Jonathan Lalou's Blog

Posts Tagged ‘HybridCloud’

At Devoxx Poland 2022, Paweł Piekut, a seasoned software developer at Bosch, delivered an insightful presentation on the migration of their e-bike cloud platform from a private cloud to a public cloud environment. Drawing from his expertise in Java, Kotlin, and .NET, Paweł narrated the intricate journey of transitioning a complex IoT ecosystem, highlighting the technical challenges, strategic decisions, and lessons learned. His talk offered a practical roadmap for organizations navigating the complexities of cloud migration, emphasizing the balance between innovation, scalability, and compliance.

Navigating the Private Cloud Landscape

Paweł began by outlining the initial deployment of Bosch’s e-bike cloud on a private cloud developed internally by the company’s IT group. This proprietary platform, designed to support the e-bike ecosystem, facilitated communication between hardware components—such as drive units, batteries, and controllers—and the mobile app, which interfaced with the cloud. The cloud served multiple stakeholders, including factories for device flashing, manufacturers for configuration, authorized services for diagnostics, and end-users for features like activity tracking and bike locking. However, the private cloud faced significant limitations. Scalability was constrained, requiring manual capacity requests and investments, which hindered agility. Downtimes were frequent, acceptable for development but untenable for production. Additionally, the platform’s bespoke nature made it challenging to hire experienced talent and limited developer engagement due to its lack of market-standard tools.

Despite these drawbacks, the private cloud offered advantages. Its deployment within Bosch’s secure network ensured high performance and simplified compliance with data privacy regulations, critical for an international product subject to data localization laws. Costs were predictable, and the absence of vendor lock-in, thanks to open-source frameworks, provided flexibility. However, the need for modern scalability and developer-friendly tools drove the decision to explore public cloud solutions, with Amazon Web Services (AWS) selected for its robust support.

The Hybrid Cloud Conundrum

Transitioning to a hybrid cloud model introduced a blend of private and public cloud environments, creating new challenges. Bosch’s internal policy of “on-transit data” required data processed in the public cloud to be returned to the private cloud, necessitating complex and secure data transfers. While AWS Direct Connect facilitated this, the hybrid setup led to operational complexities. Only select services ran on AWS, causing a divide among developers eager to work with widely recognized public cloud tools. Technical issues, such as Kafka’s inaccessibility from the private cloud, required significant effort to resolve. Error tracing across clouds was cumbersome, with Splunk used in the private cloud and Elasticsearch in the public cloud, complicating root-cause analysis. The simultaneous migration of Jenkins added further complexity, with duplicated jobs and confusing configurations.

Despite these hurdles, the hybrid model offered benefits. It allowed Bosch to leverage the private cloud’s security for sensitive data while tapping into the public cloud’s scalability for peak loads. This setup supported disaster recovery and compliance with data localization requirements. However, the on-transit data concept proved overly complex, leading to dissatisfaction and prompting a strategic shift toward a cloud-first approach, prioritizing public cloud deployment unless justified otherwise.

Embracing the Public Cloud

The full migration to AWS marked a pivotal phase, divided into three stages. First, the team focused on exploration and training to master AWS products and the pay-as-you-go pricing model, which made every developer accountable for costs. This stage emphasized understanding managed versus unmanaged services, such as Kubernetes and Kafka, and ensuring backup compatibility across clouds. The second stage involved building new applications on AWS, addressing unknowns and ensuring secure communication with external systems. Finally, existing services were migrated from private to public cloud, starting with development and progressing to production. Throughout, the team maintained services in both environments, managing separate repositories and addressing critical bugs, such as Log4j vulnerabilities, across both.

To mitigate vendor lock-in, Bosch adopted a cloud-agnostic approach, using Terraform for infrastructure-as-code instead of AWS-specific CloudFormation. While tools like S3 and DynamoDB were embraced for their market-leading performance, backups were standardized to ensure portability. The public cloud’s vast community, extensive documentation, and readily available resources reduced knowledge silos and enhanced developer satisfaction, making the migration a transformative step for innovation and agility.

Lessons for Cloud Migration

Paweł’s experience underscores the importance of aligning cloud strategy with organizational needs. The public cloud’s immediate resource availability and developer-friendly tools accelerated development, but required careful cost management. Hybrid cloud offered flexibility but introduced complexity, particularly with data transfers. Private cloud provided security and control but lacked scalability. Paweł emphasized defining precise requirements—budget, priorities, and compliance—before choosing a cloud model. Startups may favor public clouds for agility, while regulated industries might opt for private or hybrid solutions to prioritize data security and network performance. This strategic clarity ensures a successful migration tailored to business goals.

Links:

• Bosch company website

Lecturer

Cyril Morcrette serves as Technical Director at Mappy, a pioneering French provider of geographic and local commerce services with thirteen million euros in annual revenue and eighty employees. Under his leadership, Mappy has evolved from a traditional route planning service into a comprehensive platform integrating immersive street-level imagery, local business discovery, and personalized recommendations. His infrastructure strategy reflects deep experience with both cloud and on-premises environments, informed by multiple large-scale projects that pushed technological boundaries.

Abstract

Cloud computing excels at enabling rapid prototyping and handling uncertain demand, but its cost structure can become prohibitive as projects mature and usage patterns stabilize. This presentation chronicles Mappy’s journey with immersive geographic visualization — a direct competitor to Google Street View — from initial cloud deployment to eventual repatriation to on-premises infrastructure. Cyril Morcrette examines the economic, operational, and technical factors that drove this decision, providing a framework for evaluating infrastructure choices throughout the application lifecycle. Through detailed cost analysis, performance metrics, and migration case studies, he demonstrates that cloud is an ideal launch platform but often not the optimal long-term home for predictable, high-volume workloads. The session concludes with practical guidance for smooth repatriation and the broader implications for technology strategy in established organizations.

The Immersive Visualization Imperative

Mappy’s strategic pivot toward immersive geographic experiences required capabilities beyond traditional mapping: panoramic street-level imagery, 3D reconstruction, and real-time interaction. The project demanded massive storage (terabytes of high-resolution photos), significant compute for image processing, and low-latency delivery to users.

Initial estimates suggested explosive, unpredictable traffic growth. Marketing teams envisioned viral adoption, while technical teams worried about infrastructure bottlenecks. Procuring sufficient on-premises hardware would require months of lead time and capital approval — unacceptable for a market-moving initiative.

Amazon Web Services offered an immediate solution: spin up instances, store petabytes in S3, process imagery with EC2 spot instances. The cloud’s pay-as-you-go model eliminated upfront investment and provided virtually unlimited capacity.

Cloud-First Development: Speed and Agility

The project launched entirely in AWS. Development teams used EC2 for processing pipelines, S3 for raw and processed imagery, CloudFront for content delivery, and Elastic Load Balancing for web servers. Auto-scaling handled traffic spikes during marketing campaigns.

This environment enabled rapid iteration:
– Photographers uploaded imagery directly to S3 buckets
– Lambda functions triggered processing workflows
– Machine learning models (running on GPU instances) detected business facades and extracted metadata
– Processed panoramas were cached in CloudFront edge locations

Within months, Mappy delivered a functional immersive experience covering major French cities. The cloud’s flexibility absorbed the uncertainty of early adoption while development teams refined algorithms and user interfaces.

The Economics of Maturity

As the product stabilized, usage patterns crystallized. Daily active users grew steadily but predictably. Storage requirements, while large, increased linearly. Processing workloads became batch-oriented rather than real-time.

Cost analysis revealed a stark reality: cloud expenses were dominated by data egress, storage, and compute hours — all now predictable and substantial. Mappy’s existing data center, built for core mapping services, had significant spare capacity with fully amortized hardware.

Cyril presents the tipping point calculation:
– Cloud monthly cost: €45,000 (storage, compute, bandwidth)
– On-premises equivalent: €12,000 (electricity, maintenance, depreciation)
– Break-even: four months

The decision to repatriate was driven by simple arithmetic, but execution required careful planning.

Repatriation Strategy and Execution

The migration followed a phased approach:

1. Data Transfer: Used AWS Snowball devices to move petabytes of imagery back to on-premises storage. Parallel uploads leveraged Mappy’s high-bandwidth connectivity.

2. Processing Pipeline: Reimplemented image processing workflows on internal GPU clusters. Custom scripts replaced Lambda functions, achieving equivalent throughput at lower cost.

3. Web Tier: Deployed Nginx and Varnish caches on existing web servers. CDN integration with Akamai preserved low-latency delivery.

4. Monitoring and Automation: Migrated CloudWatch metrics to Prometheus/Grafana. Ansible playbooks replaced CloudFormation templates.

Performance remained comparable: page load times stayed under two seconds, and system availability exceeded 99.95%. The primary difference was cost — reduced by seventy-five percent.

Operational Benefits of On-Premises Control

Beyond economics, repatriation delivered strategic advantages:
– Data Sovereignty: Full control over sensitive geographic imagery
– Performance Predictability: Eliminated cloud provider throttling risks
– Integration Synergies: Shared infrastructure with core mapping services reduced operational complexity
– Skill Leverage: Existing systems administration expertise applied directly

Cyril notes that while cloud elasticity was lost, the workload’s maturity rendered it unnecessary. Capacity planning became straightforward, with hardware refresh cycles aligned to multi-year budgets.

Lessons for Infrastructure Strategy

Mappy’s experience yields a generalizable framework:
1. Use cloud for uncertainty: Prototyping, viral growth potential, or seasonal spikes
2. Monitor cost drivers: Storage, egress, compute hours
3. Model total cost of ownership: Include migration effort and operational overhead
4. Plan repatriation paths: Design applications with infrastructure abstraction
5. Maintain hybrid capability: Keep cloud skills current for future needs

The cloud is not a destination but a tool — powerful for certain phases, less optimal for others.

Conclusion: Right-Sizing Infrastructure for Business Reality

Mappy’s journey from cloud experimentation to on-premises efficiency demonstrates that infrastructure decisions must evolve with product maturity. The cloud enabled rapid innovation and market entry, but long-term economics favored internal hosting for stable, high-volume workloads. Cyril’s analysis provides a blueprint for technology leaders to align infrastructure with business lifecycle stages, avoiding the trap of cloud religion or on-premises dogma. The optimal stack combines both environments strategically, using each where it delivers maximum value.

Links:

• Video of the lecture
• Mappy website