The implementation of Snowflake, the cloud data warehouse, on AWS can unlock tremendous value for your business through scalability, flexibility, and cost savings. However, this journey is not without challenges. Drawing from our experience in assisting clients with migrating to and optimizing Snowflake on AWS, we've identified the top three implementation challenges - along with practical tips on how to tackle them.
The Top 3 Snowflake on AWS Challenges
1. Managing Costs and Consumption
A primary challenge in implementing Snowflake on AWS is keeping cloud consumption costs under control. Snowflake's consumption-based pricing model requires close monitoring of your warehouses, while AWS infrastructure costs can escalate quickly.
Tips:
- Right-size your Snowflake warehouses for each workload. Scale up and down to match usage cycles.
- Set up AWS Reserved Instances for predictable costs on steady-state infrastructure.
- Utilize AWS Cost Explorer to identify spending anomalies and optimize utilization.
2. Migrating Data and Workloads
Migrating terabytes or petabytes of on-premise data into Snowflake on S3, along with shifting ETLs and analytical workloads, can be daunting. It involves refactoring code, repointing users and applications, and data validation.
Tips:
- Use AWS Database Migration Service (DMS) for minimally invasive data replication.
- Stagger workload migrations to test and validate before full cutover.
- Implement monitoring of query runtimes and resource consumption as usage shifts.
3. Security, Access, and Governance
With data now in the AWS and Snowflake cloud, providing robust security, access controls, and data governance is critical. This includes managing end-user access, network policies, S3 access controls, multi-factor authentication, and more across environments.
Tips:
- Define IAM roles in AWS for least-privilege Snowflake access.
- Configure VPC endpoints for private S3 connectivity from Snowflake.
- Establish a Snowflake role hierarchy aligned with the organizational structure and security policies.
- Enable MFA for Snowflake and AWS.
- Utilize tagging and metadata for data discovery and lineage tracking.
By anticipating these common implementation challenges with Snowflake on AWS and taking strategic steps to address them, you can smooth the migration journey and accelerate realizing Snowflake’s benefits - such as near-unlimited concurrency and scalability. The key lies in architecting a secure, governed platform optimized for analytic workloads.
