Free Practice Questions for the UiPath Certified Professional - Infrastructure Engineer UiPath-IEPASv1 Exam (2026 Updated)

When executing an in-place upgrade on an Automation Suite cluster on Linux, the upgrade workflow separates the infrastructure layer from the application service layer. Upgrading the underlying Kubernetes distribution (RKE2), container runtime, and foundational infrastructure charts requires executing `./bin/uipathctl rke2 upgrade cluster_config.json --versions versions/helm-charts.json`. This command uses the target version definitions specified in `versions/helm-charts.json` and evaluates the existing parameters inside `cluster_config.json` to sequentially update the control plane, cordoning and draining nodes in a rolling fashion to preserve control-plane quorum. Legacy script parameters (such as `install-uipath.sh --upgrade` or `configureUiPathAS.sh`) were deprecated in favor of modern `uipathctl` subcommands, which orchestrate both infrastructure engine rollouts and Helm management. Once the infrastructure upgrade completes successfully, platform engineers proceed with upgrading the core application services. (Reference: UiPath Automation Suite Upgrade Procedures – Infrastructure and Kubernetes Upgrade Lifecycle).

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UiPath Automation Suite on Linux explicitly supports both AMD and Intel 64-bit processors, provided the systems meet core architecture and clock speed requirements. The containerized software suite is compiled for x86_64/AMD64 instruction set architectures. Both enterprise Intel Xeon and AMD EPYC families provide the microarchitecture capabilities, hardware virtualization features, and vector instruction support required to execute Automation Suite container workloads. ARM-based processor platforms, including AWS Graviton, Ampere Altra, and Apple Silicon, are strictly unsupported due to underlying architectural incompatibilities with compiled product binaries and container base layers. When deploying across virtual machines or physical hosts, engineers must verify that CPU features are exposed transparently by the hypervisor and that minimum aggregate cluster compute thresholds (e.g., 96 cores across multi-node production clusters) are met across Intel or AMD hardware pools. (Reference: UiPath Automation Suite Infrastructure Requirements – CPU Architecture Support).

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When executing the Automation Suite installer scripts on Linux platforms, the `-k` flag executes the built-in pre-installation validation check. This validation routine scrutinizes the host environment against foundational Linux prerequisites, checking for mandatory operating system packages (e.g., `lvm2`, `tar`, `curl`), kernel modules, sysctl network settings (such as `net.bridge.bridge-nf-call-iptables`), and disabled swap memory. It also verifies CPU and memory resource baselines, validates mount points, and ensures that firewall configurations permit intra-cluster communication across essential ports. By passing the `-k` parameter prior to committing cluster mutations, infrastructure architects proactively catch prerequisite gaps that would otherwise cause partial installation failures deep within RKE2 or container runtime provisioning. Passing the prerequisite check validates the underlying Linux host as certified and compliant with UiPath infrastructure requirements. (Reference: UiPath Automation Suite Installation Reference – CLI Flags and Host Pre-Requisites).

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Within the UiPath Automation Suite architecture, a server node is defined as a host that provides the Kubernetes control plane services responsible for cluster management and core operational functions. These essential services include cluster state management via the distributed etcd datastore, API request validation through the `kube-apiserver`, workload scheduling via `kube-scheduler`, controller reconciliation loops via `kube-controller-manager`, and request distribution to platform microservices. In environments where compute resources permit, server nodes may also host certain UiPath product pods and shared platform components; however, this capacity sharing does not alter their primary architectural definition. Server nodes are distinguished from agent nodes (which focus on running business products) and specialized agent nodes (which are isolated for GPU workloads and Automation Suite Robots). Preserving the performance and quorum of server nodes is vital for platform reliability. (Reference: UiPath Automation Suite Architecture Overview – Server Node Capabilities and Responsibilities).

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For offline and air-gapped Automation Suite installations, an internal temporary Docker/OCI registry is used to host container layers and Helm charts during cluster bootstrapping. Because container bundles for the platform require hundreds of gigabytes of disk storage, UiPath recommends placing this additional storage capacity under the `/uipath` mount point. By default, the temporary registry data path is configured as `/uipath/data/registry`. The `/uipath` mount is provisioned over a dedicated, high-capacity, high-performance volume, ensuring that unpacking large container images does not exhaust the root partition (`/`) or system logging directories (`/var`). Placing heavy image data on generic partitions can lead to operating system instability and node failures during setup. (Reference: UiPath Automation Suite Offline Installation Guide – Disk Partitioning and Temporary Registry Storage).

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When deploying UiPath Automation Suite across multi-zone or multi-region topologies utilizing independent regional load balancers, Azure Traffic Manager (or AWS Route 53) provides global DNS-based traffic routing. Azure Traffic Manager operates at the DNS transport layer, evaluating endpoint health and directing client connections to specific load balancer IP addresses based on configured routing methods. Supported algorithms include priority routing for active-passive failover, weighted round-robin for distributing loads proportionally, and geographic routing for latency optimization. The other listed tools serve distinct operational functions: FluentD aggregates cluster logs, ArgoCD automates declarative GitOps platform deployments, and Prometheus collects time-series monitoring metrics. Traffic Manager provides DNS-level endpoint health checking and routing algorithms for multi-load balancer architectures. (Reference: UiPath Automation Suite Cloud Architecture Guide – Multi-Zone DNS and Traffic Management).

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To enable an Automation Suite cluster to pull container images from an external OCI-compliant container registry, the configuration must declare the network endpoint: the Fully Qualified Domain Name (FQDN) or IP address of the registry server. During cluster bootstrapping and subsequent pod provisioning, the containerd runtime and Kubernetes image pull secrets resolve this FQDN or IP over HTTPS (or HTTP via insecure registry flags) to authenticate and pull container layers. Infrastructure details such as CPU core counts, datacenter locations, or backend storage vendors are abstracted by the registry's OCI API and are irrelevant to client connection configurations. Supplying a valid, network-accessible FQDN or IP address—along with required authentication credentials and CA trust chains—ensures nodes can download container images during installation and pod scheduling. (Reference: UiPath Automation Suite Pre-requisites – OCI Registry Connection Parameters).

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When configuring an external S3-compatible or Azure Blob object store for UiPath Automation Suite, setting up an accurate Cross-Origin Resource Sharing (CORS) policy is mandatory to facilitate secure, direct browser-to-storage and service-to-storage communication. The documented CORS configuration explicitly requires the AllowedMethods parameters to include `GET`, `POST`, `DELETE`, `HEAD`, and `PUT`. These methods correspond directly to essential storage actions executed across the suite's microservices. Specifically, `PUT` and `POST` enable direct multi-part uploads of large automation packages, execution media, and Document Understanding datasets; `GET` enables retrieval of packages and artifacts; `HEAD` allows the service endpoints to verify object presence and metadata headers without downloading payloads; and `DELETE` permits lifecycle cleanup routines to remove deprecated artifacts. Excluding any of these five methods—most notably `PUT` or `HEAD`—results in HTTP 403 Forbidden errors during execution artifact publishing or client downloads in products such as Orchestrator, AI Center, and Data Service. (Reference: UiPath Automation Suite Infrastructure Pre-requisites – Object Store Configuration and CORS Policy Rules).

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Automation Suite integrates GitOps methodologies (powered by ArgoCD) to automate the deployment, synchronization, and lifecycle management of platform microservices using Git repositories as the source of truth. When utilizing private repositories to protect proprietary configurations and sensitive parameters, the GitOps engine must authenticate to the remote repository. This requires configuring valid access credentials within the GitOps tool, typically using private SSH deploy keys, personal access tokens (PAT), or HTTPS credentials. These credentials allow ArgoCD to clone repositories, read Helm charts, detect branch drift, and apply configurations automatically. Exposing internal company configurations by making repositories public or attempting to co-locate Git servers on cluster nodes violates enterprise security standards. (Reference: UiPath Automation Suite GitOps Deployment Guide – ArgoCD Private Repository Access).

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Federal Information Processing Standard (FIPS) 140-2 is a U.S. government computer security standard governing cryptographic modules. Within UiPath Automation Suite, host machines operating with FIPS 140-2 mode enabled are not supported for the UiPath Insights service. Insights utilizes third-party analytics and data visualization runtimes whose cryptographic algorithms and hashing libraries are not certified under or compatible with the strict kernel-level enforcement of FIPS 140-2. When Automation Suite is installed in a FIPS-compliant Linux host environment, the Insights service must be disabled in `input.json` or `cluster_config.json`. Attempting to run Insights with FIPS enabled results in container initialization crashes and service startup failures due to non-compliant cryptographic calls. Organizations requiring FIPS compliance must either exclude Insights from their deployment scope or run Insights in an isolated, non-FIPS environment. (Reference: UiPath Automation Suite Security and Compliance Guide – FIPS 140-2 Compatibility Matrix).

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Restoring an online UiPath Automation Suite cluster from a backup after a disaster recovery event requires a minimal, valid `cluster_config.json` manifest. The recovery process requires the following specific components in the configuration file: `fixed_rke_addess` (or `fixed_rke_address`), `fqdn`, `rke_token`, `profile`, `external_object_storage`, and `install_type`. Each parameter supports a specific aspect of cluster reconstruction: `fixed_rke_address` establishes the primary control-plane endpoint, `fqdn` defines the platform domain, `rke_token` supplies the node join security secret, `profile` designates the sizing tier, `external_object_storage` connects to persistent buckets, and `install_type` specifies an online deployment. Omitting any of these key-value pairs or using invalid property names will cause the restoration toolchain to fail during initial manifest validation. (Reference: UiPath Automation Suite Disaster Recovery Guide – Cluster Restore Configuration Parameters).

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In an enterprise production deployment of UiPath Automation Suite, data availability and durability take precedence over cost-reduction measures. A critical architectural consideration is ensuring that the underlying persistent storage solution offers built-in hardware and software redundancy and fault tolerance. Automation Suite relies heavily on stateful storage for SQL transactional logs, etcd consensus quorum state, distributed application volumes (via Longhorn or CSI drivers), and external object storage buckets. Production environments must utilize storage layers designed with enterprise RAID arrays, multi-zone volume replication, synchronous mirroring, and automated snapshot capabilities. Relying on ephemeral disks or non-redundant local disks introduces catastrophic single points of failure: a single hypervisor or physical disk crash would lead to unrecoverable cluster state divergence and data corruption. Resilient, fault-tolerant storage architectures ensure sustained service continuity during node or rack failures. (Reference: UiPath Automation Suite Infrastructure Design – High Availability Storage Considerations).

During Automation Suite installation on bare-metal or virtualized Linux machines, storage provisioning is handled via automated scripting utilities. The specific command `./bin/uipathctl rke2 disk` prepares, formats, and mounts the dedicated disk partitions and logical volumes mandated by UiPath's storage layout. Automation Suite enforces a strict multi-disk architecture separating the root operating system, cluster runtime binaries, etcd datastore, and persistent application data into distinct volumes formatted with supported file systems (ext4 or xfs). The `uipathctl rke2 disk` command automates creating physical volumes, volume groups, and logical volumes via LVM, formats them with required parameters, mounts them to their target mount paths (such as `/var/lib/rancher/rke2` and `/uipath`), and records them in `/etc/fstab`. Executing this command ensures reliable disk layout without the human error inherent in manual partitioning. (Reference: UiPath Automation Suite Linux Deployment Guide – Storage and Disk Automation).

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When preparing block storage and disk partitioning for an Automation Suite installation on enterprise Linux distributions (such as RHEL or Rocky Linux), UiPath mandates formatting the underlying storage devices with either ext4 or xfs file systems. The automated storage initialization tools, including the script `./configureUiPathDisks.sh` and the command `./bin/uipathctl rke2 disk`, partition raw devices via Logical Volume Manager (LVM) and format mount points using xfs or ext4. These POSIX-compliant file systems supply the essential performance characteristics, file-locking semantics, atomic read/write behaviors, and extended attributes required by container runtimes (containerd), RKE2 control plane services, etcd transactional logs, and the shared local storage provisioner (Longhorn or Ceph). Alternative file systems such as Btrfs, ZFS, or non-Linux file systems like NTFS and ReFS are completely unsupported due to container overlay storage driver incompatibilities and unpredictable write amplification during database and logging operations. Proper configuration of `/etc/fstab` with either ext4 or xfs ensures volume stability across system reboots. (Reference: UiPath Automation Suite Infrastructure Pre-requisites – Disk Configuration and Filesystem Requirements).

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UiPath Automation Suite architecture formally classifies nodes within the underlying Kubernetes cluster into three distinct operational profiles: Server nodes, Agent nodes, and Specialized agent nodes. Server nodes host the Kubernetes control plane services (such as etcd, the kube-apiserver, and the scheduler) and orchestrate state management and request distribution. Agent nodes (general worker nodes) run standard UiPath product microservices—including Orchestrator, Identity Server, and Data Service—alongside core platform-shared services like RabbitMQ and Redis. Specialized agent nodes are dedicated worker nodes tailored with specific hardware acceleration or isolated resource profiles, such as GPU-enabled nodes dedicated to high-throughput Document Understanding and Computer Vision model pipelines, or nodes isolated via taints and tolerations to host Automation Suite Robots and Task Mining analysis engines. Categorizing workers into standard and specialized agent nodes prevents resource starvation across foundational business workflows. (Reference: UiPath Automation Suite Architecture Overview – Node Roles and Workload Scheduling).

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UiPath Automation Suite supports adding both server and agent nodes post-installation to scale compute and memory capacity across either single-node evaluation or multi-node production deployment profiles. However, adding nodes to a single-node evaluation cluster does not convert it into a multi-node High Availability (HA)-ready production deployment. Converting a single-node environment into a certified HA-ready setup requires specific architectural changes: migrating in-cluster databases to external SQL instances, configuring external object stores, provisioning a zone-redundant load balancer, deploying an odd number of server nodes (minimum three) to establish etcd quorum, and reconfiguring storage replication. Adding nodes to a single-node cluster merely provides additional compute capacity for specialized workloads (such as attaching a GPU agent node) while leaving the single control plane as a single point of failure. (Reference: UiPath Automation Suite Administration – Cluster Scaling and Node Addition Constraints).

In an enterprise Automation Suite deployment implementing modern Document Understanding projects without CPU fallback inference, UiPath hardware sizing standards require a minimum of five (5) dedicated GPU-enabled agent servers (or GPU allocations). Modern Document Understanding utilizes separate concurrent neural network pipelines to process unstructured business documents, invoices, and receipts. These five dedicated GPU instances are allocated across four functional roles: OCR processing pipelines, custom model training tasks, custom model inference pipelines, and out-of-the-box (OOTB) pre-trained model inference engines. Sharing a smaller number of GPUs across these distinct operations leads to GPU memory exhaustion (CUDA out-of-memory errors) and inference job queuing. Dedicating five GPU-enabled servers ensures each pipeline has the compute throughput required to sustain real-time document processing and training cycles. (Reference: UiPath Automation Suite Sizing Guide – Modern Document Understanding GPU Sizing).

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In an air-gapped or offline deployment scenario where cluster nodes lack outbound internet connectivity to public registries and UiPath repositories, a temporary Docker/OCI-compliant registry is provisioned to serve as the local distribution point for all deployment artifacts. Offline installation bundles (shipped as massive compressed tar archives) contain hundreds of microservice container images, foundational infrastructure binaries, and deployment Helm charts required across the entire platform lifecycle. During the initialization phase, the installer script hydrates this temporary registry with these assets. During cluster bring-up, RKE2 nodes and the local Helm engine pull required container layers and chart configurations directly from this endpoint over port 30070 or internal ingress ports without touching external endpoints. Once the permanent local container registry or in-cluster registry infrastructure is established and cluster services stabilize, the temporary registry can be decommissioned or repurposed. This staging mechanism guarantees reproducible, hermetic deployments in secured operational environments. (Reference: UiPath Automation Suite Offline Installation Guide – Registry Architecture).

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In UiPath Automation Suite, the single-node deployment profile is architected specifically for evaluation, Proof-of-Concept (PoC), testing, and demonstration scenarios. In a single-node configuration, all Kubernetes control-plane components and enabled platform application services reside on a single server machine. Consequently, this model offers zero fault tolerance or high availability: a single operating system failure, hardware disruption, or hypervisor outage brings down the entire platform. UiPath explicitly mandates multi-node deployments (consisting of at least three server nodes to maintain etcd consensus) for high-availability production workloads. Production use of single-node deployments is restricted to specific constrained profiles and lacks the resilience needed for mission-critical operations. The single-node profile allows infrastructure engineers to validate integrations and explore product features with minimal hardware investment. (Reference: UiPath Automation Suite Architecture Overview – Deployment Profiles).

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Configuring an Active/Passive multi-site disaster recovery deployment of UiPath Automation Suite requires two separate High Availability Add-on (HAA / Redis Enterprise) licenses: one for each participating cluster. In an Active/Passive topology, both the primary production cluster and the standby secondary cluster run independent instances of the Redis High Availability Add-on to provide session caching, state replication, and message brokering. Because each cluster operates as an independent Kubernetes deployment with its own control plane and network boundary, an independent license must be activated on each site. UiPath technical specifications dictate that each cluster must be licensed for a minimum of two shards. Attempting to share a single HAA license across clusters or omitting licensing on the standby site prevents cluster synchronization and breaks failover readiness. (Reference: UiPath Automation Suite Disaster Recovery Architecture – HAA Redis Licensing Model).

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In an offline or air-gapped environment, the Automation Suite cluster cannot contact public clouds, external certificate authorities, or remote services. To maintain operational parity, high availability, and end-to-end security, the cluster relies on an internal service mesh (powered by Istio) configured alongside a locally hosted Certificate Authority (CA). This internal architecture handles mutual TLS (mTLS), internal routing, service discovery, and traffic management between microservices without external dependencies. Online deployments often rely on external trust anchors or cloud-native providers, whereas an air-gapped cluster must manage internal certificate issuance and trust stores locally. Without an internalized service mesh and local CA, inter-service authentication fails in an isolated network. (Reference: UiPath Automation Suite Security Architecture – Offline Service Mesh and CA Configuration).

Deploying UiPath Automation Suite on managed Kubernetes distributions (AKS, EKS, or Red Hat OpenShift) requires configuring external platform prerequisites, including relational databases in Microsoft SQL Server and container buckets in external object storage. The automated command utilized to generate these requisite external configurations and resources is uipathctl prereq create. When executed with the deployment manifest (uipathctl prereq create input.json --versions versions.json), the command checks the flags enabled in input.json and automatically provisions the required SQL databases and object-storage buckets. Conversely, uipathctl prereq run is strictly a read-only validation check that confirms prerequisites without provisioning them. The prereq create subcommand standardizes the preparation of the external infrastructure tier. (Reference: UiPath Automation Suite on Managed Kubernetes – Automated Prerequisite Provisioning).

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When deploying UiPath Automation Suite on Linux utilizing built-in in-cluster persistent storage (Longhorn/Ceph) rather than an external enterprise SAN or cloud-managed block store, maximizing resilience against data loss is achieved using an all-server-node deployment configuration. In an in-cluster storage architecture, persistent volumes are replicated across the underlying cluster nodes to ensure data durability. When all nodes are designated as server nodes, every node participates in both control-plane consensus and storage volume replication. This symmetric architecture allows volume replicas to remain distributed across all machines. If a node fails, the surviving server nodes retain storage replicas and continue servicing I/O operations without breaking control-plane quorum. In contrast, in mixed configurations, agent node failures can compromise storage replicas without providing the redundancy benefits of an all-server topology. (Reference: UiPath Automation Suite Storage Architecture – In-Cluster Storage Resilience Guidelines).

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UiPath Automation Suite categorizes hardware and storage baseline requirements based on product selection profiles: Basic (or Minimal) vs. Complete. When deploying the "Complete" product selection—which encompasses data-heavy services such as Process Mining, Task Mining, AI Center, and Document Understanding alongside core platform components—the required data disk capacity on server nodes is a minimum of a 2 TiB (or 2 TB) SSD with a sustained performance profile of at least 1100 IOPS. This requirement applies to both single-node evaluation and multi-node HA-ready production profiles. The 512 GiB SSD disk size is only permitted for a restricted "Basic" profile deployment containing minimal services (such as standalone Orchestrator, Action Center, and Identity Server). Provisioning less than 2 TB for a complete installation leads to disk exhaustion and cluster failure as services generate persistent state. (Reference: UiPath Automation Suite Sizing Guide – Complete Product Selection Storage Requirements).

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When consolidating multiple, isolated Automation Suite environments (e.g., Development, Staging, or multiple business units) within a shared Red Hat OpenShift cluster, tenant isolation and state boundary integrity are enforced at the namespace level. UiPath microservices depend on Redis for distributed caching, user session state storage, and transient queuing across services like Orchestrator and Identity Server. In a multi-instance scenario on a single cluster, engineers must install an independent Redis instance within each corresponding Automation Suite namespace and subsequently update the respective `input.json` deployment file with the distinct Redis host connection strings. Sharing a single, centralized Redis deployment across multiple distinct Automation Suite namespaces is unsupported because cache key collisions, session cross-talk, and unified cache flushes would compromise tenant data separation and operational availability. Namespace-isolated Redis deployments maintain predictable caching latencies and adhere to OpenShift security context constraints. (Reference: UiPath Automation Suite on OpenShift – Multi-Tenancy and Shared Cluster Topologies).

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When executing a full platform restore from an infrastructure snapshot on a cluster where AI Center is not enabled, administrators must complete specific post-restoration procedures to re-establish platform integrity. The documented workflow comprises three mandatory operational steps: recovering the `cluster_config.json` configuration file, re-adding internal Certificate Authority (CA) certificates to the host operating system trust stores across all restored virtual machines, and retrieving the regenerated monitoring stack password for Prometheus and Grafana access. Recovering `cluster_config.json` restores cluster metadata and operational flags, while re-importing the CA certificates into the operating system certificate store prevents SSL/TLS handshake failures during intra-cluster and container communication. Because Dex credentials rotate or reset during snapshot restores, retrieving the new monitoring password restores administrative visibility into system metrics. Clusters with AI Center enabled require an additional specialized pipeline restoration step. (Reference: UiPath Automation Suite Backup and Restore Guide – Post-Restoration Configuration).

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Before committing cluster changes, applying manifests, or initiating software installation on managed Kubernetes platforms, platform engineers must validate that all external systems and infrastructure baselines are prepared. The documented command used to validate prerequisites against the declared configurations in `input.json` is `uipathctl prereq run input.json --versions versions.json`. Executing this command triggers validation routines that test network reachability, verify SQL Server connection strings and collation settings, confirm database permissions, test read/write capabilities against object storage buckets, and check Kubernetes cluster compute allocations. While `uipathctl prereq create` provisions missing databases and buckets, `prereq run` operates as an evaluation check to verify that all environmental dependencies meet requirements prior to deployment. Passing the `prereq run` check helps prevent partial cluster failures during subsequent manifest rollouts. (Reference: UiPath Automation Suite on Managed Kubernetes – Prerequisite Validation).

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In a multi-site disaster recovery deployment of UiPath Automation Suite (whether Active/Passive or Active/Active), the two clusters are administered completely independently. There is no shared global Kubernetes control plane or cross-cluster configuration manifest linking the environments. Each cluster maintains its own dedicated control-plane infrastructure, etcd consensus datastore, ArgoCD instance, and local service configuration. Operational lifecycle tasks—such as platform maintenance, configuration changes, certificate rotations, monitoring, troubleshooting, and version upgrades—must be executed separately on each distinct cluster. Only the underlying stateful data tiers (external Microsoft SQL Server databases via Always On Availability Groups, external object stores via cross-region replication, and distributed Redis caches via High Availability Add-on replication) are synchronized across the sites. Treating the clusters as independent operational entities ensures that an administrative failure, corrupted manifest, or control-plane crash in the primary site does not propagate to the secondary site, preserving disaster recovery readiness. (Reference: UiPath Automation Suite High Availability and Disaster Recovery – Multi-Site Administration).

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The core architectural distinction between online and offline UiPath Automation Suite deployments centers on network perimeter connectivity and the mechanism used for artifact distribution. An online installation requires nodes to have outbound internet connectivity (directly or through an enterprise forward proxy) to dynamically download container images, OS packages, and Helm charts directly from UiPath cloud registries and official package repositories during deployment. Conversely, an offline (air-gapped) installation operates in isolated network environments without internet access. In this mode, deployment media must be staged manually: installation bundles are downloaded on an external internet-connected machine, transferred via secure jump-hosts, and hydrated into a local, in-cluster, or customer-managed OCI-compliant container registry. While both deployment types support identical product features and require similar hardware profiles, offline architectures require additional operational planning for package mirroring, local certificate authorities, and offline bundle synchronization. (Reference: UiPath Automation Suite Deployment Methods – Online vs. Offline Architectural Models).

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UiPath Computer Vision is a deep-learning-based capability that analyses graphical user interfaces (GUIs) across virtual desktops, Citrix, and remote terminal sessions where standard UI element selectors are unavailable. Because the underlying neural network models demand high parallel-compute processing throughput to execute real-time image segmentation and OCR inference, installing Computer Vision within Automation Suite requires a dedicated agent node provisioned with specialized GPU support. UiPath requires NVIDIA GPUs (such as Tesla T4, A10, or newer enterprise Ampere architectures) equipped with the official NVIDIA container toolkit and drivers installed at the host operating system level. To prevent standard product pods or control-plane services from exhausting GPU memory, this node is tainted so that only Computer Vision and specialized AI workloads tolerate and schedule onto it. Attempting to run Computer Vision purely on generic CPU-bound agent nodes is unsupported due to severe inference latency and pod scheduling constraints. (Reference: UiPath Automation Suite Sizing and Hardware Requirements – Specialized GPU Nodes).

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When configuring scheduled snapshot backups on an Automation Suite cluster on Linux, UiPath utilizes an external Network File System (NFS) share as the primary target repository for persistent volume snapshots and platform state files. A mandatory architectural prerequisite for this backup mechanism is that the external NFS server must be network-reachable from all cluster nodes (both server and agent nodes). Because container workloads and backup agents (e.g., Velero or local snapshot daemon pods) run distributed across any node within the Kubernetes cluster, every single node must be able to mount the NFS target storage. If firewall barriers, routing policies, or subnets restrict access to only a subset of nodes, snapshot operations will fail intermittently depending on which node hosts the backup pod. The NFS server should be provisioned outside the cluster to ensure backup persistence in the event of total cluster hardware loss. (Reference: UiPath Automation Suite Backup and Disaster Recovery – Backup Storage Prerequisites).

UiPath Process Mining utilizes a dedicated analytical data store known as the Process Mining Warehouse (`AutomationSuite_ProcessMining_Warehouse`) to process business process logs and transformation models. When configuring external Microsoft SQL Server connectivity for this warehouse database, UiPath specifies standard TCP port 1433 in connection strings and firewall configurations. Port 1433 is the default TCP listening port for Microsoft SQL Server Database Engine instances. Infrastructure engineers must ensure that network firewalls, subnets, and host-level security groups permit bi-directional communication between Automation Suite worker nodes and the SQL database host over TCP port 1433. Blocking or misconfiguring this port prevents Process Mining data transformation jobs from executing and generates connection timeout errors within the warehouse ETL pipelines. (Reference: UiPath Automation Suite Database Configuration – Process Mining Warehouse Specifications).