Free Cloud Adoption Survey

Knowing the virtualization platforms in use helps determine compatibility and migration paths. It's critical to match cloud-hosted instances to existing configurations.

This question clarifies your application footprint and identifies candidates for cloud migration. A clear inventory supports scope and timeline planning.

Understanding existing cloud storage usage highlights data residency and integration status. It also shows how comfortable your team is with cloud storage management.

Container usage indicates modern deployment practices and influences orchestration requirements. This helps estimate the cloud service models needed.

Assessing network readiness identifies potential bottlenecks in cloud data transfer. Adequate bandwidth and low latency are essential for performance.

A complete asset inventory reduces migration surprises and uncovers hidden dependencies. It also streamlines license and compliance checks.

Legacy integrations can be tricky and often require specialized middleware or refactoring. Early planning avoids costly redesigns post-migration.

Database compatibility determines whether you'll refactor, rehost, or replatform. This directly impacts migration complexity and cost.

Existing backup and DR processes inform your cloud continuity strategy. You can then map these processes to cloud-native solutions.

Scalability needs drive instance sizing and auto-scaling policies. Clear requirements help design resilient, cost-effective architectures.

Identifying applicable regulations ensures your cloud setup addresses legal and industry requirements. This reduces compliance risk and potential fines.

Understanding your IAM practices helps design secure authentication and authorization in the cloud. Consistent access policies prevent unauthorized data access.

Encryption practices safeguard sensitive data across environments and during transfers. Confirming encryption standards is vital for security posture.

A documented response plan helps contain and remediate security incidents quickly. It also ensures timely communication with stakeholders and regulators.

Knowing data location constraints guides cloud region selection. This prevents violations of data residency laws and enhances user trust.

Effective auditing tools detect unauthorized actions and support forensic analysis. Monitoring access is a cornerstone of a strong security posture.

Framework adoption indicates maturity and provides structured controls for cloud security. This simplifies alignment with industry best practices.

Regular testing reveals security gaps before they are exploited. Scheduled assessments demonstrate proactive risk management.

Human error is a common threat - training reduces this risk. Awareness programs foster a security-first culture within your organization.

Maintaining accurate records supports audits and regulatory inquiries. Automated reporting reduces manual work and errors.

Clarifying the main motivator - cost savings, agility, or innovation - focuses strategy development. It also helps measure success post-migration.

Measurable KPIs - such as uptime, cost reduction, or performance - guide progress tracking. They provide accountability for teams and leadership.

A realistic timeline aligns resources and sets stakeholder expectations. It also helps identify critical milestones and dependencies.

Identifying sponsors, IT leads, and business owners ensures cross-functional collaboration. Early involvement reduces resistance to change.

A step-by-step roadmap mitigates risks and keeps the project on track. Phased approaches allow iterative validation and adjustment.

Prioritization should consider business impact, complexity, and dependencies. Early wins build momentum and support for ongoing migration.

Selecting the right tooling impacts migration speed and reliability. Evaluation should include cost, features, and vendor support.

Techniques like blue-green deployments and replication reduce service interruptions. Planning for rollback scenarios further strengthens resilience.

Comparing cloud versus on-premises costs ensures financial viability. It also highlights potential savings and hidden expenses.

Rigorous testing - functional, performance, and security - confirms migration success. It prevents unforeseen issues from impacting users.

Access methods influence UX design and infrastructure configurations. Clear access planning reduces user friction.

IT teams need hands-on skills for provisioning, monitoring, and troubleshooting. Tailored training accelerates cloud proficiency.

Structured onboarding ensures users understand new workflows and benefits. Early engagement fosters positive attitudes toward change.

Consistent messaging via email, intranet, or chat keeps users informed. Clear communication reduces confusion and resistance.

User surveys and feedback forms highlight pain points and improvement areas. Continuous feedback loops support iterative enhancements.

Tracking logins, feature usage, and support tickets quantifies adoption levels. Metrics guide ongoing training and support efforts.

Peer advocates accelerate adoption by providing real-world insights. Champion programs create a support network for hesitant users.

Accessible resources empower users to resolve issues independently. This reduces support demand and speeds up adoption.

Defining support tiers and response times maintains service quality. Well-documented processes ensure consistent assistance.

Pre- and post-training assessments measure knowledge gains. Training satisfaction surveys reveal areas for improvement.

Establishing the baseline on-premises costs allows for direct comparison with cloud expenses. This facilitates clear ROI calculations.

Setting a realistic budget prevents overspend and aligns stakeholder expectations. It also guides vendor selection and service tiers.

Implementing cost tracking tools ensures real-time visibility into spend. Usage data drives optimization and rightsizing decisions.

Understanding consumption-based billing highlights potential savings. It also helps identify scenarios where reserved or committed use may be more cost-effective.

Scenario modeling compares outcomes of lift-and-shift, refactoring, and hybrid approaches. This informs strategic choices based on financial impact.

Key metrics like cost per VM, storage spend, and data transfer fees provide insights into efficiency. Regular reviews ensure alignment with budget goals.

Controlling unexpected charges requires alerting thresholds and governance policies. Proactive management avoids billing surprises.

Rightsizing aligns resource allocation with actual usage, reducing waste. Automated tools can recommend adjustments for optimal performance and cost.

Auto-scaling policies should include budget controls and usage caps. Planning for peak and off-peak cycles prevents runaway spend.

Accurate forecasting accounts for growth trends and seasonal variations. It ensures budgets remain aligned with evolving business needs.

Defining monitoring tools and metrics ensures service levels are met. Proactive alerts reduce downtime and user impact.

SLAs define uptime guarantees and penalties, setting clear expectations. They also influence your choice of service tiers and vendors.

Documented processes enable swift issue resolution and limit business disruption. Clear escalation paths ensure accountability.

Automation accelerates optimization by detecting and addressing inefficiencies in real time. It supports consistent performance at scale.

Redundant architectures and failover strategies prevent single points of failure. Regular testing validates these mechanisms.

Comprehensive logging supports troubleshooting and compliance. Alert thresholds aligned with KPIs drive timely interventions.

Automated patch management minimizes vulnerabilities and maintenance windows. Scheduling and rollback plans mitigate risk.

IaC ensures consistency, repeatability, and version control for deployments. It accelerates recovery and scaling activities.

Metrics like mean time to repair (MTTR) and resource utilization highlight performance trends. Regular reporting fosters continuous improvement.

Predictive analytics and usage patterns inform proactive scaling decisions. Capacity planning prevents performance bottlenecks and over-provisioning.