Leading player in cloud services and security replaces Datadog with groundcover

Introduction

A leading player in cloud services and security sought to enhance their Kubernetes observability. Facing high costs with their existing solution, Datadog, they turned to groundcover for a more cost-effective, scalable, and comprehensive observability solution. The significant benefits realized from implementing groundcover include:

• Enhanced monitoring capabilities
• Cost efficient observability
• Better resource utilization
• Improved team collaboration

The Problem

Their infrastructure is primarily Kubernetes-based, with separate clusters for development, staging, and production. Their existing observability solution, Datadog, while comprehensive, became prohibitively expensive as their infrastructure scaled, bringing with it mission-critical challenges including:

• High costs: Increasing infrastructure scale led to unsustainable costs.
• Kubernetes observability: Needed deeper, real-time insights specific to Kubernetes.
• Integration: Required seamless integration with their existing tech stack.
• Real-time insights and alerting: Crucial to support their need for rapid issue resolution.

Why groundcover?

The team heard about groundcover through industry forums and validated the hype through wholehearted peer recommendations.The evaluation highlighted strong capabilities that led the company to choose groundcover over Datadog and other evaluated solutions, including:

• Kubernetes-centric insights: Possible only in a cloud-native solution catering to modern Kubernetes stacks, groundcover offers unique visibility, including entire sections of the platform dedicated to workloads, nodes, pods, and Kubernetes events data.
• Volume agnostic pricing: The company sought out a  pricing model that would be an enabler of growth and upscale and needed a solution that was based solely on the number of nodes.
• Seamless integration: groundcover’s approach enabled a smooth integration with existing Kubernetes infrastructure, compared to other general-purpose observability solutions.
• Features tailored for cloud-native architectures: Customizable dashboards and advanced visualization tools gave the company a clear and comprehensive view of their system health. In addition, detailed metrics and logging capabilities allowed them to monitor and analyze every aspect of their system.

“Compared to other solutions we evaluated, including Datadog, groundcover stood out due to its seamless integration with our Kubernetes environments and its robust feature set tailored for modern cloud-native architectures.” 

- Senior SRE Manager

The Impact

The implementation began with their staging cluster, mirroring production without risking live services. Initially, the Customer Success (CS) and Site Reliability Engineering (SRE) teams were the primary users, providing critical feedback. 

Successful deployment in staging led to wider adoption across production and development clusters, eventually extending to application development and quality assurance teams.

The company realized significant improvements in monitoring and observability processes with groundcover:

1. Increased coverage: Achieved near-complete environment coverage, including development clusters that were previously impractical due to cost constraints. This enhanced issue detection and resolution across all development pipeline stages.
2. Improved team alignment: groundcover's user-friendly platform and detailed insights fostered better collaboration among DevOps, SRE, application development, and QA teams. This improved communication and streamlined processes, enhancing operational efficiency.
3. Cost efficiency and resource utilization: Delivered significant cost savings and optimized resource use.

“With groundcover, we achieved near-complete coverage of our environment, including development clusters that were previously impractical to monitor with Datadog due to cost constraints. This comprehensive coverage has enhanced our ability to detect and resolve issues across all stages of our development pipeline.”

- Senior SRE Manager

Detailed performance improvements

• Scalability: groundcover seamlessly integrated with all clusters, scaling effortlessly to handle increased loads and maintaining consistent performance.
• Complex workloads: Effectively managed diverse microservices with varying resource demands, providing granular visibility and real-time insights. For example, resolving a resource bottleneck in a high-traffic service led to a 15% improvement in response times.
• Dynamic environments: Adapted to frequently changing clusters and nodes for testing and development without requiring extensive reconfiguration. During a load testing phase, groundcover handled increased data and activity seamlessly.
• Comprehensive visibility: Provided visibility into previously under-monitored areas, improving stability and performance across the development lifecycle by enabling early issue detection and resolution.

Data security and privacy

groundcover's unique inCloud architecture, which deploys with out-of-the-box local storage, enables complete visibility without the need to stream any data outside your environment. This aligned perfectly with the company’s stringent data privacy and security requirements:

• Data privacy compliance: Demonstrated compliance with global data privacy regulations.
• Secure data handling: Underwent thorough review of data handling practices, encryption protocols, and compliance with industry standards.

Future Plans

The company plans to continue expanding groundcover's use to additional teams and environments. The collaboration aims to leverage groundcover's full potential, exploring new features and updates to further support their observability and monitoring needs.