Amazon Redshift Cost Optimization best practices

Amazon Redshift Provisioned

Cluster compute configuration

Make sure your cluster is appropriately sized for your workload. Selecting the right instance type and the optimal number of nodes is crucial for cost optimization when you are using provisioned cluster

1. For production workloads that runs nearly 24/7, consider purchase-reserved-node-instance for either 1 year or 3 years to achieve significant cost savings compared to on-demand pricing.
2. If you are utilizing an on-demand cost structure, pause clusters based on your workload requirements to manage costs effectively. https://www.youtube.com/watch?v=761UNvtjsFQ
3. RA3 instance types allow you to share data between different clusters without duplicating data. Utilize data sharing between clusters where applicable to reduce storage costs and avoid the need for building data pipelines. https://docs.aws.amazon.com/redshift/latest/dg/datashare-overview.html
4. Consider evaluating Redshift-Serverless as a potential solution for enhancing cost efficiency. Redshift Serverless operates on a pay-as-you-go basis, featuring automatic scaling to match your workload demands and automatic pausing when no active tasks are present.

Redshift Provisioned Cluster Spectrum Usage

Using Amazon Redshift Spectrum, you can efficiently query and retrieve structured and semi structured data from files in Amazon S3 without having to load the data into Amazon Redshift tables. In Redshift provisioned cluster based on the size of data scanned ($5.00 / TB), charged with a 10 MB minimum per query. You can implement several strategies to control the Spectrum cost, including setting usage limits, optimizing data storage formats, partition S3 files to minimize data scanning and improve query performance.

1. Monitor Redshift-spectrum-query-charges periodically and take necessary actions to reduce scanning to minimize cost
2. You can manage-and-control-your-cost-with-amazon-redshift-spectrum by putting limits on usage
3. Follow redshift spectrum best practices to optimize cost.

Redshift Provisioned Concurrency Scaling Usage

Amazon Redshift's Concurrency Scaling when enabled, automatically adds cluster capacity when there's an increase in read and write query volume. Whether queries run on the main cluster or a concurrency-scaling cluster, users always have access to the most up-to-date data. Concurrency scaling has a additional per second charges out side of free tier. manage-concurrency-scaling-cost

High daily usage of concurrency scaling even after following best practices, suggests your main cluster lacks capacity for current workloads, leading to high on demand costs beyond the free tier. To optimize your spending, consider two alternatives:

1. purchase-reserved-node-instance for cost savings
2. Modernize your architecture by implementing Redshift datashare, which allows to isolate workloads to reduce resource conflicts and improve scalability & cost efficiency

Amazon Redshift Serverless configuration

Amazon Redshift Serverless automatically handles infrastructure management and scaling of your analytics workloads while offering flexible payment options. You can choose to pay on-demand, purchase reserved capacity, or implement a hybrid approach combining both payment methods to optimize your costs.

https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-billing.html

Although Amazon Redshift Serverless automatically scales to meet workload demands, implementing RPU limits is crucial for cost management Setting maximum RPU hours can help you meet your price/performance requirements while maintaining predictable costs. Best practice involves monitoring actual usage patterns and adjusting these limits periodically to maintain the sweet spot between performance requirements and budget objectives.

https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-workgroup-max-rpu.html

Resource Tagging

Tags serve as customizable metadata labels for AWS resources, enabling efficient resource organization and cost allocation. By creating user-defined key-value pairs, you can easily track, filter, and categorize Amazon Redshift resources while mapping expenses to specific business units, projects, or applications for improved cost transparency.

https://aws.amazon.com/blogs/big-data/manage-your-data-warehouse-cost-allocations-with-amazon-redshift-serverless-tagging/

https://docs.aws.amazon.com/redshift/latest/mgmt/amazon-redshift-tagging.html

Data Lifecycle Management

Define data retention policy

An open-ended data retention policy can lead to increasing processing power requirements as the volume of data grows. work closely with business and data stakeholders to establish retention periods based on specific business needs and compliance requirements. This can help improving the efficiency of data management ,processing and storage costs.

Data archival

Archive infrequently accessed data to Amazon S3 and access through Redshift Spectrum or move it to History schema in Redshift.

Backups Storage Cost

Automated snapshots in Provisioned are offered at no charge to customers. Automatic snapshots run every 8 hours or 5 GB of data changes.

Recovery points in Amazon Redshift Serverless are not charged when they are less than 24 hours old. Amazon Redshift Serverless automatically creates recovery points every 30 minutes and keeps them for 24 hours.

Manual snapshots will have storage cost (0.023 USD per GB). Only keep the minimum required manual snapshots as per compliance requirement.

Manage S3 Audit logs and CloudWatch Storage

You can use either CloudWatch or Amazon S3 as a log destination for Redshift monitoring. Log data is stored indefinitely in CloudWatch Logs or Amazon S3 by default. To optimize Redshift monitoring costs while maintaining compliance, carefully configure log retention periods in either CloudWatch Logs or Amazon S3. Since logs are stored indefinitely by default, implement appropriate retention policies and compression methods to balance storage costs with regulatory requirements.

Performance optimization

Optimizing Redshift costs begins with efficient queries and table structures. Poorly constructed queries and table designs not only degrade performance but also unnecessarily increase compute costs by consuming excess resources.

Amazon Redshift Advisor offers recommendations about optimizing your Redshift cluster performance and helps you save on operating costs. you can automate Redshift Advisor notification

Query Monitoring Rules(QMR) in Amazon Redshift is a performance management feature that allows you to set performance boundaries for queries and define actions when queries exceed these boundaries. https://docs.aws.amazon.com/redshift/latest/mgmt/parameter-group-modify-qmr-console.html

Table design choices are critical determinants of Redshift performance and efficiency. Optimal table design not only enhances query speed but also minimizes storage usage, leading to reduced I/O operations and more efficient memory utilization during query processing. Please refer designing-tables-best-practices for details.

Monitor Redshift cost & set up Alerts

1. aws-cost-explorer has an easy-to-use interface that lets you visualize, understand, and manage your Redshift costs and usage over time.
2. aws-budgets enables proactive monitoring of your AWS spending and resource utilization, allowing you to track costs and set up alerts.
3. aws-trusted-advisor checks your AWS setup and suggests ways to save money, improve performance, boost security, and run things better.

Redshift Admin Scripts

You can use AdminScripts to monitor and troubleshoot Redshift performance issues.