Dazz / ScaleOps – Case Study

About Dazz

Dazz delivers unified security remediation for fast-moving security and development teams. We plug into the tools that find code flaws and infrastructure vulnerabilities, cut through the noise, prioritize issues that matter most, and deliver fixes to owners, all in a developer-friendly workflow. As a result, our customers are able to massively streamline their remediation processes and reduce exposure in hours instead of weeks. Dazz is becoming the standard for leading Application Security Posture Management (ASPM), Continuous Threat and Exposure Management (CTEM), and DevSecOps practices.

Key Results

50% reduction in needed CPU and Memory

By implementing the ScaleOps platform, Dazz nearly doubled the number of running workloads and pods while maintaining the same operational costs. Utilizing automatic pod rightsizing across all their Kubernetes clusters, Dazz significantly optimized resource allocation. ScaleOps continuously tracked CPU and Memory usage of pods and automatically adjusted resource requests to meet real-time demand. This dynamic resource management eliminated waste, improved cluster performance, and enhanced availability. As a result, Dazz could scale its services effectively to meet growing business demands without incurring additional infrastructure expenses.

Seamless resource management across all environments

ScaleOps automated resource management across Dazz’s Dev, Staging, and Production environments. By deploying ScaleOps throughout their development pipeline, Dazz ensured consistent performance optimization at every stage. The platform’s ability to automatically adjust resource requests based on real-time usage meant that each environment operated efficiently without manual intervention, whether for development, testing, or live deployment. This automation enhanced cluster performance and availability, allowing Dazz to focus on innovation rather than routine maintenance.

Rapid & smooth onboarding onto all clusters

Using ScaleOps’ self-hosted architecture and frictionless installation process, Dazz successfully and effortlessly onboarded ScaleOps onto all of their Kubernetes clusters quickly and efficiently. The self-hosted model allowed Dazz to deploy the platform within their own secure infrastructure, aligning with their compliance and security requirements. The straightforward installation process required minimal configuration and no significant downtime, enabling Dazz to implement automatic pod rightsizing across all clusters rapidly. This quick onboarding facilitated immediate benefits from resource optimization without disrupting existing operations.

The Challenge

Manual Management of Pod Requests

The manual approach to pod resource requests at Dazz led to inefficiencies and inconsistencies in resource allocation. Estimating the precise CPU and memory requirements for each workload was time-consuming, often resulting in over-provisioned resources and wasted costs.

High Reliability for Production Environments

For Dazz, maintaining high reliability in production environments was crucial. Any fluctuation in resource availability risked interruptions in service, potentially affecting customer trust and tarnishing the brand’s reputation. ScaleOps is needed to deliver efficient resource allocation and ensure stability and reliability.

Managing Resources Across Multiple Environments

Dazz operates across Production, Staging, and Development environments, each with unique characteristics and demands. For example, while Production required consistent uptime and reliability, the Development and Staging environments required flexibility for testing and adjustments. Manually managing these differences was complex and time-consuming.

Hundreds of different Workloads

Dazz’s infrastructure supports a variety of workloads, each with its own CPU and memory requirements. Variability in developer-defined resource requests often led to inefficiencies, with resources either over- or under-provisioned. Managing these inconsistencies became increasingly challenging, especially as Dazz scaled its operations.

The Solution

Automation across environments

ScaleOps automated Dazz’s containerized workloads across various cloud-native technologies, including their hybrid setup. This automation ensured optimal resource requests, adjusting in real-time to workload demands and optimizing both cost and performance across their on-premises and cloud clusters.

Optimization of Critical Workloads

Using advanced automation, ScaleOps effectively optimized Dazz’s critical production workloads, which required high availability. The platform ensured precise resource allocation, maintaining reliability and performance without causing any disruption. This robust operational environment bolstered Dazz’s confidence in consistently meeting customer expectations.

Out-of-the-Box Scaling Policies

ScaleOps provided predefined and auto-assigned scaling policies, making it easy for Dazz to optimize different workloads with varying characteristics and scaling goals. This resulted in a zero-touch experience that maximized cost savings and performance. The flexibility of these policies allowed Dazz to tailor resource management to specific needs without extensive manual configuration.

The Impact

Cost Savings with Increased Workload Capacity

By automatically right-sizing resources, ScaleOps reduced Dazz’s required resources by 50%, effectively doubling Dazz’s production workload capacity without increasing costs. This optimized resource usage translated into substantial cost savings and a scalable foundation for future growth​​.

Automated Resource Management Across All Environments

Within days, Dazz was able to onboard ScaleOps across all clusters. This seamless, hands-free setup allowed Dazz’s teams to quickly transform their approach to resource management, automating each cluster’s rightsizing while maintaining the flexibility to monitor and adjust as needed​​.

Freedom for Engineering Teams

By eliminating the need for manual rightsizing, ScaleOps freed Dazz’s engineers to focus on delivering valuable features and improvements. With ScaleOps automating resource adjustments, Dazz’s engineering teams could allocate more time to development work, improving productivity and innovation​​.

Dazz’s experience with ScaleOps showcases how automated resource management can drive both operational efficiency and cost savings across Kubernetes environments. ScaleOps’ powerful optimization features have transformed Dazz’s resource allocation, allowing the company to manage larger workloads without increased costs. By adopting ScaleOps, Dazz achieved consistent, optimized resource utilization, strengthened reliability, and empowered engineers to focus on high-value tasks. This case highlights ScaleOps’ potential to help organizations achieve a scalable, efficient Kubernetes infrastructure designed to meet dynamic business needs.