Data Tiering: 5 Observability and Security Scenarios Where You Can Save Millions

We hear it time and time again: "data is growing at a rapid and ever-accelerating pace and our costs are growing too."

This is why implementing a data tiering strategy across observability and security tools is essential for optimizing costs while maintaining critical visibility into system performance, uptime, and service availability. By structuring logs, metrics, traces, and events into tiers you ensure that critical data is accessible immediately while reducing costs for less essential data. Even with Splunk's new SVC pricing, it can be difficult for businesses to find an approach that makes sense for the business. For example, your setup could be Splunk as the top tier for real-time insights, Edge Delta as a middle tier for pre-processing and anomaly detection, and AWS S3 as a long-term storage solution. this strategy allows enterprises to strike a balance between cost efficiency and maintaining the performance and availability of mission critical systems.

Enter Telemetry Pipelines, which can help you optimize your data tiering strategies by giving you the control and flexibility to route observability and security data based on its priority and retention requirements. They enable the real-time filtering, aggregation, and transformation of these logs, metrics, traces, and events before forwarding them to different tiers, ensuring only the most critical data is sent to high-cost platforms like Splunk. By pre-processing data with tools like Edge Delta, Telemetry Pipelines are fully integrated to reduce the volume of non-critical information that reaches expensive storage layers. This approach allows enterprises to balance cost and performance, ensuring critical insights are available instantly while long-term data is archived efficiently in cost-effective solutions like S3. Additionally, telemetry pipelines can automate the movement of data between tiers based on predefined rules, further streamlining data management and compliance efforts. Let’s explore five specific technical scenarios where this Data Tiering approach can be applied.

Scenario 1: Kubernetes Logs in Production vs. Development Environments

Dev >> Test >> Stag >> Prod -- there are different things you're looking for in each of these environments, rarely is there a one size fits all approach where the same architecture can or should be used across them all. In a large-scale Kubernetes deployment, logs from production services like API Gateway traffic or database queries are critical for real-time operational visibility. These logs help detect issues such as slow queries or high request rates, which directly impact customer experience. To maintain uptime, you would configure Splunk to ingest these logs for immediate monitoring and alerting. Splunk's flexible and powerful search capabilities allow teams to quickly troubleshoot and resolve performance issues while having access to the "why" of the root cause. However, logs from non-production environments, like development or staging clusters, often generate large volumes of data with less immediate operational value. Instead of sending all this data to Splunk, and intermediate tier such as Edge Delta can act as layer to pre-process and filter logs, forwarding critical events or anomalies while still giving full search capabilities across all raw data. Most of the bulk and non-critical development/test or debug logs could then be sent directly to S3 (if needed), where they are stored for long-term reference. By taking this approach, you are reducing the load on Splunk to keep costs down while maintaining appropriate access across all your data.

Scenario 2: E-Commerce Platform Monitoring During High-Traffic Events

For a typical e-commerce platform, key logs like payment failures, inventory updates, and shopping cart events need real-time processing to ensure a smooth customer experience, particularly during high-traffic events like holidays or Black Friday. These mission-critical logs should flow directly into your premium tier (we're using Splunk as an example) to ensure rapid detection and response to issues like payment processing delays or inventory mismatches. However, background logs from less essential services, such as internal system checks or batch processing jobs, can be routed into Edge Delta. Edge Delta's Telemetry Pipelines will pre-process all of the logs, sending only significant trends or warnings—such as an increase in job failures, as well as other subsets of data to Splunk. The question can come up "Well what if I need my other data" but rest assured, it can all be stored in S3 for post-event analysis or compliance purposes. This approach allows the business to optimize its cost structure by keeping Splunk focused on high-priority events while offloading less critical usage to cheaper storage tiers.

Scenario 3: Security Incident Detection and Response

In the realm of security monitoring, real-time detection of threats is paramount to prevent breaches or mitigate damage. Even though we know the statistics on the average time it takes to detect IOCs, it's still accepted that security logs such as firewall logs, failed login attempts, privilege escalation attempts, and network intrusion detection alerts should flow directly into Splunk for immediate analysis and alerting. Splunk’s real-time SIEM and correlation capabilities allow security teams to detect, investigate, and respond to threats in extremely quickly. However, for logs related to routine searches, such as looking for specific logs or events, Edge Delta can also give efficient log search access to all of your data. Finally, the entirety of your logs, particularly for use cases related to internal audits or compliance scans, can be accessed from S3 which in this setup is being used for long-term retention, ensuring these logs are available for forensic analysis or regulatory purposes without incurring high storage costs in Splunk.

Scenario 4: Financial Transaction Logs for Compliance and Audits

In industries with strict regulatory requirements, like finance, you may be required to store financial transaction logs, authentication records, and audit trails for several years. Splunk should not be used as a storage destination, so instead of ingesting all this data into Splunk, which could be extremely costly, you can take advantage of this tiered storage approach. By using Telemetry Pipelines, you can enable real-time transaction monitoring—such as credit card failures, payment gateway errors, or suspicious account activities in Splunk, where real-time analysis and alerting are critical to preventing fraud or system failures. Meanwhile, all logs can be sent to Edge Delta for direct full log search access. Finally, S3’s cheaper, scalable storage, especially with cold storage options like S3 Glacier, is ideal for keeping long-term compliance data accessible when needed for audits but without incurring high ongoing storage costs.

Scenario 5: Application Performance Monitoring in a Multi-Cloud Environment

In a multi-cloud environment where your business spans multiple providers (e.g., AWS, Azure, Google Cloud), application performance metrics, system logs, and error rates come from various services, and egress costs can make things downright infeasible. Telemetry Pipelines can enable Splunk to ingest only aggregates and the most critical logs in real time, such as those that report application downtime, cloud API throttling, or severe performance degradation. However, not every log, especially those such as debug, may not need real-time processing. In this case, Edge Delta can be employed to collect and pre-process all data including these less-critical logs, sending critical alerts to Splunk while storing the full data in S3. This allows for optimized use of Splunk for urgent multi-cloud issues while maintaining a cost-effective, unified view of performance data across your cloud environments. Again, at the risk of being repetitive, you would use S3 as an archival layer once again.

By using Telemetry Pipelines to enable this tiered approach, enterprises can optimize costs while maintaining critical real-time visibility into the system. we explored 5 scenarios where the setup was similar: Splunk provides fast access to high-priority data, Edge Delta is the intermediary solution to provide balance, and AWS S3 ensures cost-effective long-term storage, providing an adaptable and efficient solution for modern infrastructure observability.