.<\/p>\n\n\n\n
                          \n
                        1. What are the primary challenges of multi-cloud management?<\/strong><\/li>\n<\/ol>\n\n\n\n
                          The biggest challenges include managing operational complexity, skill shortages across multiple platforms, inconsistent IAM paradigms, security configuration drift, high data egress fees, and fragmented monitoring visibility.<\/p>\n\n\n\n
                            \n
                          1. Which tools are commonly used for multi-cloud infrastructure management?<\/strong><\/li>\n<\/ol>\n\n\n\n
                            Common open-source and commercial tools include HashiCorp Terraform and OpenTofu for IaC, HashiCorp Vault for secrets management, Kubernetes for container orchestration, and OpenTelemetry, Prometheus, and Grafana for centralized observability.<\/p>\n\n\n\n
                              \n
                            1. How does Kubernetes help with multi-cloud infrastructure management?<\/strong><\/li>\n<\/ol>\n\n\n\n
                              Kubernetes provides a consistent application runtime layer across different infrastructure providers. By standardizing continuous deployment primitives on managed Kubernetes engines (EKS, AKS, GKE), operations teams can manage applications using uniform workflows regardless of the underlying cloud hosting platform.<\/p>\n\n\n\n
                                \n
                              1. How do cloud egress costs impact multi-cloud architecture decisions?<\/strong><\/li>\n<\/ol>\n\n\n\n
                                Cloud providers charge network egress fees when data leaves their network. Transferring high volumes of data continuously between different cloud providers can rapidly drive up operational costs, requiring teams to design architectures that minimize cross-cloud data transfer.<\/p>\n\n\n\n
                                  \n
                                1. Can Infrastructure as Code fully abstract differences between AWS, Azure, and GCP?<\/strong><\/li>\n<\/ol>\n\n\n\n
                                  No. Tools like Terraform standardize deployment workflows and state tracking, but individual provider modules must still interact with vendor-specific API resource models. IaC simplifies the management paradigm, but it does not completely erase operational differences between underlying platform APIs.<\/p>\n\n\n\n
                                    \n
                                  1. How do teams enforce security across multi-cloud environments?<\/strong><\/li>\n<\/ol>\n\n\n\n
                                    Security teams enforce consistent security by federating identities through a single IdP, defining security policies as code, standardizing on cross-cloud secrets engines, and routing all platform access logs into a centralized SIEM for unified security monitoring.<\/p>\n\n\n\n
                                      \n
                                    1. What role does FinOps play in multi-cloud operations?<\/strong><\/li>\n<\/ol>\n\n\n\n
                                      FinOps establishes cost transparency across heterogeneous cloud footprints. It normalizes billing data from different cloud providers, enabling operations teams to analyze expenditures, enforce resource tagging standards, and optimize capacity allocation across cloud providers.<\/p>\n\n\n\n
                                      Conclusion<\/h2>\n\n\n\n
                                      Effective multi-cloud infrastructure management requires balancing programmatic standardization with a respect for the unique capabilities of each public cloud provider. By establishing centralized identity, automating infrastructure deployments through standard declarative frameworks, enforcing security guardrails early, and unifying operational telemetry, engineering organizations can scale multi-cloud footprints without incurring prohibitive operational friction. Success relies on building practical platform engineering abstractions that reduce complexity for developers while retaining robust control, reliability, and security for operations teams.<\/p>\n\n\n\n
                                      <\/p>\n","protected":false},"excerpt":{"rendered":"
                                      Introduction Operating across multiple cloud providers has shifted from an ambitious edge-case strategy to an operational reality. Organizations routinely distribute […]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[110,430,429,22,111],"class_list":["post-870","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-cloudcostoptimization","tag-cloudinfrastructure","tag-cloudops","tag-devops","tag-finops"],"_links":{"self":[{"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/posts\/870","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/comments?post=870"}],"version-history":[{"count":1,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/posts\/870\/revisions"}],"predecessor-version":[{"id":872,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/posts\/870\/revisions\/872"}],"wp:attachment":[{"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/media?parent=870"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/categories?post=870"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bestorthohospitals.com\/blog\/wp-json\/wp\/v2\/tags?post=870"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}