CoreLogicis a leading provider of global property information, analytics, and data-enabled solutions, and runs over 25,000 business-critical application instances on Google Cloud using container runtimes. Recently, it implemented several Google Cloud technologies that resulted in a 30% improvement in operational efficiency while increasing application performance and data availability for its business users. Read on to learn more.
Seeking a scalable, cost-effective, modern application platform
CoreLogic’s property data powers real estate professionals, financial institutions, insurance carriers, government agencies, and other customers by providing access to over 5.5 billion property records spanning 50 years. In addition, CoreLogic processes $152 billion in combined tax payments for eight out of every 10 escrowed homeowners in the U.S.
To facilitate these and other operations, the company operates over 1,000 application ecosystems. For the past several years, CoreLogic has run these applications using commercial Cloud Foundry software, hosted primarily within its on-premises data centers.
As CoreLogic’s business and data growth accelerated, the deployment footprint for commercial Cloud Foundry was expanding rapidly, which was driving up licensing and operating costs. In addition, CoreLogic scaled its infrastructure to meet the demands of its expanding data processing needs. With its commitment to innovation and leadership in the data space, CoreLogic began to explore alternative solutions for its application platform needs.
Adopting a state-of-the-art application platform
After considering various cloud and on-premises options to host its applications, CoreLogic selected Google Kubernetes Engine (GKE) as its container runtimes platform of choice. Partnering closely with Google Cloud, CoreLogic modernized these application ecosystems using the GKE stack.
The new Google Cloud-based modern application platform helps CoreLogic meet the business demands of its customers. The platform is reliable, resilient, and scalable, which allows CoreLogic to provide customers with the high-quality data and analytics they need to make informed decisions. Here are a few examples of CoreLogic’s leading analytics products built on the platform:
Discovery Platform, a property analytics product that allows businesses including CoreLogic’s core markets of property and real estate technology, mortgage lenders, marketers and insurance firms to discover, integrate, analyze, and model property insights to make critical business decisions fasterClimate Risk Analytics, designed to help government agencies and enterprises measure, model and mitigate the physical risks of climate change to the real estate industryTotal Home ValueX™ (THVx) from CoreLogic, a modern automated valuation model that is a new approach to property valuation. THV is highly accurate and reliable, allowing CoreLogic to create assessments faster, and allowing the customer to make business decisions with confidence.
In short, the shift to Google Cloud goes beyond a matter of necessity and better aligns with CoreLogic’s broader focus of adopting industry standards like Kubernetes and investing in innovative technologies.
Improving cost and operational efficiency by 30%
CoreLogic realized significant cost and operational efficiency gains from this implementation. Not only did the company eliminate all commercial Cloud Foundry licensing expenses but it also realized ongoing savings from cost reduction features like committed use discounts for Google Cloud infrastructure.
As part of its migration to Google Cloud, CoreLogic enabled multiple platform features to align infrastructure spending with business objectives and realize operational efficiencies through unlimited scale and optimization:
The platform processes tens of thousands of requests per second and operates on tens of terabytes of application data. With GKE auto-scaling as a key enabler, application containers automatically scale out and back in, responding quickly to any application transaction spikes.
CoreLogic uses GKE node pools to fine-tune infrastructure options tailored to specific workloads. CoreLogic’s Google Cloud infrastructure is much better suited for such workload distribution and scale out.
GKE’s fully managed control plane is backed by Google Site Reliability Engineers (SRE) and their reliability best practices. This means less operational toil and more productivity. CoreLogic teams no longer self-manage the Cloud Foundry control plane and data plane, which frees them up to do more valuable work. As a result of these changes, the company attracts and retains more productive development and engineering talent to run GKE on Google Cloud.CoreLogic also adopted GKE Workload Identity, allowing application workloads to access Google Cloud Services without managing Identity and Access Management (IAM) service accounts.
Achieving even higher application performance and availability
CoreLogic’s customers rely on its applications to make important decisions, so the uptime of the platform is essential to CoreLogic’s success in the data and analytics business. Automation and managed Google Cloud services are foundational components for high reliability, fewer human errors, and reduced business disruption.
CoreLogic realizes service reliability facets such as high availability and high performance using built-in GKE features, e.g., regional GKE clusters that remain fault tolerant even during complete zonal outages. Additionally, GKE’s node auto-repair and rolling updates enable zero downtime software upgrades.By defining application environments as data and utilizing Anthos’ configuration and policy management features, CoreLogic achieves improved auditability and drift management, for better operational governance.CoreLogic uses Anthos Service Mesh traffic management and telemetry to realize full observability of its application services. The platform team has unified, real-time visibility across its entire application estate. Platform operators are now empowered to troubleshoot, configure, and optimize applications using real time metrics.
CoreLogic’s ability to measure the performance of its service requests and identify slow-running services allows them to proactively resolve bottlenecks and exceed its service levels, to the benefit of its customers.
What’s next?
Looking ahead, CoreLogic has a tremendous opportunity to build on the next-generation GKE application platform foundation by taking advantage of the various current and emerging Google Cloud services and practices. The company may consider a zero-ops model, automating much of the infrastructure management with Google Cloud serverless technologies. And certainly, the business could benefit from additional insights powered by Google Cloud machine learning and data analytics. By exploring other Google Cloud services such AI and ML, CoreLogic is poised to build richer applications and bring more value to its clients.
Ready to modernize your own environment? Check out this guide to Google Cloud Application Modernization.
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