Everyone needs software configuration management in an infrastructure-as-code world. Source control systems have been part of the configuration management conversation for decades for application development. Now, they increasingly support infrastructure teams as well, as infrastructure as code should also be under source control. Collaboration platforms like Atlassian Bitbucket, GitHub, and GitLab have grown rapidly, providing a new center of gravity for digital professionals.

New workloads are in a constant state of flux — creation, decommissioning, and frequent change — for cloud infrastructure services’ hypervisors, storage, containers, and SaaS solutions. Configuration changes present significant challenges: Untested or overly permissive compute, storage, and network configurations expose data to hackers and threaten service availability and operational continuity. Zero Trust in the cloud is unimaginable without configuration management.

Agentic AI promises to change this dramatically. Agents can scan unstructured documentation, extract structured data, and review repository data for quality and completeness, surfacing key issues for human or AI intervention. EA tools like SAP LeanIX and ServiceNow Enterprise Architecture increasingly integrate directly with configuration management databases (CMDBs) to expand into IT service management (ITSM), IT financial management (ITFM), collaborative work management, AIOps, and more.

BMC TrueSight provides strong capabilities in server and network provisioning, patch management, and integration with monitoring tools. It focuses on maintaining support for legacy infrastructure, and TrueSight thus does not support the new infrastructure constructs like containers. This limits the scope of TrueSight to traditional and legacy infrastructure. Other weaknesses include community ecosystem and engagement, dashboarding, and configuration management. Customer feedback.

Other key measures are incident response efficacy (31%), delivering ROI or business value (26%), adaptability to market changes (26%), and cost of compliance (25%). The data is based on responses from 728 ERM decision-makers. This graphic has an associated spreadsheet that includes all data presented. Please access the spreadsheet for details. Figure 11

Introducing OASIS: A Framework For Outcome-Driven Infrastructure Platforms The OASIS Framework helps leaders align infrastructure with business goals and evolve through iterative change (see Figure 1). It defines five core capability areas essential for AI-native platforms — embedding performance, governance, and security directly into their design.

Application and infrastructure management, testing services, business process services, workplace services, and managed security services are good examples. The goal here is to define bundles of capabilities that you can outsource to a provider to create clearer responsibilities and simplify coordination.

We’ve identified the following use cases as extended: application configuration management, application patching, infrastructure configuration management, orchestration/IT process automation, and vulnerability remediation (see Figure 4). Some buyers look to address these use cases in addition to the core ones, but infrastructure automation platforms may less commonly address them.

ManageEngine offers a user-friendly interface for process workflow and task management, with native integrations to its ITOM solutions for infrastructure monitoring and strong asset and configuration management. Its virtual agent enhances user interactions, and its analytics and dashboards provide AI-driven insights.

In Forrester’s Automation Survey, 2025, two of the infrastructure automation challenges most often mentioned by automation technology decision-makers were the difficulty of attracting and retaining talent and a lack of automation management skills (see Figure 3). Companies need tech management skills like change management, communication, collaboration, analytics, and project and program management.