How to Identify Critical Workloads for Cloud Migration

Migrating to the cloud? Start by identifying your critical workloads. These are systems or applications where downtime or issues could severely impact your business operations, revenue, or reputation. Here's a quick guide to get started:

• What Makes a Workload Critical?
  Look for workloads with high availability needs, strict security or compliance requirements, or those handling sensitive data (e.g., payment systems or customer databases).
• Steps to Identify and Prioritise Workloads:
  1. List All Workloads: Document applications, databases, and services, noting their function, usage patterns, resource needs, and dependencies.
  2. Categorise by Importance: Group workloads by business criticality, performance needs, security, and compliance requirements.
  3. Rank for Migration: Assess each workload’s business impact and migration risk to determine the order.
  4. Test Compatibility: Check architecture, data storage, and security requirements for cloud readiness.
  5. Plan and Execute: Group similar workloads, schedule migrations, and test thoroughly to minimise disruptions.
• Key Metrics to Monitor Post-Migration:
  Track availability (99.9%+), response times (<200ms), and costs to ensure performance and efficiency.

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Step 1: List and Review Current Workloads

Start by creating a complete inventory of your workloads to uncover dependencies and potential risks.

Make a Full Workload List

Document every application, database, and service in your system. Include key details like:

A fintech CTO highlights the importance of detailed documentation:

"As a fintech company, downtime isn't just an inconvenience - it's a risk to our customers' trust. Their rapid incident response and 24/7 monitoring have drastically reduced our recovery times, and their team feels like an extension of our own. Knowing we have certified engineers on call around the clock gives us complete peace of mind."

Once you’ve compiled the list, group workloads into categories to better understand their individual needs.

Sort Workloads by Type

Organise workloads based on their unique characteristics and requirements. Use these key classification factors:

After categorising, focus on identifying how these workloads interact with one another.

Find Connected Systems

Pinpoint dependencies to avoid disruptions during migration. Document key connections, such as:

• Direct Dependencies: Systems that communicate directly with each other.
• Shared Resources: Databases, storage, or authentication services used by multiple workloads.
• Integration Points: APIs, message queues, or other communication methods.
• Data Flows: The movement of information between systems.

Pay attention to critical paths and bottlenecks when mapping these connections. This will help you decide which workloads to prioritise for migration and which should be moved together to keep the system running smoothly.

Step 2: Rank Workloads for Migration Order

Once you've completed your workload inventory, the next step is to decide which systems should be migrated first. This involves assessing their business impact and migration risks.

Assess Business Impact

Evaluate each workload based on the following factors:

Use measurable data, like revenue contributions or user engagement, to create a composite score for each workload.

Categorise Migration Risk Levels

Workloads can be grouped into risk levels to prioritise migration:

Low-Risk Workloads:

• Stand-alone applications
• Internal tools that are not mission-critical
• Development or testing environments
• Systems already optimised for cloud

Medium-Risk Workloads:

• Customer-facing systems with moderate traffic
• Applications with manageable dependencies
• Systems requiring minor modifications for cloud compatibility
• Services that can tolerate some downtime

High-Risk Workloads:

• Revenue-critical systems
• Applications subject to strict compliance regulations
• Legacy systems with outdated architecture
• Services requiring continuous availability

Build Priority Charts

Rank workloads by evaluating key factors:

Consider using AI-powered tools to refine your analysis. Studies indicate that organisations leveraging AI for cloud planning can reduce cloud costs by 25% while maintaining performance.

"We don't just support your cloud, we elevate it."

Finally, use a migration readiness matrix to compare business impact against complexity of implementation. This approach helps determine the ideal migration sequence and prepares you for the next step: cloud compatibility testing.

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Step 3: Check Migration Requirements

Test Cloud Compatibility

Before migrating, ensure your applications are compatible with the cloud environment. Review their architecture and dependencies carefully:

Identify any bottlenecks or areas where architectural adjustments might be required.

Calculate All Costs

Migration expenses go beyond just infrastructure. Plan for both direct and indirect costs:

Direct Costs:

• Infrastructure and platform fees
• Data transfer charges
• Storage requirements
• Backup and disaster recovery
• Security and compliance tools

Indirect Costs:

• Training for staff
• Third-party tools and services
• Performance monitoring
• Technical support
• Temporary parallel environments

A detailed cost analysis helps avoid unexpected expenses and ensures resources are used efficiently.

Run Test Migrations

Testing your migration process is essential to avoid disruptions. Here's how to approach it:

1. Set Up a Test Environment
   Create a test setup that mirrors your production environment. Measure key metrics like response times, throughput, resource usage, and service-level indicators (SLIs and SLOs).
2. Conduct Pilot Migrations
   Start with non-critical workloads to validate your process. Research shows that organisations leveraging AI insights can resolve issues 40% faster during migration testing.

"We don't just support your cloud, we elevate it." - Critical Cloud

Thorough testing ensures a smoother migration and helps you create a reliable plan.

Step 4: Write the Migration Plan

Group Similar Workloads

Organise workloads that share common technical needs, resources, business functions, or downtime tolerances. This approach helps streamline the migration process.

Use these groupings to create migration waves. This helps maintain system stability and minimises disruptions during the process.

Schedule and Assign Teams

Recent studies show that AI-powered cloud support can improve engineering efficiency by 60%.

When planning schedules, focus on these key elements:

• Assign specialised teams and allocate resources efficiently
• Schedule migrations during off-peak hours to limit business impact
• Allow time for thorough testing between migration phases

Once the schedule is set, prepare backup plans to handle any unexpected issues during the migration.

Prepare for Issues

Develop strong contingency plans to manage potential problems.

"Their structured post-incident analysis identifies recurring risks and improves platform stability".

Research shows that organisations using AI-powered cloud support experience the following benefits:

• 40% faster incident resolution
• 25% lower cloud costs
• Improved platform stability through proactive monitoring

For expert support during your migration, consider partnering with Critical Cloud. Their AI-driven cloud support services are designed to optimise performance and minimise disruptions.

Step 5: Track and Improve Cloud Performance

Check Performance Goals

Define clear SLIs (Service Level Indicators) and SLOs (Service Level Objectives) to evaluate performance after migration. Focus on metrics that directly affect business operations:

Using real-time AIOps monitoring can significantly speed up problem detection, cutting customer impact by up to 40%. These metrics guide adjustments like cost control and fine-tuning for future migrations.

Lower Cloud Costs

Post-migration, it’s essential to keep an eye on costs and make adjustments where needed. AI-driven tools can highlight inefficiencies and suggest changes, which could reduce cloud expenses by as much as 25%.

Focus on these areas:

• Resource usage: Prevent over-provisioning by using automated scaling.
• Data management: Archive infrequently accessed data and remove duplicates.
• Network traffic: Use caching and content delivery methods to streamline data flow.

These insights can also shape better strategies for future migrations.

Learn from Each Migration

Analyse the results of each migration to improve your overall cloud approach. Keep track of performance shifts, technical challenges, resource allocation accuracy, time taken for migration, and how actual costs compared to estimates.

This information helps refine strategies for better performance and cost management. Leverage AI tools and expert support, like those from Critical Cloud, to maintain a secure, efficient, and high-performing cloud environment.

Keys to Migration Success

Moving to the cloud successfully requires careful planning, ongoing oversight, and the right expertise. By combining AI-driven tools with professional guidance, organisations can resolve issues up to 40% faster and reduce cloud expenses by 25%.

Here are three core principles to help ensure a smooth migration process:

• Proactive Monitoring and Response
  Round-the-clock monitoring helps catch problems early, while AI pinpoints patterns to keep migration on track.
• Blending Automation with Expertise
  Critical Cloud's AIM combines AI insights with certified specialists to align automated processes with business goals and security requirements.
• Commitment to Continuous Improvement
  After migration, success hinges on tracking performance and managing costs effectively. Key areas to focus on include:

These principles tie together all the essential steps of migration planning, forming a solid foundation for cloud success. With a structured approach and expert guidance, organisations can transition seamlessly while maintaining strong performance and cost control.

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