Building and delivering capable, performant robots is hard.
We understand that robotics development teams struggle through a number of disparate challenges – hardware development and integration, fleet operations, regulatory compliance, customer constraints, and software development across multiple capabilities. Facing all of these battle fronts, your team may find itself searching for tooling to address capabilities outside of its core competencies, oftentimes making build-vs-buy decisions.
Our new series of blog posts walks through the effort required to build a data platform providing cohesive tooling and automation to accelerate data-dependent robotics software development workflows.
The robotics software development process revolves around the data generated from robotics operations and simulation.
- Robotics developers often must visualize log data to triage and determine the root cause of issues.
- Discovery of interesting events within the data, such as performance insufficiencies, degradation, and anomalies, provides crucial feedback to developers.
- Aggregated analysis of robotics data enables reporting on overall software and operational performance.
- Scenario analysis provides insights into what robots encounter and exposes gaps in operational domain coverage.
- Machine learning training and validation require high-quality, curated data sets.
Harnessing the power of the recorded logs requires a multidisciplinary software engineering effort, especially when robot fleet deployments generate high volumes of data. Efficient, event-driven processing of data lends itself to processing in the cloud to enable resource elasticity and minimize infrastructure costs. Understanding that some teams require on-premise deployments due to customer or bandwidth constraints, leveraging cloud infrastructure during the development process provides more flexibility and velocity for the software development team, and containerization enables a fairly infrastructure-agnostic approach.
Laying a strong foundation in cloud infrastructure management unlocks other capabilities for your organization to maximize the power of your robotics data, such as event-driven microservice architectures, data pipelines, workflow orchestration, and analytics tooling integration.
Sustainably adopting cloud infrastructure requires planning and risk management to protect your organization’s data and prevent cost overruns. Your team must consider several broader architecture decisions requiring a number of cloud-based skill sets. Some examples include:
- Networking:
- Designing and implementing secure and efficient network topologies within the cloud environment.
- Optimizing network performance to minimize latency and ensure data transmission reliability.
- Component Selection:
- Choosing the appropriate cloud components and resources to align with your organization's specific needs and budget constraints.
- Evaluating the scalability, performance, and cost-effectiveness of various cloud offerings, including compute instances, storage solutions, and databases.
- Operationalization:
- Creating automated deployment processes to streamline the provisioning and configuration of cloud resources.
- Implementing version control and configuration management tools to maintain consistency and track changes.
- Integrating continuous integration and continuous delivery (CI/CD) practices to accelerate development and deployment cycles.
- Deploying monitoring tools to track performance and utilization.
- Planning capacity and optimizing resource utilization to avoid over-provisioning and manage costs.
- Implementation of backup and recovery strategies to protect your data and ensure business continuity.
The architectural decisions above lay important foundations for additional capabilities required to support robotics development data management. We will cover these in subsequent blog posts, including:
- Microservice and event-driven architectures
- Data pipelines and workflow orchestration
- Analytics and robotics intelligence tooling integration
- Data lifecycle management and compliance
Building data infrastructure requires significant planning and engineering that can divert resources away from core robotics development efforts. At Model-Prime, we help your team accelerate toward your goals by providing a turn-key solution for robotics data management. Find more details about how you can use our platform at https://docs.model-prime.com.
