In the cloud computing landscape, Amazon Managed Service for Prometheus has emerged as a robust solution for managing time-series data. With recent updates, the service now offers a higher default active series limit of 50 million per workspace, significantly up from the previous 10 million. This comprehensive guide will walk you through the implications of this change, explore how to effectively use the service, and provide actionable insights to maximize its capabilities.
What is Amazon Managed Service for Prometheus?¶
Amazon Managed Service for Prometheus is a fully-managed service designed to simplify the process of collecting, storing, and querying Prometheus metrics. It enables developers to monitor their containerized applications efficiently without the underlying complexities of managing the Prometheus server and its associated infrastructure.
Key Features:¶
- Scalability: Automatically scales to meet demand, accommodating significant growth in monitoring needs.
- High Availability: Designed for resilience and uptime, ensuring your observability tools are always operational.
- Simplicity: Reduces the operational burden associated with deploying and maintaining Prometheus instances.
The New Active Series Limit¶
As of July 30, 2025, the default limit for active time series in Amazon Managed Service for Prometheus has been increased to 50 million per workspace. This change is pivotal for users managing large datasets, making it easier to scale without needing to request limit increases.
Why is This Significant?¶
- Reduced Friction: Previously, users had to go through a limit increase request process to manage over 10 million active series, which could introduce delays in scaling their monitoring solutions.
- Enhanced Monitoring Capabilities: As applications scale and become more complex, the need for monitoring a higher volume of time-series data is inevitable. This increase allows companies to monitor more metrics without the overhead of managing limits actively.
- Cost Efficiency: Users can optimize costs by eliminating the need to request additional series limits and making better use of available resources.
How to Utilize the New Limits Effectively¶
Understanding how to leverage this new 50 million series limit can enhance your monitoring strategy. Here are some actionable steps to maximize the benefits of the increased limits.
1. Monitor More Metrics¶
With a higher active time series limit, consider monitoring additional metrics that could provide deeper insights into application performance.
- Application Performance Metrics: Track response times, error rates, and resource utilization.
- Infrastructure Metrics: Monitor CPU, memory usage, disk I/O, and network latency.
Action Step:¶
Build dashboards that visualize these metrics in a way that stakeholders can easily understand, enhancing your team’s ability to respond to issues.
2. Implement Effective Labeling Strategies¶
Efficient labeling within your metrics can help in efficiently querying and managing thousands or millions of time series.
- Use Consistent Naming Conventions: Ensure that metric names and labels are clear and descriptive.
- Leverage Relational Labels: Create hierarchical structures where necessary, allowing you to filter results easily.
Action Step:¶
Review your current labeling strategy and refine it to align with best practices for metric naming.
3. Optimize Query Performance¶
As the number of active series increases, the complexity of queries can also grow. To ensure efficient querying:
- Use Aggregation Functions: Apply functions like
sum,avg, ormaxto reduce the amount of data returned. - Filter Early: Always filter as much as possible before applying aggregation to minimize computational load.
Action Step:¶
Experiment with different query structures to find the most performant options for your use case.
Integrating Amazon Managed Service for Prometheus¶
For organizations already using AWS, integrating the Amazon Managed Service for Prometheus with existing systems is straightforward. Here are some tips to facilitate smooth integration:
1. Leverage IAM for Security¶
Ensure that access to your Prometheus workspaces is safeguarded using AWS Identity and Access Management (IAM) policies.
- Define Roles and Policies: Create specific roles that allow different services or team members the minimum necessary permissions.
- Audit Regularly: Regularly review and update IAM permissions to ensure compliance and prevent unauthorized access.
2. Use AWS Native Tools¶
Integrate with other AWS tools to enhance your workflows.
- Amazon CloudWatch: Use CloudWatch for alerts on thresholds defined in your Prometheus metrics.
- AWS Lambda: Trigger Lambda functions in response to specific metrics, automating responses to certain conditions.
3. Explore the AWS Ecosystem¶
Take advantage of other AWS services to complement your observability needs.
- AWS X-Ray: Utilize X-Ray for distributed tracing in microservices architectures.
- Amazon EKS: If you’re using Kubernetes, EKS can be an excellent environment to leverage Prometheus in containerized applications.
Frequently Asked Questions¶
What is an Amazon Managed Service for Prometheus workspace?¶
A workspace is a dedicated logical space for storing and querying Prometheus metrics, ensuring data is organized and easily accessible.
How can I request an increase beyond the default limit?¶
If you need more than the 50 million active time series, you can submit a service limit increase request through the AWS Management Console.
Is there any cost associated with the Amazon Managed Service for Prometheus?¶
Yes, costs are incurred based on the volume of active time series, data ingested, and stored. Ensure to check the pricing page for the latest details.
Summary and Future Insights¶
The update to Amazon Managed Service for Prometheus significantly alters the landscape for those monitoring time-series data on AWS, allowing organizations to seamlessly scale without worrying about limits.
Key Takeaways:¶
- Increased Limit: 50 million active series per workspace, up from 10 million.
- Enhanced Monitoring: Provides an opportunity to track more metrics for better insights.
- Simplified Management: Reduces the operational complexity involved in scaling monitoring systems.
As the emphasis on observability grows in cloud-native architectures, services like Amazon Managed Service for Prometheus will be pivotal in maintaining performance and reliability.
For more insights on monitoring and observability within AWS, be sure to check our blog for the latest updates and best practices.
To learn more about Amazon Managed Service for Prometheus, visit the product page today!
In conclusion, the Amazon Managed Service for Prometheus with its new limits serves as a powerful tool in the realm of time-series monitoring and management.