Cloud Computing Trends in 2019 - Beyond Infrastructure to Business Transformation

Cloud computing has evolved from a cost-saving infrastructure alternative to a fundamental enabler of digital business. As we progress through 2019, organizations are moving beyond basic cloud adoption to leverage more sophisticated capabilities that drive innovation and competitive advantage. This comprehensive guide explores the most significant cloud computing trends of 2019 and how they're reshaping enterprise IT and business strategies.

The Evolving Cloud Landscape

The cloud market continues to mature and expand:

• Accelerating Enterprise Adoption: 94% of enterprises now use cloud services in some capacity
• Market Growth: The global public cloud market is projected to reach $214.3 billion in 2019, up 17.5% from 2018
• Shifting Focus: Organizations moving from "Why cloud?" to "Which cloud for which workload?"
• Business Driver: Cloud becoming central to digital transformation initiatives
• Architectural Evolution: Increasingly sophisticated deployment models and service options

These developments are driving the specific trends we'll explore below.

Top Cloud Computing Trends for 2019

1. Multi-Cloud Strategies

Organizations embracing multiple cloud providers:

Strategic Diversification

• Vendor Risk Mitigation: Reducing dependency on a single provider
• Best-of-Breed Selection: Choosing optimal services from different platforms
• Geographic Coverage: Leveraging regional strengths of various providers
• Negotiation Leverage: Maintaining competitive pressure on vendors
• Specialized Capabilities: Accessing unique features from different clouds

Implementation Challenges:

• Management Complexity: Coordinating across multiple environments
• Skill Requirements: Developing expertise across platforms
• Cost Management: Optimizing spending across providers
• Security Consistency: Maintaining uniform protection
• Governance Frameworks: Ensuring compliance across environments

Best Practice: Develop a cloud decision framework that guides workload placement based on specific requirements rather than defaulting to a single provider.

2. Hybrid Cloud Maturation

Seamless integration between private and public clouds:

Practical Implementations

• Workload Portability: Moving applications between environments as needed
• Data Consistency: Maintaining synchronized information across clouds
• Unified Management: Administering hybrid environments through single interfaces
• Consistent Security: Applying uniform protection across environments
• Flexible Scaling: Expanding to public cloud during demand spikes

Implementation Approaches:

• Cloud-Native Platforms: Kubernetes and container technologies enabling consistency
• Hybrid Cloud Platforms: Solutions like Azure Stack, AWS Outposts, and Google Anthos
• Software-Defined Infrastructure: Creating consistent environments across locations
• API-Driven Integration: Connecting services through standardized interfaces
• Hybrid Data Services: Databases and storage that span environments

Example: Capital One has implemented a hybrid cloud strategy that maintains sensitive financial data on private infrastructure while leveraging public cloud for customer-facing applications and analytics.

3. Serverless Computing Expansion

Moving beyond infrastructure management:

Beyond Functions-as-a-Service

• Event-Driven Architecture: Building systems that respond to triggers
• Microservices Integration: Combining serverless with container-based services
• Backend-as-a-Service: Complete application backends without infrastructure management
• DevOps Transformation: Changing development and operational practices
• Cost Optimization: Paying only for actual execution time

Business Benefits:

• Development Acceleration: Focusing on code rather than infrastructure
• Operational Simplification: Reducing management overhead
• Automatic Scaling: Handling variable workloads without provisioning
• Cost Efficiency: Eliminating idle capacity expenses
• Innovation Enablement: Rapid prototyping and experimentation

Example: Coca-Cola implemented a serverless architecture for its vending machines, processing over 1 billion transactions per day while reducing operational costs by 65% compared to their previous solution.

4. Kubernetes Dominance

Container orchestration becoming standard:

Enterprise Adoption Acceleration

• Multi-Cloud Enablement: Providing consistency across environments
• Operational Standardization: Creating common management practices
• Ecosystem Expansion: Growing marketplace of compatible tools and services
• Enterprise Features: Maturing security, monitoring, and governance capabilities
• Managed Services Growth: Cloud providers offering Kubernetes-as-a-Service

Implementation Considerations:

• Organizational Learning Curve: Developing necessary skills and knowledge
• Legacy Application Integration: Connecting traditional systems with containerized services
• Persistent Storage Management: Handling stateful applications effectively
• Security Implementation: Protecting containerized environments properly
• Cost Management: Optimizing resource utilization and spending

Example: The New York Times migrated from a monolithic application to a Kubernetes-based microservices architecture, reducing deployment time from 45 minutes to under 1 minute and enabling more frequent updates.

5. AI and Machine Learning Cloud Services

Democratizing advanced analytics:

Accessible Intelligence

• Pre-Built AI Services: Ready-to-use capabilities like vision, speech, and language processing
• AutoML Platforms: Simplified model development for non-specialists
• ML Infrastructure: Optimized environments for training and inference
• Industry-Specific Solutions: Vertical AI applications for healthcare, finance, etc.
• Edge-Cloud AI Integration: Combining on-device and cloud intelligence

Business Applications:

• Customer Experience Enhancement: Personalization and conversational interfaces
• Operational Optimization: Predictive maintenance and process improvement
• Decision Support: Data-driven insights for strategic choices
• Product Innovation: Embedding intelligence into offerings
• Risk Management: Fraud detection and compliance monitoring

Example: Zola, an online wedding planning company, uses Google Cloud's AI services to automatically categorize and tag thousands of wedding photos, improving search functionality and customer experience.

6. Edge Computing Integration

Extending cloud capabilities to the edge:

Distributed Cloud Models

• Edge-Cloud Continuum: Seamless operation across centralized and distributed resources
• IoT Integration: Processing data closer to collection points
• Latency Reduction: Enabling real-time applications and services
• Bandwidth Optimization: Minimizing data transfer to central clouds
• Offline Operation: Functioning during connectivity interruptions

Implementation Approaches:

• Edge Gateways: Devices that provide local processing and cloud connectivity
• Mini Clouds: Reduced cloud stacks deployed in distributed locations
• Telecom Edge: Leveraging 5G infrastructure for edge computing
• Content Delivery Integration: Combining CDN with compute capabilities
• Edge AI: Running machine learning models on local devices

Example: Chevron has implemented edge computing in its oil fields, processing sensor data locally to detect equipment failures in real-time, reducing downtime and maintenance costs.

7. Cloud Security Evolution

Adapting protection for distributed environments:

Advanced Security Approaches

• Zero Trust Architecture: Assuming no implicit trust regardless of location
• Cloud Security Posture Management: Continuously monitoring configuration and compliance
• DevSecOps Integration: Embedding security throughout the development lifecycle
• Automated Compliance: Ensuring regulatory adherence through code
• Identity-Centric Security: Making identity the primary security perimeter

Emerging Solutions:

• Cloud Access Security Brokers: Providing visibility and control across services
• Container Security Platforms: Protecting containerized applications
• Serverless Security Tools: Securing function-based architectures
• API Protection: Safeguarding the connective tissue of cloud services
• Cloud-Native Security Platforms: Purpose-built for distributed environments

Best Practice: Implement a "shift left" security approach that integrates protection from the earliest stages of development rather than applying it after deployment.

Industry-Specific Cloud Adoption

How different sectors are leveraging cloud technologies:

1. Financial Services

Banks and insurers embracing cloud capabilities:

• Core System Modernization: Moving from legacy platforms to cloud-native alternatives
• Customer Experience Transformation: Creating digital-first banking experiences
• Risk Modeling and Analytics: Leveraging cloud computing power for complex calculations
• Regulatory Compliance: Implementing automated governance and reporting
• Fraud Detection: Using cloud-based AI for real-time transaction monitoring

Example: HSBC migrated risk analytics workloads to Google Cloud, reducing calculation time from days to hours while improving accuracy and compliance.

2. Healthcare

Medical organizations transforming through cloud:

• Telehealth Enablement: Supporting remote care delivery platforms
• Health Data Interoperability: Facilitating secure information exchange
• Medical Research Acceleration: Providing computing power for genomics and drug discovery
• Patient Experience Personalization: Creating tailored digital health journeys
• Operational Efficiency: Optimizing administrative and clinical workflows

Example: Providence St. Joseph Health implemented a cloud-based data platform that integrates information from 51 hospitals, enabling better care coordination and operational insights.

3. Manufacturing

Industrial companies leveraging cloud capabilities:

• Smart Factory Implementation: Connecting production environments to cloud analytics
• Supply Chain Visibility: Creating end-to-end transparency across operations
• Product Development Acceleration: Enabling collaborative design and simulation
• Predictive Maintenance: Anticipating equipment failures before they occur
• Digital Twin Creation: Building virtual replicas of physical assets

Example: Siemens uses cloud-based IoT and analytics platforms to monitor over 500,000 connected devices, optimizing performance and reducing downtime across its manufacturing operations.

4. Retail

Merchants transforming customer experiences:

• Omnichannel Integration: Creating seamless shopping across channels
• Personalization at Scale: Tailoring experiences to individual preferences
• Inventory Optimization: Ensuring product availability while minimizing costs
• Dynamic Pricing: Adjusting prices based on demand and competition
• Supply Chain Resilience: Building adaptable fulfillment networks

Example: Walmart has migrated significant portions of its e-commerce platform to the cloud, enabling them to handle 5x traffic increases during peak shopping periods without performance degradation.

Cloud Implementation Best Practices

Strategies for successful cloud adoption and optimization:

1. Cloud Governance Frameworks

Establishing control and oversight:

• Policy Development: Creating clear guidelines for cloud usage
• Cost Management: Implementing processes to control and optimize spending
• Compliance Automation: Ensuring adherence to regulatory requirements
• Security Standards: Defining and enforcing protection measures
• Service Catalog: Curating approved services and configurations

Best Practice: Implement a Cloud Center of Excellence (CCoE) that brings together stakeholders from IT, security, finance, and business units to develop and maintain governance frameworks.

2. Cloud Financial Management

Optimizing cloud economics:

• Resource Right-Sizing: Matching provisioned resources to actual needs
• Reserved Capacity Planning: Leveraging discounts for predictable workloads
• Spot Instance Utilization: Using variable pricing for flexible workloads
• Idle Resource Elimination: Identifying and removing unused services
• Chargeback/Showback Models: Allocating costs to appropriate business units

Best Practice: Implement automated cost optimization tools that continuously monitor usage patterns and recommend efficiency improvements.

3. Cloud Migration Strategies

Moving workloads effectively:

• Assessment Frameworks: Evaluating applications for cloud suitability
• Migration Patterns: Selecting appropriate approaches (rehost, refactor, etc.)
• Phased Implementation: Moving workloads in logical groups
• Testing Methodologies: Ensuring functionality and performance
• Rollback Planning: Preparing for potential issues

Best Practice: Develop a comprehensive application assessment framework that considers technical compatibility, business criticality, and potential benefits to prioritize migration efforts.

4. Cloud Talent Development

Building necessary skills:

• Training Programs: Developing internal cloud capabilities
• Certification Paths: Creating clear skill development roadmaps
• Partner Relationships: Leveraging external expertise when needed
• Organizational Structure: Aligning teams with cloud operating models
• Knowledge Sharing: Facilitating internal learning communities

Best Practice: Create a cloud skills matrix that identifies required capabilities across different roles and develop targeted learning paths for each position.

Overcoming Cloud Adoption Challenges

Addressing common obstacles to successful implementation:

1. Legacy Integration

Connecting traditional systems with cloud services:

• Challenge: Difficulty integrating older applications with modern cloud platforms
• Solutions:
  • Implement API layers to expose legacy functionality
  • Use hybrid cloud approaches to maintain some workloads on-premises
  • Leverage middleware to bridge technology gaps
  • Create data synchronization mechanisms
  • Adopt incremental modernization approaches

Example: The Commonwealth Bank of Australia implemented an API layer that allowed modern cloud applications to interact with their core banking system, enabling innovation without replacing critical infrastructure.

2. Cloud Complexity Management

Handling increasingly sophisticated environments:

• Challenge: Growing difficulty in managing multi-cloud, hybrid architectures
• Solutions:
  • Implement cloud management platforms for unified administration
  • Adopt infrastructure as code for consistent provisioning
  • Leverage automation for routine operational tasks
  • Develop standardized operating procedures
  • Create abstraction layers that simplify interaction

Best Practice: Implement a cloud operating model that clearly defines roles, responsibilities, processes, and tools for managing complex environments.

3. Skill Gaps

Addressing talent shortages:

• Challenge: Insufficient internal expertise for advanced cloud implementation
• Solutions:
  • Develop comprehensive training and certification programs
  • Partner with managed service providers for specialized capabilities
  • Implement mentoring and knowledge transfer initiatives
  • Leverage cloud provider professional services
  • Create centers of excellence to concentrate expertise

Example: Capital One established a Cloud Center of Excellence and developed a comprehensive training program that has certified over 3,000 engineers in cloud technologies.

4. Compliance and Sovereignty

Meeting regulatory requirements:

• Challenge: Navigating complex regulatory landscapes across regions
• Solutions:
  • Implement data residency controls for sensitive information
  • Leverage regional cloud providers where necessary
  • Develop comprehensive compliance frameworks
  • Automate compliance monitoring and reporting
  • Maintain clear documentation of security controls

Best Practice: Create a compliance matrix that maps regulatory requirements to specific cloud controls and configurations, ensuring consistent adherence across environments.

Measuring Cloud Success

Approaches to evaluating cloud initiatives:

1. Technical Metrics

Assessing operational improvements:

• Performance Indicators: Response times, availability, throughput
• Agility Measures: Deployment frequency, lead time for changes
• Reliability Metrics: Mean time between failures, recovery time
• Scalability Assessment: Ability to handle variable workloads
• Technical Debt Reduction: Legacy system retirement progress

Best Practice: Implement a balanced scorecard of technical metrics that provides a holistic view of cloud performance across multiple dimensions.

2. Business Impact Metrics

Measuring organizational benefits:

• Cost Efficiency: Total cost of ownership compared to previous solutions
• Revenue Impact: Contribution to new or enhanced revenue streams
• Time-to-Market: Acceleration of product and feature delivery
• Customer Experience: Improvements in satisfaction and engagement
• Innovation Capacity: Increase in experimentation and new initiatives

Best Practice: Develop clear linkages between cloud capabilities and business outcomes, with specific metrics that demonstrate value to non-technical stakeholders.

3. Transformation Indicators

Tracking organizational change:

• Cultural Evolution: Shifts in mindset and working practices
• Skill Development: Growth in cloud-related capabilities
• Process Improvement: Adoption of cloud-native methodologies
• Organizational Agility: Ability to respond to changing conditions
• Innovation Metrics: New products and services enabled by cloud

Best Practice: Conduct regular assessments of cloud maturity across technical, process, and organizational dimensions to track transformation progress.

The Future of Cloud Computing: 2019 and Beyond

Emerging trends that will shape cloud adoption:

1. Distributed Cloud

Evolution beyond centralized models:

• Edge-Cloud Convergence: Seamless integration of edge and central resources
• 5G Integration: Leveraging next-generation networks for distributed computing
• Sovereign Cloud Services: Region-specific offerings addressing compliance needs
• Industry Clouds: Specialized platforms for specific sectors
• Micro Data Centers: Small-scale facilities bringing cloud closer to users

Strategic Implication: Organizations should develop architectures that can flexibly distribute workloads across a continuum from edge to central cloud based on specific requirements.

2. Cloud-Native Development

New approaches to building applications:

• Serverless Architectures: Event-driven, consumption-based computing
• Service Mesh Adoption: Managing service-to-service communication
• GitOps Practices: Infrastructure and application deployment through Git workflows
• Progressive Delivery: Advanced deployment patterns like canary and blue/green
• FinOps Integration: Bringing financial accountability to cloud development

Strategic Implication: Development teams should adopt cloud-native practices and architectures to fully leverage the benefits of modern cloud platforms.

3. AI-Driven Cloud Operations

Intelligent management of cloud environments:

• AIOps Implementation: Using AI to automate operational tasks
• Predictive Optimization: Anticipating resource needs before they arise
• Autonomous Remediation: Self-healing systems that address issues automatically
• Intelligent Security: AI-powered threat detection and response
• Natural Language Interfaces: Simplified interaction with cloud systems

Strategic Implication: Organizations should evaluate AIOps platforms that can reduce operational complexity and enable more efficient management of cloud environments.

4. Sustainable Cloud Computing

Environmental considerations in cloud strategy:

• Energy-Efficient Operations: Optimizing resource usage to reduce power consumption
• Renewable Energy Adoption: Cloud providers transitioning to sustainable power sources
• Carbon-Aware Computing: Scheduling workloads based on carbon intensity
• Hardware Lifecycle Management: Responsible disposal and recycling
• Sustainability Metrics: Measuring environmental impact of cloud usage

Strategic Implication: Organizations should incorporate sustainability considerations into their cloud strategy, selecting providers and approaches that align with environmental goals.

Conclusion: Cloud as Business Transformation

As we progress through 2019, cloud computing continues to evolve from a technology initiative to a fundamental business transformation enabler. The most successful organizations will be those that:

1. Develop sophisticated multi-cloud strategies that leverage the strengths of different providers
2. Implement cloud-native architectures that fully utilize modern capabilities
3. Focus on business outcomes rather than technology implementation
4. Build organizational capabilities for ongoing cloud evolution
5. Address governance, security, and compliance in increasingly complex environments

By approaching cloud as a comprehensive business strategy rather than just an IT initiative, organizations can realize the full transformative potential of these technologies. The future belongs to companies that can harness cloud capabilities to innovate faster, operate more efficiently, and deliver exceptional customer experiences.

Remember that cloud adoption is not a destination but a journey of continuous evolution—one that requires ongoing adaptation, learning, and refinement as both technologies and business needs change.

This article was written by Nguyen Tuan Si, a cloud strategy specialist with experience helping organizations develop and implement effective cloud adoption frameworks across various industries.