Running database workloads on AWS lets you benefit from scalability, flexibility and cost-efficiency, but you can still face challenges when it comes to optimization and making the best use of the right resources.
What if there was a way to shortcut this process to optimize your database so it runs the right way all the time?
Now NetApp® BlueXP™ workload factory for AWS can do exactly that. Its newly added continuous optimization functionality can automatically assess and optimize database workloads utilizing Amazon FSx for NetApp ONTAP (FSx for ONTAP). In this post I’ll explore this capability in detail and show how it can help you align your existing database configurations with best practices for optimal performance and resource utilization.
Here’s what I’ll cover:
- Overcoming the POC pitfall: Scaling databases to production
- Why continuous optimization matters
- How workload factory automatically optimizes your database workloads
- What you can gain with a workload factory optimized database
- Scale your database environment with confidence
Overcoming the POC pitfall: Scaling databases to production
Here’s the scenario: You've successfully navigated the initial stages of your cloud deployment with a well-executed proof of concept (POC). You’ve identified FSx for ONTAP as the most suitable service for your needs, found the right configurations for the POC goal, and did all the benchmarking. But have you considered the hidden pitfalls that may lurk in the transition to production? Many organizations stumble at this crucial juncture, mistaking a POC setup for a scalable, production-ready solution. At first it might work, but then later on problems start to show up.
This challenge is specifically relatable for databases. Database administrators face growing challenges in managing large data estates. Transitioning a database from a POC to a full production environment and its ongoing management presents unique challenges for organizations, especially at the enterprise scale. The complexity of ensuring high performance, cost-effectiveness, and compliance becomes overwhelming as the number of instances expands.
Some key challenges faced by large and growing estates are:
- Performance degradation: As database instances operate over time, they grow. As their scale increases, performance can degrade due to factors such as suboptimal storage sizing and layout, as well as configuration drift.
- Resource and license inefficiencies: Without regular assessments, database instances might be over-provisioned, leading to unnecessary costs for both extra resources and extra licenses. On the other hand, under-provisioned instances lead to performance bottlenecks.
- Availability and protection gaps: Due to their scale, large and growing database estates are more at risk for having vulnerabilities that could lead to data loss or availability issues.
- Monitoring and configuration challenges: Maintaining effective monitoring and optimal application configurations across a large and dynamic database estate can be overwhelming. This can result in missed opportunities for performance tuning and issue detection, potentially leading to reactive firefighting instead of proactive management.
- Compliance with best practices: Keeping a growing database estate aligned with industry best practices and the AWS Well-Architected Framework, requires continuous effort and expertise. If you don’t align with these best practices, you’re possibly setting yourself up for security incidents, inefficient operations, and compliance fines.
- Conflicting best practices: Different teams may have conflicting best practices for managing an environment, and that can lead to unintended misconfigurations. For example, storage admins might optimize storage for I/O performance, while DBAs might prioritize database consistency, potentially leading to suboptimal overall performance.
All these challenges could add up and lead to increased costs, data integrity issues, and inefficient operations.
BlueXP workload factory has a new way to solve those challenges and apply continuous optimization to your deployment at every layer: the continuous optimization feature.
Why continuous optimization matters
Workload factory is a free-of-charge automation and optimization service designed to align FSx for ONTAP workloads with best practices for design, deployment, and operations.
Workload factory is a valuable tool for deploying database instances on FSx for ONTAP. There are two scenarios where this can take place:
- New database deployments set up via workload factory automatically align with best practice recommendations. These new deployments can also include optimizing existing databases that have previously run on another storage service.
- Existing database deployments on FSx for ONTAP that haven’t been aligned with best practices can now be automatically reconfigured by workload factory. With the new continuous optimization feature, workload factory assists with ongoing optimization so that your database is aligned with best practices and well-architected guidelines.
With its new continuous optimization feature, workload factory makes this process faster and easier than ever. Let’s see how.
How workload factory automatically optimizes your database workloads
The continuous optimization feature in workload factory is designed to assess, optimize, and maintain existing database environments deployed on FSx for ONTAP. Let’s unpack how this feature can help optimize your existing database deployments.
Assessing your environment
The continuous optimization feature conducts a comprehensive assessment of various components across all stacks of a database environment, analyzing:
- Compute factors including the virtual machine or instance hosting the database, focusing on elements such as CPU utilization, memory allocation, and instance sizing.
- The storage layer, including the FSx for ONTAP storage configuration, storage capacity, performance tiers, and data protection mechanisms.
- Network configuration aspects such as virtual networks, security groups, and connectivity.
- Database parameters such as your database configuration, schema design, and query performance.
Identify improvement opportunities
Once the environment is assessed, the workload factory considers a multitude of factors such as performance, cost, resilience, and security to identify where your database can be improved. It adds tags to each finding making it possible to filter the results and get an easy view of each aspect which can be optimized.
For example, workload factory analyzes a database for file system headroom, adding the tags “performance efficiencies,” under the category “storage sizing.” Based on these tags, it provides the user with specific recommendations: in this case, to optimize storage performance, it recommends provisioning file system capacity as 1.35 times of total size of the provisioned volume.
In the screen below you can see the overall optimization score for an MS SQL instance. It presents the number of configurations workload factory has analyzed, divided by optimized and not optimized, and the category it relates to:
Alignment with best practices
Workload factory compares your current deployment with industry best practice recommendations. This will help you see where your system might need adjustments to meet established standards for optimal performance and security.
For example, workload factory can show you the best storage headroom for optimal performance based on your workload, and right-sizing your storage based on the amount of data on hand.
Optimization score
Based on its evaluation, workload factory assigns an optimization score for your deployment. This includes an overall score and severity of its findings across different categories such as storage layout, capacity, configuration, etc. This score provides a quantitative view of the strengths and weaknesses of your deployment, so that you can identify the areas that need most attention.
In the screen below, you can see the different aspects of the databases that were checked, their status, and improvement recommendations:
Putting optimization into effect
After the assessment, workload factory suggests improvements and explains the recommendations in detail. If you click “Optimize,” these recommendations will be automatically applied. Note the changes will be implemented only after the user’s explicit approval.
As shown here, workload factory gives you a list of recommendations, with details, and the option to optimize each with a click of a button:
Readable reports
Workload factory provides comprehensive reports on your database environment's posture, covering aspects such as performance, security, and cost. You get a detailed overview of your deployment's health and see how it aligns with best practices.
These reports look at and analyze every layer of your workload, making them relevant to diverse team member perspectives: storage admin, IT, DBA, etc.
What you can gain with a workload factory optimized database
Here are the major benefits to using workload factory continuous optimization for database operations:
Know when you can scale
By assessing your database deployment with workload factory, you can determine its readiness for scaling.
Identify potential issues before they have impact
Workload factory identifies potential issues before they lead to performance degradation, downtime, or data loss.
Remediate problems automatically
Workload factory streamlines the process of resolving identified issues by offering automated remediation options. This means all it takes is a few clicks to address problems. That’s a huge time saver and much less effort than manually resolving issues and reconfigurations.
Get full visibility into the database’s posture
With the automatic reports generated by workload factory, you gain an easy way to document deployment configurations for full transparency and accountability throughout your organization.
Benefit from expert knowledge and easy implementation
By automatically implementing workload factory best practice recommendations, you can benefit from expert insights, without bringing in consultants or support.
In this way, workload factory gives you a way to reduce dependency on third-party vendors to optimize operations. You can solve them on your own—which is also a major way to cut costs.
Scale your database environment with confidence
Optimal performance, cost-efficiency, and aligning with best practices for large database estates all take ongoing attention. With workload factory continuous optimization, there’s a powerful tool that lets you take control of your database deployment on FSx for ONTAP.
The workload factory continuous optimization capabilities allow you to autonomously optimize your databases. By automatically detecting and remediating issues related to performance, cost, and security, workload factory keeps your database running efficiently and in line with best practices.
Learn more about BlueXP workload factory or get started now.