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Optimize Metrics Costs in Coralogix by Adjusting Your Scrape Interval

Last Updated: Feb. 26, 2024

Coralogix’s metrics costs are influenced by the amount of metric data ingested, which is significantly impacted by the scrape interval settings of your OpenTelemetry Collector or Prometheus Agent. Adjusting your scrape intervals allows for more effective data ingestion management, leading to optimized costs and efficient usage.

The Optimal Scrape Interval

Why 60 Seconds Makes Sense

After thorough analysis and consideration of various monitoring needs, it’s evident that a 60-second scrape interval is the most balanced and universally applicable approach for a wide array of use cases. Here’s why:

  • Cost-Effectiveness: A 60-second interval ensures you’re not over-collecting data, which can quickly escalate costs without providing proportional value. This interval is long enough to capture meaningful trends and metrics, yet short enough to control data ingestion volumes — and thus costs.
  • Data Quality and Relevance: For the vast majority of monitoring scenarios, metrics collected every minute provide a sufficient level of detail to observe system performance, identify issues, and make informed decisions. This frequency offers a practical balance, ensuring data is both manageable and meaningful.
  • Reduced System Load: Collecting data at a more frequent interval can put unnecessary load on your systems and the data collection infrastructure. A 60-second interval minimizes this impact, preserving system resources for your core business operations.
  • Streamlined Data Management: With data collected at a consistent and reasonable rate, storage, analysis, and management become significantly more straightforward. This efficiency allows your team to focus on leveraging data insights rather than handling them.

Addressing Auto-Scaling Use Cases

While a 60-second scrape interval is recommended for most scenarios, auto-scaling environments present unique challenges that might necessitate a different approach. Specifically, the need for rapid scaling based on real-time demands requires a more nuanced strategy:

  • Critical Metrics Focus: In auto-scaling scenarios, it’s essential to identify which metrics most indicate the need to scale. Collecting these critical metrics at a shorter interval, while maintaining a 60-second interval for less sensitive data, offers a balanced solution. This approach ensures that the most current and relevant data inform your auto-scaling decisions without overwhelming your system with excessive metric collection.

Adopting a dual-interval strategy allows you to enjoy the benefits of a balanced, cost-effective monitoring setup for general purposes while still catering to the specific needs of auto-scaling scenarios. This tailored approach optimizes your monitoring efficiency and cost, ensuring that you have the necessary data when it matters most, without incurring unnecessary expenses.

Adjusting Your Scrape Interval

OpenTelemetry Collector and Prometheus Agent Configuration: Review and adjust the scrape_interval setting in your configuration files to adopt the 60-second standard for general monitoring and consider shorter intervals for critical metrics affecting auto-scaling decisions.

OpenTelemetry Collector:

		    - job_name: 'otel-collector'
		      scrape_interval: 60s
		      - targets: [''] 
		    - job_name: 'node-exporter'
		      scrape_interval: 15s
		      - targets: ['localhost:9100'] #Auto-Scaling/Critical metrics

This adjustment is foundational to achieving a more cost-effective and efficient monitoring setup.

By thoughtfully setting your scrape intervals, you embrace best practices for most monitoring scenarios while accommodating the specialized needs of auto-scaling environments. This strategic approach ensures that your monitoring practices are cost-efficient and highly responsive to dynamic operational requirements.


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