We’re proud to share the latest additions to our Google Cloud Expertise portfolio: Cloud Native Application Development, MLOps, and Improve Software Delivery Pipeline. These milestones reaffirm our position as a trusted, end-to-end Google Cloud Partner delivering measurable client success across the full innovation lifecycle, and complement our extensive existing Expertise designations.
These designations are a testament to our team’s technical proficiency, relentless dedication to tackling complex client challenges, and proven track record of harnessing Google Cloud’s capabilities to drive real-world business transformation.
Let’s pull back the curtain on what each of these designations truly means.
Cloud Native Application Development: building the future, faster and smarter
Our Cloud Native Application Development Expertise is Google Cloud’s stamp of approval on our ability to help organizations rapidly and reliably develop, build, deploy, secure, and monitor applications designed specifically for the cloud. This means embracing a modern approach using technologies like Google Kubernetes Engine (GKE) and serverless solutions.
Imagine applications that are inherently agile, infinitely scalable, and incredibly resilient. That’s the promise of cloud native. Are you looking to break free from rigid legacy systems? Do you need to launch new features at lightning speed, or scale effortlessly to meet unpredictable demand? We help you move beyond traditional, rigid systems to create flexible, microservices-driven architectures that empower you to:
- Ignite innovation: Launch new features and updates at lightning speed, keeping you ahead of the curve.
- Scale without limits: Effortlessly handle fluctuating demand, ensuring seamless performance and cost efficiency.
- Achieve built-in resilience: Design systems that shrug off individual component failures, guaranteeing always-on availability.
Cloud native in action
Here’s just one example of how we made cloud-native resilience real for a global financial leader:
Fortifying financial operations with unmatched resilience
A prominent financial institution faced a daunting challenge: ensuring their mission-critical wire transfer operations remained seamless, even amidst system outages. They grappled with securely handling sensitive financial data, processing real-time transactions, adhering to stringent regulatory compliance, and guaranteeing high availability and disaster recovery.
We partnered with them to architect a sophisticated cloud-based Business Continuity Plan (BCP) solution on Google Cloud. Our strategy was comprehensive:
- Microservices for flexibility: We designed the solution with a granular microservices architecture for enhanced adaptability and inherent resilience.
- Multi-region Kubernetes: Deploying the solution across multiple Google Cloud regions using GKE provided vital redundancy and fault tolerance, ensuring operations continued uninterrupted.
- Ironclad security with Cloud Armor: Implementing Google Cloud Armor delivered advanced DDoS protection and Web Application Firewall (WAF) capabilities, forming a robust shield for their critical financial operations.
- Seamless legacy integration: We integrated the new system with their existing financial infrastructure, ensuring a smooth transition and operational continuity.
The impact: This financial powerhouse now boasts a highly available, secure, and scalable wire operations system. They’ve achieved 99.99% system availability, sub-second response times, 100% security compliance, and can process thousands of daily transactions with an error rate of less than 0.1%. This resilient cloud solution guarantees their critical wire transfers remain uninterrupted, safeguarding their business and their customers’ trust.
MLOps: turn your AI ambition into a production-ready reality
Our MLOps Expertise is Google Cloud’s recognition of our proven ability to not just build, but truly operationalize and test production-grade AI models, creating robust, end-to-end machine learning solutions. This demanding expertise requires a powerful blend of skills across infrastructure, DevOps, data engineering, and machine learning, ensuring your AI efforts are scalable, reliable, and impactful.
Are your promising AI models stuck in pilot purgatory? Do you struggle to move from experiment to continuous, real-world impact? MLOps is the engineering discipline that bridges the gap between groundbreaking AI research and tangible business value. It’s about building automated pipelines to manage the entire ML lifecycle, guaranteeing that your AI initiatives are sustainable, continuously improving, and deliver consistent results. Our expertise encompasses:
- Robust data pipelines: Architecting solid data foundations using BigQuery and Cloud Storage, with efficient ETL processes powered by tools like Dataflow.
- Vertex AI: Leveraging the comprehensive Vertex AI platform for automated ML workflows (Vertex AI Pipelines), intelligent feature management (Feature Store), rigorous versioning (Model Registry), lineage tracking (ML Metadata), and proactive performance monitoring (Model Monitoring).
- DevOps for AI: Implementing CI/CD practices (Cloud Build), Infrastructure as Code (Terraform), and robust version control (GitHub) to automate model deployment and updates.
- Actionable intelligence: Connecting ML outputs to business intelligence tools like Looker for insightful, data-driven decision-making.
Driving real-world AI impact with MLOps
We’ve helped organizations transition their data science initiatives from concept to continuous operation, enabling seamless automation and model evolution. Here’s just one example:
Unlocking network insights with automated AI for a global leader
A global leader in internet performance testing embarked on developing an AI/ML platform to analyze vast network performance datasets. Their critical challenge was to accurately predict the geographic location of traceroutes through complex network data, and they urgently needed to operationalize this capability for ongoing, real-time analysis.
We partnered with them to construct a minimum viable model and a robust, automated ML pipeline built entirely on Google Cloud’s Vertex AI:
- End-to-end automation: We implemented a comprehensive ML pipeline on Vertex AI, automating data preprocessing, model training, evaluation, and conditional deployment, orchestrated through Vertex AI Pipelines.
- Leveraging managed services: The solution smartly utilized Vertex AI’s managed services for efficient training and deployment, including AutoML Tabular Training for regional models and XGBoost for custom training.
- Seamless data integration: Extensive use of Vertex AI and BigQuery ML ensured robust machine learning training and deployment for their critical network diagnostics.
The impact: This project successfully delivered a powerful AI/ML platform for traceroute data analysis, with models achieving impressive precision and recall in predicting geographic locations. By automating the entire ML workflow, we enabled them to efficiently deploy and maintain predictive models, showcasing the immense power of Vertex AI and BigQuery ML in enhancing the understanding and management of vital internet infrastructure.
Improve Software Delivery Pipeline: turbocharge your path to production
Our Improve Software Delivery Pipeline Expertise is all about revolutionizing how quickly and reliably you can build, test, and deploy code changes across diverse platforms. It’s about empowering your developers to focus on what they do best – writing brilliant code – by automating away infrastructure management and minimizing operational errors.
Are your development cycles bottlenecked? Do manual errors slow down your releases? By embracing robust automation and streamlined workflows, we help organizations achieve:
- Blazing fast time-to-market: Get innovative features and critical updates into your users’ hands at unprecedented speed.
- Enhanced developer focus: Free your talented developers from tedious, manual tasks, allowing them to channel their energy into high-value coding and innovation.
- Error-free precision: Automate repetitive processes and implement Infrastructure as Code (IaC) to virtually eliminate human error and enhance reliability.
- Peak operational efficiency: Optimize resource utilization, simplify complex deployment processes, and reduce overhead.
See how we’ve delivered faster, more reliable software
Here’s how we helped one leading organization build more agile and robust software delivery pipelines:
Streamlining client onboarding and integration for a data analytics innovator
A global leader in data analytics faced a significant bottleneck: new clients integrating with their software endured a manual, protracted onboarding process that often stretched from 3 to 9 months and incurred substantial costs. Their vision was to create a public, free demo environment that would eliminate cumbersome VM downloads and manual configurations.
We partnered with them to overhaul their software delivery, prioritizing speed, automation, and self-service:
- CI/CD power-up with Cloud Build: We implemented robust continuous integration/continuous delivery (CI/CD) pipelines using Cloud Build, automating the entire build, test, and deployment workflow.
- Dynamic deployments with Cloud Run: Leveraging Cloud Run, we enabled rapid, scalable deployment of containerized applications for their new demo environment, adapting effortlessly to demand.
- Intelligent automation with Cloud Functions: We utilized Cloud Functions to write and deploy event-driven code, automating various processes within the demo environment for maximum efficiency.
- Infrastructure as Code (IaC): Developing Infrastructure as Code for deploying their cutting-edge analytics experience on Google Cloud ensured repeatable, error-free deployments and significantly faster setup times.
The impact: This transformation led to a 10X increase in customer demos and opened three exciting new avenues for customer engagement. The solution empowered customers and partners to run integration tests directly within their CI/CD pipelines against their databases, dramatically accelerating release speed and virtually eliminating manual errors. This collaboration infused their team with full-stack development expertise and Google Cloud infrastructure knowledge, becoming pivotal to their project’s resounding success.
Partnering for a cloud-powered, agile future
These Expertises collectively highlight our comprehensive capability to help organizations across their entire cloud journey—from architecting and building highly resilient, scalable applications, to operationalizing cutting-edge AI at scale, and turbocharging their entire software delivery lifecycle. We’re excited to continue partnering with customers, leveraging the full power of Google Cloud to solve their most complex challenges, drive innovation, and achieve lasting business value.
Ready to transform your cloud strategy and unlock your organization’s full potential?
Join SADA Ground School 2025, a complimentary digital event hosted by SADA and Google Cloud. You’ll explore practical strategies and get production-ready blueprints from sessions covering diverse enterprise AI use cases, along with crucial insights on data readiness and cloud security. Discover a clear roadmap to achieve real ROI with AI and other cloud solutions. Register today to transform your aspirations into tangible results!
You can learn more and register for the event here: SADA Ground School 2025
