Grafana Cloud Shines Bright After Testing It Out!

Tiny Big Spark Newsletter: Grafana Cloud Shines Bright After Testing It Out!

Welcome to the latest edition of Tiny Big Spark, where we explore the advancements poised to elevate your infrastructure.. As an Engineering Leader, I’m dedicated to identifying solutions that enhance our infrastructure while fostering enthusiasm across our teams. This month, we’re focusing on observability—a vital component for ensuring resilience, performance, and proactive maintenance across our extensive environment, which includes infrastructure devices and appliances such as switches, routers, and storage arrays. After thoroughly testing out various solutions, we’ve committed to Grafana Cloud as our leading observability platform, and I’m excited to share why it’s illuminating our FinTech-driven landscape with its AI capabilities, industry-standard tools, and exceptional cost benefits for our business and operational needs. Join me for an insightful look into our findings, including a detailed exploration of Sift Investigation—a tool that’s set to help us achieve our goal of predicting hardware challenges with precision, as we prepare to fully implement it!

Why Observability Is Our Strategic Advantage

Envision managing a dynamic ecosystem of servers, virtual machines, and infrastructure devices and appliances—switches, routers, storage arrays—all collaborating to support our FinTech operations. That’s our reality, and observability is the strategic advantage that keeps it thriving. It goes beyond merely monitoring metrics; it’s about gaining deep insights, anticipating challenges, and ensuring our systems operate seamlessly. Observability will enable us to:

• Proactively Address Issues: Identify anomalies across compute, storage, networking, and hardware to prevent disruptions.

• Anticipate Hardware Challenges: Leverage Redfish exporters to predict disk or DIMM failures, minimizing downtime across our infrastructure devices and appliances.

• Ensure Compliance Seamlessly: Meet FinTech regulations by keeping our data exclusively in Japan, aligning with our commitment to regulatory excellence.

• Streamline Incident Response: Enhance on-call workflows with tools that make incident resolution efficient and effective.

Without observability, we’d be navigating this ecosystem without clarity—not an option for a team like ours. So, we set out to find the ideal observability solution, and after testing out various options, Grafana Cloud has earned our commitment and enthusiasm!

Why Grafana Cloud Emerged as Our Top Choice After Testing

As an Engineering Leader, I prioritize solutions that empower our teams, align with industry standards, deliver exceptional value, and optimize costs for our business and operations. Grafana Cloud excelled in all these areas during our evaluation, outperforming competitors like Datadog and securing our commitment to move forward. Here’s why we’re eager to begin this journey with Grafana Cloud:

• Building on Our OSS Grafana Expertise: We’ve long relied on open-source Grafana (OSS Grafana) to create insightful dashboards and manage our metrics effectively. When we tested Grafana Cloud, it felt like a seamless evolution—like transitioning from a trusted tool to a more powerful, cloud-enhanced version. Our team’s extensive experience with OSS Grafana allowed us to dive in confidently, crafting dashboards and setting up alerts with ease. This familiarity gives us a strong foundation as we prepare to fully adopt Grafana Cloud.

• Leveraging Industry-Standard Prometheus Exporters: Grafana Cloud utilizes Prometheus exporters to collect metrics, which is widely recognized as an industry standard in observability. From Node Exporter for system metrics to our custom Redfish exporters for hardware telemetry, Prometheus provides a standardized, scalable approach to monitoring our infrastructure devices and appliances. During our evaluation, we saw firsthand how Prometheus seamlessly integrated with our existing workflows, positioning us for a robust, future-proof observability strategy that aligns with industry best practices.

• AI-Driven Insights with Sift: Grafana Cloud’s Sift Investigation impressed us with its AI-driven anomaly detection and hardware prediction capabilities. It’s like having a forward-looking tool that anticipates when a disk or DIMM might fail—more on this innovation below!

• Core Lesson: Significant Cost Benefits for Business and Operations with Grafana Cloud: One of the most compelling reasons for choosing Grafana Cloud was the substantial cost savings it offers for our business and operational expenses. Our testing revealed that Grafana Cloud’s Adaptive Logs and Adaptive Metrics features intelligently optimize data storage and ingestion, reducing operational costs by 50–80% compared to alternatives like Datadog. To illustrate this core lesson, let’s break down the numbers using examples for infrastructure monitoring (1,000 hosts for Datadog), log ingestion (1 TB/day), and metrics (4,000,000 raw metrics from our infrastructure devices and appliances).Infrastructure Monitoring Cost Comparison (1,000 Hosts for Datadog):Cost Comparison Formula for Hosts:

  • Datadog’s pricing for infrastructure monitoring (Pro tier) is $23 per host per month, where a host is any OS instance (e.g., physical servers, VMs, containers, databases).

  • Grafana Cloud’s Pro tier starts at $15 per host per month, with additional savings from cost optimization features like Adaptive Metrics.

• Core Lesson: Grafana Cloud’s cost optimization features, including Adaptive Logs and Metrics, can save our business between $2.7 million and $2.9 million annually for 1,000 hosts, 1 TB of logs per day, and 4 million raw metrics from our infrastructure devices and appliances, while still providing robust observability. When scaled to our full infrastructure, the savings could be even more significant. Additionally, the Flexible Spend Commit Card allows us to allocate our budget across all Grafana products without rigid product-specific or monthly commitments, with multi-year rollovers for unused funds. This flexibility ensures we can scale efficiently while optimizing our investment, directly benefiting our business by reducing operational overhead and allowing us to allocate resources to other strategic initiatives. These savings are a game-changer, enabling us to redirect funds toward innovation and growth, all while maintaining top-tier observability across our infrastructure.

• Compliance by Keeping Data in Japan: As a FinTech company, keeping our data exclusively in Japan is a non-negotiable requirement for regulatory compliance. Grafana Cloud’s ability to store data solely in Japan ensures we’ll meet these standards while maintaining data sovereignty, a key factor that stood out during our testing.

• A Flexible Fallback Option: If needed, we can transition to the open-source Grafana stack, providing us with the flexibility to evolve without being tied to a proprietary system—a strategic benefit for our long-term plans.

Our evaluation revealed that Grafana Cloud isn’t just a solution—it’s a strategic partner that aligns with our needs, from predictive insights to significant cost savings for our business and operations, all while integrating seamlessly into our workflows. We’re eager to see the impact it will have once we fully implement it!

Sift Investigation: A Glimpse into the Future of Predictive Observability

A standout feature from our testing was Sift Investigation, Grafana Cloud’s AI-powered tool that’s set to help us achieve a key goal: predicting hardware failures with precision. Sift uses machine learning to detect anomalies and anticipate hardware issues before they impact our FinTech operations. During our evaluation, it offered an exciting preview of what’s possible. Here’s how it’s poised to help us realize this goal across our infrastructure devices and appliances once we fully implement Grafana Cloud’s AI/ML capabilities and Sift:

How Sift Investigation Works

Sift leverages Grafana Cloud’s unified observability stack, which includes Prometheus for metrics, Loki for logs, and Tempo for traces, to gather insights from every corner of our infrastructure. Here’s the detailed process we observed during testing:

• Data Ingestion: Sift collects high-cardinality data from our infrastructure and devices using Prometheus exporters, including our custom Redfish exporters for hardware telemetry (such as disk SMART data, DIMM error rates, and temperature sensors), alongside OpenTelemetry for application and network insights.

• Machine Learning Analysis: Sift employs unsupervised ML models to establish baseline behavior for our environment—such as typical disk I/O patterns, CPU usage, or network latency. It then identifies anomalies by detecting deviations, even in our dynamic, multi-device setup. During our testing, we saw Sift flag an unexpected spike in disk latency on a storage appliance with impressive speed.

• Predictive Capabilities: Sift doesn’t just identify issues—it anticipates them. It analyzes trends to forecast potential failures, such as a disk at risk due to increasing reallocated sectors or a DIMM showing rising error rates. This predictive insight will allow us to replace hardware proactively, ensuring system reliability.

• Root Cause Analysis: Sift correlates anomalies across metrics, logs, and traces, providing a unified view to pinpoint issues efficiently. In our testing, we observed it linking a network latency spike on a switch to a Redfish-reported temperature anomaly, enabling us to address overheating risks preemptively.

• Actionable Alerts with Clarity: Sift generates stateful alerts with detailed context, visualized on Grafana dashboards via the Sift panel. With role-based access controls (RBAC), our teams can collaborate securely, diving into issues across our infrastructure devices and appliances with ease.

Sift in Action: Achieving Our Goal of Hardware Prediction with Grafana Cloud

One of our primary goals is to predict hardware failures to ensure minimal downtime across our infrastructure, and Grafana Cloud’s AI/ML capabilities, paired with Sift, are set to make this a reality. While we haven’t fully implemented this yet, here’s how we aim to achieve this goal with Grafana Cloud based on our testing:

• Disk Failure Predictions: We aim to use Sift to analyze Redfish data and detect early warning signs, such as increasing reallocated sectors or wear-leveling issues on SSDs. Sift’s ability to provide failure timelines will enable us to schedule disk replacements during maintenance windows without disruption, a capability we’re excited to fully leverage once we implement Grafana Cloud.

• DIMM Failure Prevention: Our goal is to have Sift monitor DIMM error rates, temperature, and voltage anomalies, identifying potential failures before they impact a system. For example, Sift could flag a server with rising memory errors, allowing us to address it proactively—something we’re eager to put into action with Grafana Cloud’s AI/ML tools.

• Device-Level Insights: Across our infrastructure devices and appliances, we plan to use Sift to predict issues like fan failures or power supply degradation. With Grafana Cloud and Sift, we’re on the path to ensuring comprehensive hardware reliability, a goal we’re committed to achieving as we move forward.

Sift Investigation Features That Impressed Us

• Customizable Analysis: We can tailor Sift to focus on specific metrics (like disk latency or memory errors) or combine data for deeper insights—ideal for our diverse environment.

• Sift Panel Visualization: Sift allows us to visualize anomalies and predictions directly on Grafana dashboards, with drill-down capabilities to explore root causes across our infrastructure devices and appliances.

• Automated Workflows: Sift integrates with Grafana Incident Response & Management (IRM), triggering alerts and workflows for proactive resolution. For instance, a predicted disk failure would notify our on-call team to schedule a replacement.

• Scalability Excellence: Sift handled the substantial data volume from our infrastructure devices and appliances with ease, leveraging Grafana Cloud’s efficient storage and processing capabilities.

Why Sift Has Us Enthusiastic

Sift transforms observability into a proactive discipline, aligning perfectly with our goal of predicting hardware failures. During our testing, it acted like a forward-looking guide, offering a glimpse of how it will ensure our FinTech workloads remain robust while streamlining our operations once we fully implement Grafana Cloud’s AI/ML capabilities and Sift.

Benefits We’re Eager to Realize

For Our Customers:

• Uninterrupted Operations: Sift will predict hardware failures across our infrastructure devices and appliances, ensuring smooth and reliable performance.

• Regulatory Confidence: Keeping our data exclusively in Japan will ensure compliance with FinTech regulations, reinforcing our customers’ trust.

• Cost-Effective Innovation: The cost savings from Adaptive Logs, Adaptive Metrics, and the Flexible Spend Commit Card will allow us to reinvest in customer-focused advancements, ensuring we deliver value without compromising quality.

For Our Infrastructure Teams:

• Proactive Maintenance: Sift with Redfish exporters will enable us to prevent disk and DIMM failures, enhancing our operational efficiency and reducing unexpected disruptions.

• Efficient Incident Response: Grafana IRM will streamline on-call workflows, with data stored exclusively in Japan for added assurance, allowing our teams to focus on innovation rather than firefighting.

• Scalability with Familiarity: Prometheus exporters and our OSS Grafana expertise will ensure seamless scaling, with an open-source fallback for strategic flexibility, all while keeping business and operational costs manageable as we grow.

Looking Ahead: Grafana Cloud Lights the Path Forward

Grafana Cloud, with Sift Investigation, is poised to become the cornerstone of our observability strategy, illuminating the path to resilience, cost efficiency, and compliance across our infrastructure devices and appliances. Our expertise with OSS Grafana and the reliability of Prometheus exporters give us confidence that we’re on the right track, while Sift will help us achieve our goal of predicting hardware failures. The substantial cost benefits we observed for our business and operations—potentially saving millions annually compared to alternatives—further solidify Grafana Cloud as a smart investment for our future. In the next Tiny Big Spark, we’ll explore our security module, sharing how we’re safeguarding our infrastructure from emerging threats—stay tuned for more insights!

A Tiny Big Spark for What’s to Come

Grafana Cloud has ignited a spark of anticipation in our infrastructure, combining industry-standard Prometheus exporters, our open-source Grafana expertise, Sift Investigation’s predictive capabilities, and significant cost savings for our business and operations, paving the way for an environment that operates with precision. As your Engineering Leader, I’m proud to champion solutions like Grafana Cloud—ones that empower our teams, support our customers, and lay the groundwork for a future of efficiency and innovation, all while delivering exceptional value. We’ve committed to this journey, and I’m eager to see the transformative impact it will bring once we fully implement it. Here’s to more tiny sparks that lead to remarkable outcomes! Until next time, let’s continue to drive excellence together.

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