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Saurabh Sharma
VP of EngineeringVP of Engineering at Closeloop, a seasoned technology guru and a rational individual, who we call the captain of the Closeloop team. He writes about technology, software tools, trends, and everything in between. He is brilliant at the coding game and a go-to person for software strategy and development. He is proactive, analytical, and responsible. Besides accomplishing his duties, you can find him conversing with people, sharing ideas, and solving puzzles.
Cloud technology is an indispensable enabler of digital transformation, offering businesses innovation, scalability, and agility. Thanks to its business value propositions, average cloud spending has steadily increased; according to a report, it grew 20-30 percent year over year - creating the need for organizations to seek cloud cost optimization methods to mitigate rising expenses.
Moving all applications onto smaller VM sizes might make sense if an organization was solely looking at cost optimization. Still, businesses would only tolerate taking such drastic action for performance reasons. Thus, when it comes to Cloud services, cost and performance are intrinsically tied together; although their benefits are many; their costs quickly escalate without active spend management.
Cloud cost optimization encompasses expansive strategies, techniques, best practices, and tools to lower cloud costs while increasing their business value. To properly optimize costs, it goes beyond mere expense reduction; rather, it must align them with business objectives to create tangible value from cloud adoption - as both prices and workload performance are intrinsically connected in this environment.
Cloud cost optimization reduces organizational cloud spending by identifying unmanaged resources, eliminating cost leakage points, reserving computation and storage capacities for higher discounts, and right sizing virtual machines to scale up and out more easily.
Too many businesses need help to optimize their Microsoft Azure cloud costs effectively. Here are three strategies you can immediately put into place to achieve cost optimization:
Cloud-native technologies such as microservices and containers as well as highly scalable platforms, like Kubernetes, can create cost-tracking blind spots due to their complexity. To avoid such blind spots in cost-monitoring efforts.
One way of combating this problem is through full-stack cost monitoring. Please do this by collecting as much data from as many infrastructure components as possible and using an appropriate cost optimization tool for automating, scaling, and reporting on it.
Microsoft Azure Cloud provides several in-built tools to assist in this effort, such as:
Azure Application Insights: This tool detects and analyzes incidents across applications and their dependencies.
Azure VM and Container Insights: It offers insight into infrastructure issues via metrics and logs, while Azure Log Analytics gives deeper insights from log data for faster problem resolution.
Automated actions: Automated actions allow for scaling cloud and on-premises operations with minimal manual intervention.
Azure dashboards and workbooks: These tools enable you to monitor the health of your infrastructure, apps, and networking components within a single platform for an in-depth evaluation.
Azure Monitor Metrics: This solution gathers and analyzes metrics data from various Azure resources such as Cosmos DB Insights, Backup, and IoT Edge.
Change Analysis: Change Analysis helps assess any changes that have occurred over time to support ongoing monitoring or incident management.
These Azure native tools will get you started with Azure cost monitoring, but over time, a more robust solution may be necessary to capture more accurate, actionable data at scale.
Once your cost monitoring program has been implemented, keep it always active. Your Azure cloud environment is ever-evolving so resource usage and associated costs are ever-changing - this constant monitoring ensures optimal resource usage at reduced prices.
Continuous monitoring helps detect cost anomalies quickly, helping you avoid expensive problems from developing. Furthermore, continuous monitoring allows you to quickly pinpoint the cause of a monster, helping fix the issue immediately and prevent future budget overruns.
Collecting Azure cost data manually through spreadsheets can often be too time-consuming and daunting for FinOps teams to handle effectively, while continuous cost management of Azure requires cloud cost optimization tools to automate aggregation, analysis, and reporting processes.
Unfortunately, most cloud cost management tools do just that - they aggregate, visualize, and report costs, showing total and average expenses to organizations, making it hard for 7 out of 10 organizations to track exactly where their Azure spending goes.
Knowing their Azure costs have increased may tempt them to cut spending across the board rather than optimize spending; herein lies the difference.
Instead of considering average costs, focus on price per unit instead. Think about the total amount spent serving each customer individually rather than the average costs of serving everyone overall. Utilizing unit economics techniques can provide actionable insights, including:
How much you need to charge for services to ensure a healthy profit margin
Which customers should move up a pricing tier
Which customer segments are more lucrative (so that you can focus more on attracting them)
Anticipate how your costs will shift as more similar customers join
Where you can cut expenses without jeopardizing Service Level Agreements (SLAs)
Azure allows you to identify resources in production using plain text key-value pairs that you set according to your organization's needs.
For example, you can track resources through their deployment environments by adding an Environment key-value pair. If the resources you deploy to production require special labeling with production as their value, label them accordingly - this identifier will appear in Azure resource utilization and cost reports.
Tagging can be tedious work; according to the most recent State of the Cloud Cost Intelligence Report, only 13% of companies had allocated at least 75% of their cloud development services costs. Yet tagging can significantly enhance your ability to see which resources are using up your Azure budget and take action accordingly. Some cost optimization tools do not require users to have perfect tags in order to generate accurate cost allocation data for you.
Many companies do not conduct substantial workloads during nights and weekends, making turning on virtual machines only when necessary one of the best ways to save money and cut expenses. Here is the next step.
Your next step should be reducing resource usage and costs when your virtual machines run. Azure Virtual Machine Automatic Shutdown helps reduce operating costs by automatically shutting off idle virtual machines after they remain inactive for an established amount of time, helping reduce operating expenses while optimizing resource use and costs.
Autoscaling refers to setting rules determining how Azure VM compute, memory, network, and storage capacities automatically adapt to your workload's changing demands.
Azure Autoscale improves performance and lowers costs by terminating redundant VMs once peak performance no longer needs to be attained.
Teams used to configure high-performing VMs as a backup in case they needed more power in the future, but that is no longer necessary - now all it takes to increase or decrease capacity is just a click or two in your browser. There are no long-term commitments or provisioning requirements!
Rightsizing Azure Virtual Machines begins by choosing the ideal Virtual Machine types to suit your workload. Here's a handy overview of each virtual machine type and when to utilize them:
General Purpose Azure VMs: Azure's A, B, and D series virtual machines can be used for testing environments and small to medium development environments for smaller development teams, smaller databases, or servers with lower traffic loads.
Compute Optimized Azure VMs: F-Series Azure VM types offer a higher CPU/memory ratio and are well suited to websites with medium traffic, batch processes, and mid-sized business apps.
High-Performance Compute Azure VMs: Azure Virtual Machines with High-Performance Compute, commonly called H-Series types, provide the highest compute setup to handle demanding workloads such as financial analysis and simulations.
Memory Optimized Azure VMs: E, Mv, and D series virtual machines offer an extremely high memory-to-CPU ratio for supporting memory-intensive workloads such as relational database servers, in-memory analytics, and mid-sized to large caches.
Storage Optimized Azure VMs: Ls VMs provide optimized solutions for big data processes, including running data warehouses (SQL/NoSQL databases).
GPU Optimized Azure VMs: N-series VM types provide GPU power for rendering graphics-intensive workloads like video editing, rendering images for rendering, modeling, and deep learning.
Adjust your Azure VM type configuration according to your daily operations and feedback received.
There's an inherent correlation between this Azure cost optimization best practice and understanding your cloud costs more granularly. Once you know where your money goes, it becomes much simpler to identify any adjustments necessary to maximize returns or reduce expenditure.
Once you know how much a particular product or software feature costs, it allows you to make decisions such as:
Removing it from the free tier if its cost becomes unsustainable
Offering it as a paid service
Converting the free forever tier into a 14 or 30-day free trial (with money-back guarantees) to prevent overspending.
Analyzing its popularity relative to costs and determining whether it should stay or be changed according to different use cases
Knowing these options provides the data-backed insights necessary for positioning yourself strategically within your market.
By correctly configuring elastic pools, achieving high performance at an economical price is possible. Azure SQL Database Elastic Pools enable you to pool resources together before sharing them among multiple database workloads.
Instead of allocating resources individually to meet the fluctuating usage requirements of each database, this resource pool distributes resources across them all at different times to make this approach viable. Peak workloads should occur simultaneously across all databases to make this feasible.
Its Azure offers storage tiering as a pricing strategy based on how frequently or infrequently you access and modify data stored with them; the less often this occurs, the greater your savings are likely to be. Several redundancy levels exist including Hot, Cool, and Archive storage options with lower redundancies offering lower costs of storage solutions (Blob Storage offers Hot Cool Archive Storage as an example of such possibilities).
To reduce costs and optimize efficiency, move less-sensitive or infrequently-accessed data to lower-cost tiers or redundancy options. Configure your setup to automatically move old files onto lower-cost storage options.
By taking advantage of Azure Hybrid Benefit, you can utilize your current on-premises (Software Assurance-enabled) SQL Server and Windows Server licenses on the Azure cloud; RedHat Linux subscriptions also qualify for this licensing benefit.
With this offer, you can get more from your license without incurring additional charges, increasing returns. Take advantage of this deal for up to 40% savings off Azure Virtual Machines (IaaS) and up to 55% savings off PaaS solutions such as Azure SQL Database or SQL Server!
Improved Azure Hybrid Benefits combined with Savings Plans or Reserved Instances can yield discounts of up to 80%!
Azure Advisor analyzes resource settings and usage metrics, logs, and traces and utilizes this data to make recommendations on improving cost savings, performance reliability, and security across your subscriptions. Its dashboard offers customized recommendations tailored specifically for each subscription.
Filter recommendations by subscription and resource type so you can implement cost optimization strategies in Azure.
Azure's Reserved Virtual Machine Instances (RVMIs) can give you up to 72% savings over pay-as-you-go pricing as long as they are reserved in advance for one to three years.
Azure Reserved Infrastructure Services encompass a range of services, such as App Service, Azure Cosmos DB, Storage Reserved Capacity, SQL Database, and Synapse Analytics.
With this option, you can pay all upfront or in installments - helping reduce upfront cash outlay. Combining RVMIs with Azure Hybrid Benefits could even save up to 80% off their standard (uncommitted) price!
Azure Spot VMs offer discounts of up to 90% on pay-as-you-go rates for spare Azure compute capacity, similar to AWS Spot Instances. Should Azure require the power back for any reason, you will receive a 30-second notice to convert the Spot VMs back into pay-as-you-go instances if needed.
However, Azure Spot VMs can still be useful for short-term tasks, including batch jobs, rendering, development/testing, and advanced analytics.
Visual Studio customers can take advantage of Azure's ongoing development/test pricing plan - up to 65% discount depending on which service you choose - by taking advantage of their development/test pricing plan for up-and-running development/testing projects.
Dev/test discounts can be gained when using Windows and Windows Server virtual machines, Azure development services instances, Azure App Service, SQL Database, HDInsight instances, and Azure Logic Apps for development/testing.
This offer also lets you take advantage of Azure DevTest Labs, Azure Shared Image Galleries, and Windows Virtual Desktop services designed to facilitate development testing.
Azure Savings Plans allow you to lock in a fixed hourly rate on computer services for one or three years at up to 65% savings off pay-as-you-go prices, applying across instance types, operating systems, and regions - even pairing these plans with Azure Hybrid Benefits can unlock additional savings potential!
As your commitment lengthens, so too do the potential savings. However, should you require more capacity than your plan allows per hour, additional charges may apply and be invoiced separately and at pay-as-you-go prices.
Azure Price Matching allows you to purchase or trade in active reservations for savings plans at competitive prices. Azure will cancel any reservation that is exchanged for savings plans.
Azure can price-match similar Amazon services within 90 days of submitting your application.
Price-matching capabilities exist between Amazon EC2 (compared with Azure Linux VMs), Amazon S3 Standard (comparable to Azure Block Blob Storage ZRS Hot), AWS Lambda (Azure Functions), and Amazon S3 Standard Infrequent Access (comparable to Azure Block Blob Storage ZRS Cool).
You could benefit from significant discounts by running workloads within a specific Azure region in one geographic area.
Running a DS2 v2 instance in East US 2 costs $0.114 per hour with a pay-as-you-go pricing plan compared to the East US region; that represents a 22% discount per hour and could save significant sums each month on monthly bills.
Real-time cost anomaly detection tools can assist in the early identification of potential issues before they become costly failures.
Microsoft Azure's Anomaly Detector provides near real-time univariate (up to 20,000 transactions per month free) or multivariate ($0.314 per 1,000 transactions) detection with live feedback that enables immediate action at no additional cost.
Azure Policy provides a convenient location for setting and enforcing safeguards across different areas, such as Azure resource governance. Not only can policy assessments and enforcement happen in real-time, but Azure Policy can also automate resource remediation at scale.
Understanding Azure costs is about understanding your business and who/what/why your Azure costs change over time. Knowing more about the people, processes, and products driving spend makes pinpointing opportunities to reduce Azure cloud costs much simpler.
Utilizing unit costs instead of averages and totals will enable you to precisely pinpoint where to increase investments to increase returns and maximize profitability.
Take these four examples as examples:
Analyzing customer costs per acquisition can help your marketing team identify customer segments with higher gross margins so they can target customer acquisition campaigns toward increasing these types of customers.
Utilizing unit costs, your finance team can accurately calculate how much to charge customers or specific services for project types or products.
To protect margins by analyzing cost per feature and retiring or raising prices on costly components.
Understanding your Cost of Goods Sold (COGS) allows management to predict how costs may change as your business expands, and plan in advance to take advantage of economies of scale.
IT leaders often grapple with how to utilize cloud services best while managing costs effectively with appropriate tools and practices that reduce the wastage of computing resources. Two crucial considerations when using services from the cloud efficiently include controlling costs with proper tools and implementing the best procedures that mitigate unused compute resource wastage.
In this blog, we delved deeply into cloud cost optimization strategies for Microsoft Azure. From right sizing virtual machines to using Azure cost management tools, we shared actionable insights that can help navigate the challenging world of cost optimization while maintaining high levels of performance and availability.
Organizations looking to move their IT assets onto Azure can avail of consulting services provided by cloud providers they collaborated with during migration. Azure cloud solutions providers also assist IT teams in using cost optimization methods for Azure services to control costs and allocate resources efficiently.
Cloud cost optimization involves selecting appropriate pricing models, managing Azure resources, and using cloud services effectively; IT leaders should focus on developing a strategy to control costs while decreasing Total Cost of Ownership (TCO) and increasing Return on Investment (ROI).
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