As a solution architect utilizing Azure’s latest updates, the integration of Azure Advisor with Azure Monitor Log Analytics Workspace is a significant update to our strategy. This integration brings a suite of recommendations to improve the cost-efficiency and performance of our deployments, ensuring that we are making the most out of our resources while keeping costs in check.
Utilizing Azure Advisor for Enhanced Resource Management
Azure Advisor is a personalized tool within the Azure ecosystem designed to optimize and improve your Azure resources’ cost, performance, reliability, and security. It works by analyzing your configurations and usage patterns to provide recommendations.
Understanding Log Analytics Workspace
A Log Analytics Workspace is a unique environment within Azure Monitor that aggregates data from various sources. It’s a pivotal tool for comprehensive analytics, allowing you to gain insights from across your Azure and on-premises environment.
Cost Management with Azure Advisor
With the latest updates, Azure Advisor now extends its capability into Log Analytics Workspaces to offer specific guidance on cost management.
- Basic Logs Plan: For tables ingesting more than 1GB monthly, a shift to the Basic logs plan is recommended. This plan is less expensive and still provides sufficient capabilities for routine troubleshooting.
- Pricing Tier Optimization: Azure Advisor evaluates your Log Analytics Workspace usage and suggests an appropriate pricing tier, potentially leading to substantial savings. While it doesn’t consider custom discount rates or apply to workspaces dedicated to Azure Defender and Sentinel, it’s an effective way to ensure you’re not overpaying for your actual usage.
- Unused Restored Tables: The Advisor now also helps identify restored tables that are no longer in use. By prompting their deletion, it helps prevent needless costs that accumulate from storing unnecessary data.
How to Implement Advisor Recommendations
To implement these recommendations:
- Navigate to the Advisor through the Azure portal, I recommend using the search bar and search ‘advisor’.
- Look for the cost section to find relevant suggestions under ‘Recommendations’.
- Review the details of each recommendation, including potential savings and impact.
- Take action directly from the Advisor interface, such as changing pricing tiers or deleting unused tables. Take note, if you use a modern pipeline, involve your engineers to check downtime and changes need to their code base before taking action. I’ll advise you later on in this blog about this topic.
Azure Advisor Recommendations and Impact Explained
Azure Advisor provides several types of recommendations that span across different aspects of your Azure resources. Here’s an overview of what kind of advice it can give:
- Cost: Suggestions to reduce your spending without negatively affecting your services. This can include resizing or shutting down underutilized instances, choosing different pricing tiers, or removing unnecessary resources.
- Performance: Tips to enhance the efficiency and responsiveness of your applications. This might involve adjusting caching, scaling resources, or tweaking configuration settings.
- Reliability: Recommendations aimed at ensuring your applications and services are running reliably. This could include setting up availability sets or implementing disaster recovery strategies.
- Operational Excellence: Advice on best practices and patterns to improve the management and monitoring of your resources.
- Security: Guidance to strengthen the security posture of your resources, such as enforcing stronger access controls or updating security policies.
The impact of a recommendation refers to the potential benefit or effect that following the recommendation could have on your resources in terms of cost savings, performance improvement, reliability enhancement, operational efficiency, or security tightening. Azure Advisor classifies impact into three levels:
- High Impact: Implementing these recommendations could lead to significant improvements in the mentioned dimensions.
- Medium Impact: These are recommendations that offer a good balance of effort to benefit ratio.
- Low Impact: These recommendations are typically easier to implement, but may offer smaller gains compared to high or medium impact suggestions.
By assessing the impact level, you can prioritize which recommendations to implement first based on your business needs and resource optimization strategies.
For Newcomers to Azure Monitor and Log Analytics
If you’re new to Azure Monitor or Log Analytics Workspace, here’s how the integration benefits you:
- Streamlined Operations: Azure Advisor within the Log Analytics Workspace simplifies how you manage and optimize your resources.
- Cost Visibility: It provides visibility into your spending and usage, so you can make informed decisions about your Azure investments.
- Proactive Management: Advisor recommendations allow you to proactively manage resources to avoid cost overruns.
Maximizing Azure Advisor Recommendations with Commitments and Filters
To derive the best outcome from Azure Advisor, it’s essential to understand how to use commitments and filters effectively. Here’s how you can do that:
Understanding Commitments
Commitments in Azure, such as reserved instances or savings plans, offer a significant cost reduction in exchange for committing to a certain level of usage over time. When Azure Advisor makes recommendations, it may not always consider these pre-existing commitments. Therefore, it’s crucial to:
- Review Current Commitments: Before acting on cost recommendations, review any existing commitments to ensure the recommended changes align with the terms of your commitment and won’t incur penalties or waste prepaid services.
- Balance Flexibility and Savings: Determine the balance between the flexibility of pay-as-you-go services and the savings from longer-term commitments. Opt for commitments when consistent usage patterns are clear and predictable.
- Align with Business Forecasts: Align your commitments with your business’s growth and usage forecasts to avoid underutilizing or overcommitting resources.
Using Filters for best recommendations
Filters in Azure Advisor help you to narrow down the recommendations to the ones most relevant to your specific needs or areas of focus.
- Filter by Subscription or Resource Group: If you manage multiple subscriptions or resource groups, filter recommendations to view them for each specific area. This helps in allocating costs and improvements accurately.
- Impact Level Filtering: Prioritize recommendations by impact level. Start with high-impact recommendations to address the most significant optimizations first, then work your way down.
- Category Filtering: Use category filters like cost, security, or performance to focus on specific areas of improvement. This is especially useful when you have organizational goals targeting specific aspects of your cloud environment.
Considerations for Implementation
When implementing Azure Advisor recommendations, consider the following:
- Potential Disruptions: Some changes may cause disruptions. Plan for any downtime and communicate with stakeholders.
- Testing Changes: Test the recommended changes in a non-production environment, if possible, to assess their impact without risking your live environment.
- Monitoring After Changes: Once you implement recommendations, monitor the resources closely to ensure the changes have the desired effect and adjust if necessary.
- Compliance and Security: Ensure that any changes comply with your organization’s policies and do not introduce security vulnerabilities.
- Cost-Benefit Analysis: Conduct a thorough cost-benefit analysis for each recommendation to ensure that the long-term benefits outweigh the costs and effort of implementation.
By carefully considering these elements and utilizing commitments and filters, you can strategically implement Azure Advisor recommendations to optimize your Azure resources effectively.
Can I automate this with infrastructure as code?
Yes, you can implement Azure Advisor recommendations as infrastructure as code (IaC) using tools like Azure Resource Manager (ARM) templates, Terraform, or Bicep. IaC allows you to manage your infrastructure with configuration files, which are particularly useful for automating the setup and configuration of cloud resources. Here’s how you can approach this:
- Extract Recommendations: Review the recommendations from Azure Advisor and determine which can be translated into IaC. Some recommendations may be straightforward, like scaling resources, while others may require more complex changes to your configurations.
- Define IaC Templates: Once you’ve identified the applicable recommendations, define them as code in ARM templates, Bicep files, or Terraform configurations. For example, if the recommendation is to resize a virtual machine for cost savings, you would define the new size in the relevant VM resource block in your IaC template.
- Version Control: Use a version control system like Git to manage and track changes to your IaC templates. This practice is crucial for collaboration and rollback if needed. As ambassador of GitKraken I would definitly advise you to take a look at amazing GitKraken tooling for your source code managment at gitkraken.
- Test Changes: Before applying the changes to your production environment, use a staging environment to test the new configurations. This helps to ensure that the changes will behave as expected.
- Automate Deployment: Use Azure DevOps, GitHub Actions, or similar CI/CD tools to automate the deployment of your IaC templates. This ensures that changes are applied consistently and that they go through any required review processes.
- Monitor and Iterate: After deployment, monitor the impact of your changes. Azure Monitor can help you validate that the applied recommendations have the intended effect.
- Compliance Checks: Make sure your IaC templates adhere to compliance policies. Tools like Azure Policy can be integrated into the CI/CD pipeline to enforce rules and prevent non-compliant resources from being deployed.
- Documentation: Document the changes and configurations within your IaC templates to keep team members informed and to support future audits or troubleshooting.
By adopting IaC for Azure Advisor recommendations, you not only automate resource provisioning but also maintain a documented, versioned, and repeatable process that aligns with DevOps best practices. This approach leads to more predictable and efficient management of cloud resources.
Summary
In summary, Azure Advisor’s integration with Azure Monitor Log Analytics Workspace offers a powerful and proactive approach to managing Azure resources. By effectively utilizing commitments and filters, and implementing changes through IaC, organizations can ensure their cloud infrastructure is not only cost-efficient but also robust, secure, and well-maintained. This strategic approach to cloud resource optimization is essential for maintaining a competitive edge and achieving operational excellence in the cloud.
