Monitoring and alerting in storage

Understanding storage demands

The Splunk platform handles vast volumes of data on a daily basis. Whether ingesting log files from various systems or processing complex search queries, core functionality is intrinsically linked with storage operations. Understanding the nuances of storage demands involves recognizing the various components that demand storage. These might range from raw indexed data to summarized datasets to search artifacts and metadata.

Data in the Splunk platform goes through several stages, each with distinct storage needs:

• Data Ingestion: As data streams into the Splunk platform, it's written to the "hot" bucket, the first of several index buckets.
• Data Roll: Over time, as data ages, it progresses from "hot" to "warm," "cold," and potentially to "frozen" buckets, each transition marking a different phase of data storage and access patterns.
• Search Artifacts: Beyond indexed data, the Splunk platform generates intermediary artifacts when processing search queries. These also consume storage temporarily.

The balance lies in ensuring that as data flows in and evolves through these stages, storage resources aren't overwhelmed, and data remains accessible and manageable.

Understanding the benefits of proactive storage monitoring and alerting

While the design of the Splunk platform efficiently manages storage, it operates optimally within the constraints of the provided storage infrastructure. Given the dynamic nature of data influx and variable query loads, storage demands can fluctuate significantly. This variability underscores the importance of proactive monitoring.

Proactive monitoring aids in:

• Capacity Planning: Recognizing growth trends allows for forward-thinking capacity provisioning, ensuring that storage is available when needed.
• Optimized Data Retention: Monitoring can highlight datasets that are rarely accessed, prompting reviews of retention policies. Perhaps some data can be archived or moved to more cost-effective storage solutions after a certain age.
• Performance Maintenance: Storage shortfalls can adversely impact system performance. By receiving timely alerts on storage thresholds, administrators can take immediate remedial actions, safeguarding system responsiveness and user experience.

In essence, proactive storage monitoring in the Splunk platform is less about firefighting and more about strategizing for efficiency and sustainability. Through well-configured alerts, Splunk administrators can ensure that the platform continues to deliver insights without storage-induced bottlenecks and interruptions.

Monitoring storage capacity

The Splunk platform offers built-in suite of tools and capabilities to assist in optimizing system performance, preemptively addressing potential storage shortfalls, and maintaining efficient data flow. In this section, we look at the tools available within the Splunk platform for monitoring storage, how to configure and interpret storage metrics and logs, and understanding storage trends for predictive needs.

Alerting for storage capacity

One way to proactively manage storage is by implementing alerting mechanisms that notify administrators when storage capacity approaches its limits. Doing so not only preserves system performance but also prevents potential data loss or interruptions.

Planning and managing capacity proactively

Before devising a storage strategy, it's essential to understand the current growth patterns. How quickly is your data volume increasing? Are there specific times when data influx is higher? Answering such questions provides a clear picture of storage needs.

• Using historical data for future projections: Historical data serves as a valuable resource when planning for the future. By studying past storage utilization trends, one can forecast future requirements. Tools like regression analysis can be useful in making these predictions. Remember, while historical data provides essential insights, you should always account for any upcoming business changes or projects that might influence data storage needs.
• SmartStore index review: While SmartStore does transfer some of the storage needs away from the Splunk server and onto the cloud, SmartStore indexes cache a local copy of any data stored in the cloud (typically any data in cold buckets) when it is required for a search. It’s important to assess the use-cases associated with any SmartStore indexes so that data is only moved to the cloud when it is no longer needed for regularly running scheduled searches.

Following best practices for proactive monitoring and alerting

• Regular Monitoring of Storage Metrics: Use Splunk platform internal tools to keep a constant check on storage metrics. This not only includes total usage but also growth rates, patterns, and any sudden spikes in data storage.
• Set Clear Storage Thresholds: Determine what constitutes a "normal" range for your storage metrics and establish clear thresholds for when storage usage becomes a concern. For instance, if 80% storage usage is your limit, proactive actions should start well before this point.
• Implement Timely Alerts: Create alerts based on the predefined storage thresholds. As you approach a threshold, the Splunk platform should notify the relevant team members, allowing them to act before storage capacity becomes a problem.
• Customize Alert Messages: Ensure that alert messages are clear, concise, and actionable. They should provide enough information to understand the issue without being overwhelming. For example, an alert could read: "Warning: Storage usage at 78%. Predicted to reach 80% in the next 48 hours."
• Analyze Growth Patterns: Regularly review how quickly your data storage needs are growing. This helps in predicting when additional storage will be required, allowing for timely capacity planning.
• Prioritize Critical Alerts: Not all alerts are of equal importance. Prioritize them based on the potential impact. Alerts related to storage capacity of hot data, given its frequent access, should take precedence over cold data alerts.
• Regular Review of Alert Thresholds: As your business and data needs evolve, so should your alert thresholds. Regularly review and adjust these based on current data growth rates and business requirements.
• Maintain a Buffer: Always maintain a buffer in storage capacity to handle unexpected spikes in data. This ensures that even when data influx is higher than usual, the system doesn't run into immediate storage issues.
• Test and Validate Alerts: Periodically, test your alerts to ensure they're working as expected. This includes checking that notifications are sent to the right people and that they're received in a timely manner.
• Monitor Search Activity for Smartstore Indexes: Utilize inbuilt tools to monitor search activity across SmartStore indexes and produce alerts if searches are regularly executed looking over long-term historical data.

Helpful resources

This article is part of the Splunk Outcome Path, Optimizing storage. Click into that path to find more ways to develop a systematic approach to managing capacity, as well as strategies for data retention, and data lifecycle management.

In addition, these resources might help you implement the guidance provided in this article:

• Splunk Blog: Storage Monitoring: A Brief Introduction
• Splunk Docs: About metrics.log
• Splunk Docs: Introspection endpoint descriptions
• Splunk Docs: Resource usage
• Splunk Docs: Getting started with alerts
• Splunk Docs: How indexing works in SmartStore
• Splunk Resource: Splunk Infrastructure Monitoring