If you're a U.S. federal, state, or local government agency trying to deliver services to the public faster without sacrificing a single inch of security, GovCloud is the PaaS (Platform as a Service) solution.  But what exactly is GovCloud, and how can it ensure you deliver services more efficiently and effectively?  We'll tell you all you need to know so you can decide if you're ready to upgrade your tech stack with this tool.  What is GovCloud?   Let's define our term first.  GovCloud is a U.S.-specific AWS service designed with the extra levels of security necessary for those working in government agencies.  Not only does it check almost all of the compliance boxes for systems like CJIS (for criminal justice data), it also has a built-in compliance support system that enables you to create your documentation as needed to ensure you're always meeting industry rules.  You can receive GovCloud-like services from providers, including Azure Goverment (designed only for U.S. regions) or AWS GovCloud. Common services for government agencies include networking and database services, including heightened levels of security, encryption, and backup offerings.  Why GovCloud?   [caption id="attachment_16375" align="aligncenter" width="512"] Source: AWS[/caption] There’s a wide range of reasons GovCloud might be the best offering for you. Here are our top three reasons:  Reason #1: No need to worry about compliance needs If you're a government organization, GovCloud is a system designed to meet your compliance needs. It will pass every HIPPA, FedRAMP, FIPS 140-2, or ITAR regulatory review.  Reason #2: Complete data protection Even the American DoD (Department of Defense) can rest easy knowing that GovCloud providers are specifically designed to prevent sensitive data leaks. With this assurance, you can process and store sensitive data without worry. Reason #3: Handles massive workloads GovCloud is engineered for government work, which means you'll be working on a platform built to handle huge numbers of users and spikes in usage. You'll still be able to access popular AWS services, and since GovCloud is an open-source platform,  and the portability to other cloud providers or your current on-prem tech stack.  How to Use GovCloud   You'll want to confirm your company meets a certain requirements list before settling on GovCloud. Use this checklist to make sure its the best fit for you:  Consider if your company has a legal, contractual, or customer-mandated reason to use GovCloud.  Assess how your other cloud integrations or services might blend with GovCloud.  Review your security requirements.  Evaluate operational needs.  Consider business objectives.  Ensure compliance requirements will be met.  Confirm GovCloud meets all your needs before signing the deal.  If you meet the requirements and decide that GovCloud is the best service for you, here’s what you need to do to ensure a seamless migration:  Establish GovCloud endpoints. Use a management console or API calls to establish GovCloud endpoints programmatically. Configure IAM roles. IAM (Identity and Access Management) roles decide who can access what in your GovCloud setup. Migrate your data. Now that you've established your GovCloud account, you can migrate over your workloads. You may need to make some adjustments depending on compliance requirements. Test and verify the final results. Always, always, always test and verify that your set-up has been properly established.  Managing GovCloud   Once you’ve gotten started with GovCloud, you’ll want to do the following:  Regularly monitor your workloads for compliance. Consider using an automated compliance tool to assist with this task. Consider third-party tools for additional support. The right third-party cloud management tools can optimize your spending while providing valuable insights into GovCloud. This combination allows you to enjoy top-notch security alongside AI-driven cost-saving opportunities. “While GovCloud offers unmatched security and compliance for government agencies, optimizing cloud spend remains a critical concern.  Third-party tools like Anodot can help agencies identify cost-saving opportunities, automate anomaly detection, and gain granular insights into their GovCloud usage. This empowers them to make data-driven decisions and maximize their cloud investment.” ~ Limor Tepper, VP of Product,  Anodot. Are there GovCloud drawbacks?   Like any program, GovCloud has some drawbacks.  Before you commit to GovCloud, you should know that it comes with some constraints, the largest of which are slower updates. Compared to other cloud offerings, GovCloud can be a bit slower in pushing updates live. Lack of speed is the price you must be prepared to pay if you're looking for that full compliance boost.  For example, AWS GovCloud rolled out CodeConnections in the GovCloud (U.S.-Eat) Region in September 2024, whereas the same tool was released for general AWS cloud services in March 2024. Amazon EKS Pod Identities was only released for AWS GovCloud in August 2024, while the service was available on AWS Cloud since November 2023. So, you should prepare yourself for some longer waiting times with GovCloud.  Is GovCloud the best cloud provider for US government agencies?   Now that we've covered everything you need to know about whether you should go with GovCloud let's discuss whether it's the right provider.  The Pros and Cons of AWS GovCloud   AWS GovCloud is known for its secure and compliant cloud environment offering. Its services have been specifically designed for any government service, from state to federal to local. You'll have access to all the standard features of the commercial version of AWS but with the added level of security and compliance expected from the GovCloud offering.  AWS GovCloud's key features include:  Government-specific compliance for FISMA, ITAR, FedRAMP, HIPPA, and more. Ability to manage many levels of data security. Variety of access control options. AWS GovCloud’s cons include:  Lack of feature parity between commercial AWS cloud and AWS GovCloud (ex: AWS ChatBot doesn't exist in GovCloud). Access is restricted to U.S. individuals who comply with U.S. export control laws. Additional costs and latency incurred with data transfer between AWS GovCloud and other non-GovCloud accounts.  [CTA id="dcd803e2-efe9-4b57-92d5-1fca2e47b892"][/CTA] Should you use GovCloud?   Federal, government, or state entities needing compliance, heightened security, and comprehensive support from government cloud services should strongly contemplate migrating to GovCloud. Despite the additional qualification steps and longer release timelines, the assurance of 100% secure user data usually outweighs the extra effort. If you’re not in a place to support migration, it’s probably better to wait. GovCloud isn’t going anywhere, and you’ll want to ensure your migration is properly executed.  No matter what platform you choose, cloud cost management is the biggest obstacle you’ll face. AWS GovCloud provides some visibility into cloud spending but lacks comprehensive insights for effectively balancing and optimizing costs. [CTA id="47462b23-d885-42f9-9a91-7644f2c84e50"][/CTA] Optimize your GovCloud spend   Let’s cut to the chase: Anodot is one of the few Finops tools that supports AWS GovCloud.  Here’s how: Multi cloud data in one place, offering a 24-month look-back period to identify changes down to the hour. This provides complete visibility into your GovCloud spending, making it easy to spot potential budget misuse. Anodot uses machine learning (ML)  to detect cost anomalies automatically in real time. This allows government agencies to identify unexpected increases in cloud spending, helping to prevent budget overruns and ensuring efficient resource allocation. Granular Cost Allocation allows users to break down cloud expenses by department, project, or service. This helps GovCloud users ensure that each segment of their organization is accountable for its cloud usage, making cost management more transparent. Predictive analytics allows agencies to estimate future cloud costs using historical data, which helps with budget planning, particularly for government organizations that must adhere to strict budget limits. Government agencies can set customized alerts for specific spending thresholds or changes in usage patterns and take immediate action when costs deviate from expected levels. Why Anodot? We’ve been demystifying cloud costs for FinOps organizations for years. We ensure that overspending is never a problem with our automated anomaly detection and customized alerts paired with AI-powered feedback. You won’t need to lift a finger. You can just start cutting costs.  Other Anodot tool features include:  Next Level Forecasting: High-powered analyses to make planning spending easy.  AI-Powered Support: AI-powered recommendations that improves resource utilization.  Multicloud Visibility: Next-gen multicloud visibility so you can see your cloud spend and activity all in one place.  Automated Anomaly Detection: Customizable alerts that improve real-time budgeting and help you react immediately to unusual data trends.  Want a proof of concept? Talk to us to learn how much you can save with Anodot’s tools. 

Every government – especially the U.S. government – needs secure cloud space. And there is no better way to get guaranteed security and compliance-ready services than through Microsoft Azure Government's world-class cloud offerings.  But what is Azure Government? How does it work? And, most importantly, will your organization qualify to reap the benefits?  Let’s take a closer look at Azure Government, the differences between this offering and regular Azure, the benefits you can expect, what regions can use this service, and how you can optimize your cloud performance.  What is Azure Government Cloud?   [caption id="attachment_16365" align="aligncenter" width="512"] Source: Microsoft[/caption]   Azure Government Cloud is a version of Microsoft Azure, a cloud offering made specifically for the U.S. government, federal, state, and local agencies and their contractors. You can store anything from cloud data for the Department of Justice to a state department.  Since Azure Government offers an IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service) cloud model system, there can be some confusion about how each type differs from the others.  For instance, Azure Government customers can expect higher security and data protection than standard Azure offerings. Azure Government also has contractual commitments regarding data storage, and access to Azure Government is restricted to screened U.S. citizens. Let’s look at the differences between Azure Government and Azure Commercial below.  Azure Government vs commercial    The most significant difference between Azure Government and a regular Azure is that it’s a sovereign cloud. This means it’s physically separated from Azure and meant for the U.S. government only.  As we mentioned above, there are many other smaller differences as well. Azure Government offers the much-needed benefit of added security. It also requires all customers to undergo an eligibility process to determine whether they meet the requirements to utilize Azure Government.  The development environment is primarily the same, but the security, compliance, and operational procedures for deployment might differ due to the unique regulatory needs of government data. Since Azure Government can be very location-specific, you’ll want to carefully review the rules for your region before starting work. The most important thing to remember is that all areas are within the US. But don’t worry! We’ll go into more detail on the different regions in a little bit. [CTA id="dcd803e2-efe9-4b57-92d5-1fca2e47b892"][/CTA] What are the benefits of Azure for government?   The obvious pro of Azure Government's massively superior security offerings aside, here are some other benefits to enjoy:  Disaster recovery: Azure Government offers Site Recovery in case of disaster so you can fully recover your tech stack, all without the cost of a secondary infrastructure. Secure backup and archives: Azure Government offers Azure Backup, Azure Storage, and to ensure your peace of mind in keeping your data secure. Data and analytics: Analyze real-time data changes to improve customer experience. Development and test: Azure DevTest Labs is a service that helps agencies quickly create development and testing environments, allowing for experimentation without impacting production environments. Networking: You'll have access to networking services that help you load balance traffic, autoscale, monitor back-end poorl, and more with tools like Azure Load Balancer, Azure Virtual Network, Azure ExpressRoute, Azure VPN Gateway, and Azure Application gateway.  Since Azure Government is separate from Azure, it can operate with its own network. There are eight regions in the US, two of which include U.S. Department of Defense (DoD) Impact Level 5. You can expect data replication for all regions and connection via private dark fiber.   [caption id="attachment_16366" align="aligncenter" width="540"] Source: Microsoft[/caption]   You'll also have access to networking services like VNet service endpoints for SQL, Network Watcher, and Azure storage.  Azure Government makes it easier for government agencies to bring their tech stack to the modern era. You’ll finally get cloud software you can trust to protect citizen and personnel data.  What are Azure Government regions?    Azure uses paired regions to provide geo-redundant storage.  Paired regions are typically used for disaster recovery and geo-redundancy to ensure you always have coverage. The regions are usually physically far apart to reduce the risk of both areas being impacted by a single disaster. Disasters aside, paired regions mean that you don't have to worry about downtime during an update since usually only one part of a region is updated at a time.  Here are the primary and secondary region pairings used by Azure Government:    Geography Regional Pair A Regional Pair B US Government US Gov Arizona US Gov Texas US Government US Gov Virginia US Gov Texas   In other words, if you choose Regional Pair A, your data will be stored in Arizona and Virginia in the U.S. This will ensure that if there is an outage in Virginia, you can continue to operate in Arizona. Or, if your systems require updates in Arizona, you don’t need to worry about downtime and can operate as usual in Virginia.  Should you migrate to Azure Government?   Is it worth migrating to Azure Government?  Suppose you're a government, federal, or state organization seeking enhanced cloud security and compliance support, and you're already an enthusiastic user of Azure. In that case, it may be a good fit for you. If you’re new to Microsoft Cloud, your decision will largely depend on your readiness to handle migration and whether you have a capable team to navigate the learning curve. Already a User of Azure? Anodot Can Help Manage Cloud Cost and Eliminate Cloud Waste.   What is the most significant limitation behind Azure? A limited view into how Azure pricing works. Sure, you'll have data and analytics on how your dollars are put to work, but there's always some mystery behind how exactly the money goes into the cloud and services come out.  There's an easy solution to ensure your budgets are fully optimized. Third-party tools like Anodot can provide more granular insights and proactive recommendations to really impact your Government cloud spending. How do we do this? Putting all of your cloud data in one place so you can look back up to 24 months allows FinOps teams to spot trends, seasonal usage patterns, and potential inefficiencies. This allows you to pinpoint how even the smallest changes affect your cloud budget, meaning no gaps are overlooked. Y The best part?  Anodot is made for multi-cloud data management. So, if you’re juggling multiple cloud platforms and cycling between a dozen different dashboards, you can rest easy. We put all that data in one place with customizable, easy-to-understand consoles.  We’ve made it our mission to make cloud cost management our specialty. Anodot has been demystifying cloud costs for FinOps organizations for years. Our mission is to make your overspending our enemy. With our automated anomaly detection, AI-powered feedback, and next-level forecasting data, you can start cutting costs without ever lifting a finger.  Want a proof of concept? Talk to us to learn how much you can save with Anodot’s tools.

Undoubtedly, AI is our future—which means it's past time to integrate machine learning models into your FinOps multi-cloud tech stack. AI turns simple tasks into something that can be executed at the click of a button. With well-trained models, FinOps, MSPs, and Enterprises can automate cost detection, forecasting, and anomaly identification, streamlining complex financial operations without increasing their workforce. The good news?  If you're an Azure user, you can use their Azure Machine Learning feature to stay ahead.  The bad news? The Azure ML pricing structure, like all Azure pricing, can be a bit... complicated.  But don't worry! We're something of Azure experts. Read on to avoid any and all monthly budget surprises while maintaining optimal customer experiences.  What is Azure Machine Learning?   Azure Machine Learning (ML) is an open, interoperable platform that streamlines the process of building, training, and deploying machine learning models, helping you optimize your multi cloud resources and manage costs efficiently in alignment with FinOps best practices. For teams seeking flexibility in discovering new project assets and resources while easily sharing existing files, Azure ML serves as a pivotal tool for collaboration.   [caption id="attachment_16342" align="aligncenter" width="512"] Source: Microsoft[/caption]   Azure Machine Learning (ML) is recognized for its strong security features. It works well with other Azure services to keep all ML workflows secure.  Such as: Azure Key Vault securely manages and stores critical information such as API keys and credentials.  Azure Container Registry ensures the safe management of container images, maintaining isolation and safety for machine learning environments.  Azure Virtual Networks enable you to segregate machine learning projects within your network, fostering a secure and collaborative space for your ML tasks.   Who uses Azure ML for FinOps purposes?   Azure Machine Learning is the perfect tool for FinOps groups or individuals who want to start integrating machine learning processes into their multi cloud tech stack. This tool allows you and your team to focus on what you do best while Azure ML handles menial, automatable tasks.   [caption id="attachment_16343" align="aligncenter" width="540"] Source: Microsoft[/caption]   Wait, it gets better. ML integrates well with any other tools you use in the Microsoft Azure cloud ecosystem, so optimizing security networks or role-based controls is easy.  In other words, if you want to enhance your FinOps engineer's daily work, Azure ML will appeal quite nicely!  How to set up your new Azure Machine Learning workspace   [caption id="attachment_16344" align="aligncenter" width="540"] Source: Microsoft[/caption]   Setting up your Azure ML isn't as hard as you think. Follow these steps, and you should be good to go:  Sign into your Azure Portal account. Or Create an account if you don't already have one. Search for "Machine Learning". Select it from the other services. Hit "Create" to start a new Machine Learning workspace. Select the basic settings for Subscription, Resource Group (either pick an old or pre-established one), Workspace Name, and Region (pick either your region or one close to you). Pick your resource details for Storage Account (make a new one or use a pre-existing one), Key Vaulted, Container Registry. You can also opt into Application Insights for monitoring resources. Review your choices to make sure everything is accurate. Deploy your new ML workspace!    How are Azure Machine Learning costs calculated?   Before we get into these numbers, keep in mind that these prices have been calculated assuming the user is based in North America, so it’s possible your costs might be higher or lower than the numbers below. Look to see how prices might vary for other parts of the world here.  Now that that’s been covered, let's break down how your Azure ML bill works.  There are four main factors that contribute to costs:  VNets and load balancers. The more cluster support you need, the higher your bill. Compute time. Anything from profiling a data set to deployed models or real-time endpoints on Azure Kubernetes services can contribute. Storage. Anything from storage for trained models, metrics, or logs will add to your total. Azure container registry. Yes, you'll need to pay for your registered containers.  The key to keeping your Azure ML pricing low is optimizing everything to the fullest and making sure you have the best possible tools to track any changes.  Pro tips to manage Azure Machine Learning costs   Keep your Azure ML costs low while maintaining quality customer experiences by paying close attention to the following factors:  Optimizing Compute costs As you set up your compute cluster, you must select the best compute resource for your experiments.  It may surprise you to learn that the bulk of your bill won't come from compute costs and training r models. The actual training process makes up only a small amount of the costs – though this can vary from user to user. If you're expecting heavy training runs, prepare to invest more. Here are our four tips to handle compute usage if you intend on using Azure ML for training large models:  Don't pick a super low compute tier. If you pick something too low, it will likely save you more money in the short run, but because you're stuck with slower processing time, it'll cost more in the long run in resources and time. Specify 0 as the minimum number of nodes for your compute cluster. This means your compute resources can shut off when you no longer have any active work scheduled, letting you dodge additional resource charges. Use low-priority compute resources during training tasks. If you don't mind training tasks taking a bit longer or having to be restarted if there's limited capacity, your experiments are a great place to save money. Enable an idle shutdown timer. Set a stop compute instance schedule for off-hours. This means you don't have to worry about hidden-away compute instances in notebooks leading to surprise charges.  The key here is to maintain a quality offering while eliminating waste. We’ll explain how to do that below.  Monitoring Storage prices Azure Storage is the most common budget-killer when it comes to ML pricing. Make sure to delete any trained models you no longer  use . It's best to regularly audit any stored data on Azure so you're not paying for something that isn't useful.  The following are the biggest contributors to increased storage: Log Model metrics  Data profiles  Training data  Trained models For instance, when automated ML trains your models to identify the most effective hyperparameters, you'll achieve a highly efficient model. However, this process may also leave you with numerous underperforming models stored away, increasing your storage costs over time. Managing Endpoints Endpoints are another pain point for Azure ML pricing. Deploying real-time models to live endpoints is a powerful feature... which means it's also very expensive. You'll have to pay for Azure Kubernetes Services resources or Azure Container Instances and associated container registries, storage, and load balances. You’re also on the hook for all sorts of real-time costs 24/7 – always on cost, autoscaling costs, and idle costs, so plan carefully. Here's how you can optimize:  Azure Container Instances (ACI) are usually less expensive than Azure Kubernetes Services (AKS) since AKS clusters are made for product-level tasks, while ACIs are more for developing and testing. So, if you're using Azure ML for testing and development, it's a good idea to use ACI to save on costs! Use batch endpoints instead of real-time endpoints to lower compute costs when you're able.  Remove endpoints you aren't regularly using to help save costs while maintaining UI.  Azure Container Registry Azure Container Registry (also known as ACR) is where you store, build, and manage your container images. It enables you to replicate images across multiple locations and provides added security by offering image signing through Docker Content Trust.  You must create various resources in your Azure Machine Learning Workspace, but the container registry is optional. Since it comes with an associated fixed cost, opt out of it for now or use a pre-existing container registry even if you're not actively using it.  If you ever deploy a container, you won't need to worry about anything going wrong because Azure ML Workspace will automatically create a container registry. So don't make one unless you need it! How to track Azure ML pricing   Microsoft does provide some tools to help you monitor changes in Azure pricing. You can use Azure Cost Management to monitor cost alerts and changes to spend. There's also their Pricing Calculator that you can use to project how much service add-ons might cost.    However, these tools have limitations. Though you can pull your Azure AI and ML services into the same dashboards to project costs with Azure's tools, you often won't get a full view of your multi cloud experience or an in-depth analysis of how to address pricing issues. You won’t get the best view into how your resources might be going to waste, or how to optimize your customer’s user experience best while maintaining profitable margins.     [caption id="attachment_16345" align="aligncenter" width="540"] Source: Microsoft[/caption]   Top solution to track Azure ML spend What is the best solution for keeping track of your Azure ML spend?  A third-party tool that works alongside you to help reduce Azure ML pricing without any ulterior motives to increase your Azure costs. And we’re the cloud cost optimization tool. Anodot can help you save up to 40% on annual spending. Anodot lets you get all multi cloud data in one place. Picture this: a UI-friendly dashboard that shows where all of your spend is going and fluctuations captured down to the hour with retention periods up to 18 to 24 months. Finally, you can finally have that 100% visibility into your cloud performance that you’ve always dreamed of.  Why Anodot? We’ve been working to demystify cloud costs for FinOps organizations for 10 years.  Other Anodot features include:   Real-time anomaly detection: Automated alerts that improve response time to cloud spend spikes and allow you to track VM, GPU, cluster, and other training and deployment resource-associated costs.  Customizable alerts: Anodot allows you to set up custom daily, weekly, or monthly alerts based on spending thresholds, which means you will be notified when your Azure ML costs get out of hand.  AI-powered feedback: Budgeting has never been easier with our CostGPT, which informs your decisions with rapid, AI-powered recommendations. Reveal immediate insights into hidden expenses, pricing inefficiencies, unused resources, and more.  Comprehensive multi cloud visibility: Full support and visibility across all cloud platforms so you can see your cloud spend and activity all in one place. Cost-saving Recommendations: Anodot's recommendations cover a variety of Azure services, including Disk, VM, MySQL, SQL Data Warehouse, PostgreSQL, Cosmos DB, Maria DB, Load Balancer, Snapshots, Data Explorer, Redis, Kusto, RI Commitments, and App-Service. Want a proof of concept? Talk to us to learn how much you can save with Anodot’s tools. 

Autoscaling in cloud computing is the ability of a system to adjust its resources in response to changes in demand automatically. This guarantees that applications always have the resources they need to perform optimally, even during periods of high traffic. Autoscaling eliminates manual intervention, allowing your dev team time to focus on your product. All major cloud providers like AWS, Azure, and Google Cloud Platform offer robust autoscaling solutions with many features and capabilities. This is part of a series of articles about Cloud Management. What is Autoscaling?   Autoscaling in cloud computing is a feature that automatically adjusts the number of computing resources allocated to an application or service based on its current demand. This dynamic allocation ensures applications maintain optimal performance during traffic spikes while reducing costs during low-traffic periods. Adding or removing resources as per requirements improves overall system reliability and user experience and allows businesses to manage their cloud infrastructure efficiently, paying only for the resources they actually use. What Are the Types of Autoscaling?   There are two types of autoscaling: Horizontal Scaling: This type of autoscaling, also called Scaling Out, involves adding or removing instances as needed. It is ideal for applications designed for distributed environments. Vertical Scaling: This type of autoscaling is also called Scaling Up. It involves increasing resources such as CPU, memory, etc. of existing server instances. It is suitable for applications running on single large servers rather than multiple distributed servers. How Does Autoscaling Operate on the Cloud?   Autoscaling works as follows: Monitoring: Autoscaling systems continuously monitor various metrics of your application or server, such as CPU utilization, memory usage, network traffic, response times etc. Scaling Policies: Scaling policies are the conditions under which the autoscaling should occur. This is dependent on monitoring metrics. When a specific criteria is met, instances are scaled up or down. Scaling Action: When the monitoring metrics reach a certain threshold set up in the Scaling Policies, the system automatically adds or removes instances to curate to the demand. Load Balancing: Autoscaling systems work in sync with load balancers, distributing traffic to the resources the autoscaling system provides. Load Balancing: Autoscaling systems work in sync with load balancers, distributing traffic to the resources the autoscaling system provides.   Source: TechTarget  What Are the Benefits of Autoscaling?   The benefits of autoscaling in the cloud are: High Availability and Reliability: Autoscaling helps maintain your services’ availability by automatically adding resources in case of failures. Cost Effectiveness: It helps in setting up a cost-effective cloud infrastructure. Resources are only allocated when they are required. Management Simplification: A cloud infrastructure built on autoscaling principles requires minimal human intervention and is much easier to manage. Performance Improvement: Autoscaling ensures that your services and applications can handle a sudden surge in traffic without causing performance degradation. Resource Optimization: Autoscaling helps you match your resource allocation to demand. It scales up resources when demand increases and scales down when demand decreases. This eradicates the issue of over- or under-provisioning, resulting in an efficient and cost-effective infrastructure. Autoscaling vs Load Balancing    Autoscaling is a technique that adjusts the resources allocated to an application based on its current demand. In contrast, load balancing mainly focuses on distributing incoming network traffic across multiple servers. The key differences between Autoscaling and Load balancing are: Purpose: Autoscaling scales resources up or down to match demand, while load balancing distributes traffic among existing resources. Action: Autoscaling adds or removes resources while load balancing routes requests to different resources. Metrics: Autoscaling monitors CPU utilization, memory usage, and request count, while load balancing monitors response time, connection count, and traffic throughput. Scope: Autoscaling is often applied to an entire application or group of resources, while load balancing is typically applied to incoming network traffic. We can understand the differences using the following scenario: The Scenario A Fintech firm handles a substantial volume of daily transactions and experiences predictable spikes in activity during stock market opening and closing hours. It seeks to optimize its cloud infrastructure to accommodate these fluctuations cost-effectively while maintaining seamless performance even during peak periods. Solutions Implemented by the MSP Autoscaling: The Fintech’s MSP for cloud management utilizes autoscaling to dynamically adjust the number of cloud servers in real-time, responding to current transaction loads. This approach guarantees that the infrastructure is consistently optimized and appropriately sized. Load Balancing: The MSP configures load balancing to distribute incoming transactions intelligently across all available servers. This prevents any single server from becoming overwhelmed, ensuring optimal resource utilization and consistent transaction processing speeds even under heavy loads. Billing [CTA id="dcd803e2-efe9-4b57-92d5-1fca2e47b892"][/CTA] How Autoscaling and Load Balancing Work Together    As autoscaling adds or removes servers, the load balancer automatically updates its configuration to include or exclude them from traffic distribution. When autoscaling and load balancing are used in tandem, they provide: Seamless Scalability: The infrastructure can smoothly handle sudden increases in transaction volume by adding servers, i.e., autoscaling, and then efficiently distributing the traffic across them using load balancing. Cost Optimization: During periods of low activity, unnecessary servers are removed using autoscaling, which minimizes cloud spending. High Availability: Load balancing ensures traffic is automatically redirected to other healthy servers if one server fails, preventing disruptions. Performance Optimization: Load balancing prevents any single server from becoming a bottleneck and gives consistent performance even under high loads. Autoscaling and Cloud Providers   Autoscaling is a fundamental feature most major cloud providers offer, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). While the core concept remains the same – automatically adjusting resources to match demand – each provider implements autoscaling with its unique tools and terminology. Autoscaling in different cloud providers: AWS: Amazon Web Services offers Auto Scaling Groups (ASGs) that allow you to define scaling policies for different resource types like EC2 instances, ECS tasks, and DynamoDB tables. AWS also provides various scaling options like target tracking, step scaling, scheduled scaling etc Azure: Microsoft Azure offers Virtual Machine Scale Sets (VMSS) for autoscaling virtual machines and Azure Container Instances (ACI) for autoscaling containers. Azure also provides autoscaling for various Azure services, such as App Service, Azure Functions, Cosmos DB, etc. GCP: Google Cloud Platform offers Managed Instance Groups (MIGs) for autoscaling Compute Engine instances and Kubernetes Engine clusters. GCP also provides autoscaling for Cloud Functions, Cloud Run, etc. Related content: Read our guide to VMware CloudHealth Challenges of Autoscaling and How Anodot Provides Assistance   While offering significant benefits, autoscaling presents complex challenges that can strain resources and expertise. Partnering with seasoned industry professionals can be a strategic move to navigate these complexities effectively. Companies like Anodot, with their deep FinOps expertise in cloud scalability solutions, can provide invaluable support in optimizing your cloud infrastructure for growth and efficiency. Complexity: As a company's cloud infrastructure grows, it becomes very complex to manage. Managing scale and configurations across many services becomes a complex and tedious task. How Anodot helps: Anodot simplifies the management of complex cloud infrastructures by providing unified visibility, AI-powered insights, automated optimization recommendations, and customizable dashboards and reports. This helps you to gain control over your cloud environment, reduce costs, and improve efficiency.   Security: As scaling increases the attack surface and introduces new security challenges, it becomes essential that scaling maintains robust security measures (like encryption and intrusion detection), especially in newly allocated instances. How Anodot helps: Anodot provides AI-driven alerting out of the box and allows users to set up custom alerts and dashboards that track key security metrics, such as network traffic, access logs, and resource utilization. These alerts can be triggered when anomalies or unusual patterns are detected, helping teams proactively respond to potential security risks.   Cost Management: Scaling can lead to unexpected and unpredictable cost increases if not managed properly. Therefore, it is important to implement cost optimization strategies and choose the appropriate scaling configurations. How Anodot helps: Anodot’s insights can help identify unutilized resources, which can prevent overspending on unnecessary resources.   Predicting Scaling Requirements: In a complex cloud environment, proactively predicting scaling needs is often very challenging. How Anodot helps: Anodot uses artificial intelligence to analyze vast amounts of metrics in real-time. It can interpret unusual usage patterns and anomalies, addressing potential scaling needs before leading to performance degradation and service disruption.   Root Cause Analytics: Operating applications at scale can introduce vulnerabilities, such as downtime, especially during sudden traffic surges or configuration errors. How Anodot helps: Anodot’s correlation engine helps quickly pinpoint the root cause by analyzing relationships between different metrics and events. This accelerates troubleshooting and minimizes downtime.   Performance: Scaling is not straightforward. Increasing the number of service servers is often not enough. Related performance bottlenecks such as network limitations and database constraints, must be identified. How Anodot helps: Anodot uses artificial intelligence to analyze vast amounts of metrics in real time. It can interpret unusual usage patterns and anomalies, addressing potential scaling needs before they lead to performance degradation and service disruption.   Data Management and Compliance: Large volumes of data need to be managed while performing scaling operations. Ensuring data consistency becomes crucial and tricky, especially in distributed systems. How Anodot helps: Anodot's leading industry experts are well-equipped to handle the challenges of data management and compliance at scale. Seeking the help of such professionals is often a wise choice as your cloud infrastructure grows.   Human Skill Limitations: Scaling large infrastructures requires specialized skills and expertise. Organizations must hire highly skilled and experienced professionals and invest in training their current personnel. How Anodot helps: Dealing with all these challenges is often unfeasible or resource-intensive. It’s often a good idea to seek the help of industry professionals with years of expertise in this field. Final Thoughts   Autoscaling has emerged as a crucial component of modern cloud computing, empowering businesses to dynamically adapt their infrastructure to fluctuating demands. By automating the resource allocation process, autoscaling ensures optimal performance, cost efficiency, and high availability. These characteristics are necessary for modern-day cloud infrastructures to keep in sync with ever-increasing user expectations. Downtime is no longer acceptable. Any service disruption often results in significant financial losses and a decline in user trust. Embracing autoscaling as a core strategy is not just an option but a necessity for the organization. FAQs   What Is Autoscaling? Autoscaling is a cloud computing feature that dynamically adjusts the computational resources allocated to an application or service based on demand. What Are the Types of Autoscaling? There are two types of autoscaling: Horizontal and Vertical. Horizontal scaling includes adding or removing servers, whereas vertical scaling refers to increasing existing servers' resources, such as CPU and memory. Which Cloud Providers Provide Autoscaling Functionality? All major cloud providers, such as AWS, Azure, and Google Cloud Platform, offer robust autoscaling capabilities. Some common autoscaling functionalities are  AWS Autoscaling, Google Cloud Autoscaler, and Azure VM Scale Sets.

Why are Azure cloud costs such a head scratcher? A big factor is not knowing the main driver that causes your monthly bills to fluctuate. We might know the culprit behind your cloud costs— it’s almost always data transfer costs or changes to Azure bandwidth pricing. We'll give you the insider scoop so you can demystify your cloud budget and properly prepare yourself for your monthly Azure bill. What Is Azure Data Transfer? First things first: Data transfer and Azure bandwidth are the same thing. Outbound data transfers are referred to as data egress. Azure uses the term "Bandwidth" to refer to when data is moved in and out of Azure data centers or other data centers. Peering, Content Delivery Networks (CDNs), or ExpressRoute connections can also facilitate data transmission. The important thing you should remember about Azure Data Transfers is that Azure does not charge for inbound data flows. In other words, you won't need to pay a penny for traffic coming from the internet. However, this isn't the case for data that leaves Azure's network. Anything sent from your network incurs a data egress price charged per GB. How Do Data Transfer Bandwidth Costs Work? Source: Microsoft Azure  As we mentioned above, Azure bandwidth prices come into effect when data is transferred from an Azure data center to the Internet or another region. The good news is that your first 100GB of data egress is free each month. This means you can save on data transfer costs if you're a low or moderate user. Your data transfers will also be free if you move data around the same Azure region. But once you exceed 100GB per month, you'll be billed on a tier basis, with your price per GB decreasing as your data usage increases. This is why paying attention to your cloud waste is so important! You'll also have to start to pay once your data begins moving across regions, like if you're sending data from Europe to North America. Your monthly bill will increase depending on the transfer method (ex: transferring from high to low network bandwidth or transferring low amounts of data at high frequency or vice versa). So, check whether you're sending data via a transit ISP network or Microsoft's premium global network. Egress costs can be particularly steep depending on your company and trade. For example, industries with high outbound data transfer needs, such as gaming, streaming, or bandwidth-heavy services, will incur steep costs. Data Transfer Cost Breakdown? We'll go into detail about how Azure bandwidth pricing fluctuates. Remember: your costs will change because of: 1. Where you send the data. 2. How you send the data. 3. How much data you send. VNET (Virtual Network) Data Transfer When you move data within the same Azure Virtual Network (VNET) or the same subnet, you won't get charged. In other words, you save by staying local. VNET peering within same Azure region VNET Peering lets you direct traffic across VNETs using a private IPv4 address. Both data ingress and egress are charged at the peered-together VNET ends. Data transfer within the same availability zone or any data transfers you receive will be free. If you perform a data transfer from Azure Origin to Azure Front Door or to Azure CDN, that will be free as well. Regional VNET peering, or peering within the same VNET region, costs about $0.01 per GB for inbound and outbound data transfers. VNET peering across different Azure regions VNET peering between established VMs across different regions is known as global VNET peering. Prices for this service vary depending on what zones you're dealing with, as you'll be charged based on the transfer rate specific to your VM's zone. Here's a breakdown of the prices: Intra-continental data transfer If you're transferring data within the same continent but across different regions, you'll run into the following charges: Inter-continental data transfer The price is based on the source continent if you transfer data from one continent to another. So, the prices would look like this:    Internet egress (Microsoft Premium Global Network) Microsoft's Premium Global Network bases internet egress pricing on a tiered system depending on the amount of outcoming data you're sending and from where you're sending that data. You will be charged for every byte that leaves your Azure network for another cloud environment or the Internet. It doesn't matter if you're sending the data only regionally or worldwide—you'll incur a fee. Here's what you should expect for costs:   Here's what you should expect for Routing Preference ISP Network egress pricing: How to Optimize for Azure Bandwidth Pricing The key to optimizing Azure prices is first understanding and then controlling data egress. You can minimize outbound data transfer and optimize your architecture and data outflow corridors. Consider the other best practices to keep your budget reasonable: 1. Keep your data in the same region by optimizing your application architecture to minimize data travel times. 2. Eliminate or constrict cross-zone and cross-region data transfers. The more you move data across different zones, countries, or regions, the higher the bill. 3. Deploy cloud resources from low-cost regions. Try to deploy your resources from regions with low or zero data transfer costs. Consider security policies and compliance guidelines. 4. Compress and deduplicate your data with incremental synchronization before transferring. Also, delete and archive irrelevant old data! 5. Review your transfers and make sure each serves its purpose. If you don't have the bandwidth to do so, consider investing in a third-party tool (we'll get into more detail on that hack in a bit). How to Improve Azure Data Ingress & Egress Tracking If you’re ever concerned that Azure’s reporting on data bandwidth is lacking, – there’s an easy way to get full visibility into your data flow and, by doing so, massively improve your budget efficiently. As mentioned above, third-party tools are the key to tracking your transfers to ensure you’re not inflating your budget. Tools like Anodot help you identify optimization opportunities that can lead you to save up to 40% on your annual cloud spend. Here’s how. Anodot’s cost management tools mean you get all your multicloud data in one place. one place where you look back up to 24 months to see changes down to the hour and one place for complete understanding visibility into how your Azure bandwidth behaves and impacts hour and upwards, your budget. Other Anodot tool features include: - AI-Powered Recommendations: AI-powered support that improves resource utilization. - Automated Anomaly Detection: Customizable alerts that improve real-time budgeting and help you react immediately to unusual data trends, - Next-Gen Forecasting: High-powered analyses to help you best plan for future spending. - Multicloud Visibility: Next level support and visibility across all cloud platforms so you can see your cloud spend and activity all in one place. Why Anodot? We’ve been demystifying cloud costs for FinOps organizations for years. We want to ensure you never have to worry about overspending, and with our automated anomaly detection and customized alerts paired with AI-powered feedback, you won’t even need to lift a finger to start cutting costs. Want a proof of concept? Talk to us to learn how much you can save with Anodot’s tools.

If your business has predictable compute workloads and wants to save on Azure spend, Azure Reserved Instances can make you the FinOps department’s new favorite person. But we’re getting ahead of ourselves. Before we tell you how you can start saving on your cloud spend, let’s define a few terms.  What are Azure Reservations?   Azure Reservations, like Azure Savings Plans, are Azure pricing plans that offer you discounts in return for your commitment to a certain service for one or three years. You can pay for the reservations either upfront or every month. The good news is there aren’t any drawbacks to monthly payments – just keep in mind that the monthly payment option is only available for Azure products, not third-party products.  In other words, if you’re operating with a consistent workload, Azure Reservations are a pricing hack to help you save up to 72% on costs… for the most part.  To examine the fine print, we first need to divide Azure Reservations into two categories: Reserved Instances for only Azure VMs, and Reserved Capacity, a pricing option for Azure storage, data services, and apps.  Reserved Instances Azure Reserved Instances enables you to reserve a subset of VMs for either a one- or three-year period. By prepaying for that Azure virtual machine commitment, you can save up to 72% on costs. It's important to remember, though, that this discount only applies to your VM costs. You won't be getting any cuts for your installed software, storage, or networking costs.  Reserved Instances requirements The good news?  You can apply Reserved Instance pricing to your Linux or Windows Azure VMs. If you're working with Windows VMs, you can save up to 80% in comparison with Pay-as-You-Go prices. If you're using Linux VMs, you can save up to 72%.  The bad news?  Not all VMs are eligible for this discount. Those from the A-series, Av2-series, and G-series are excluded, as are promotional VMs or images in preview. Make sure to be careful when you review your eligibility! Visit the Azure site for more info. Reserved Capacity Reserved Capacity also offers discounts if you commit to services for a one or three year period, same as Reserved Instances. The two differ in that Reserved Instances covers everything but Azure VMs, like Azure Disk Storage, SQL Database, and more (don't worry, we'll explain this in complete detail below!).  Depending on the service you commit to, you can save up to 65%. But tread carefully—depending on what is excluded from the deal, you may still have to pay full price for storage, networking, or software.  Here’s what’s included and excluded for each resource for Reserved Capacity:  Resource Type One Year Commitment Three Year Commitment Reserved Virtual Machine Instance Savings up to 32% Savings up to 72% SQL Database reserved vCore Savings up to 21% Savings up to 33% Azure Disk Storage reservations Savings up to 5% Not included in offer Azure Synapse Analytics Savings up to 37% Savings up to 65% Azure Database for MySQL Savings up to 42% Savings up to 61% Azure Database for PostgreSQL Savings up to 39% Savings up to 59% Azure Database for MariaDB Savings up to 42% Savings up to 61% Azure Databricks Savings up to 39% Savings up to 61% Azure Cache for Redis Savings up to 33% Savings up to 65% Azure App Service Premium V3 Savings up to 25% Savings up to 40% Azure App Service Isolated Not included in offer Savings up to 40% Reserved Capacity requirements To qualify for Reserved Capacity, you'll need a minimum of 8vCores of SQL database or 20,000 RUs (Request Units) for Azure Cosmos DB. If you're looking for App Services discounts, you must use Premium V3 and Isolated tiers.    How do Azure Reserved Instances work?   The biggest thing you should remember about Azure Reservations is that it operates on a "use it or lose it" system. If you aren't matching the hour-by-hour reservation you made for your resource, that's money lost. In other words, unused reservation time will not be carried over.  On the other hand, if you exceed your reserved level, you'll be charged pay-as-you-go rates for however much you exceed your agreed-upon amount.  The diagram below illustrates how this works:   [caption id="attachment_16228" align="aligncenter" width="512"] Source: Microsoft[/caption] If you need to shut down your resources, Azure will automatically try to apply your reservation discount to another resource that matches your agreed-upon scope. If no other resources match that scope, the reservations will remain unused. Luckily, you can always update your reservation scope even after buying it, so you can adjust things as needed.  Another insider tip: if you have VMs in a different subscription assigned to your account, you can make that scope "shared", which tells the system to apply the reservation discount across all account subscriptions.  Best resources for Azure Reservations Accurately estimating the resources you’ll use per reservation is the key to Azure Reservations savings. This is because all reservations but for Azure Databricks are applied hourly, and if you use less than your reservation amount, those resources you’ve paid for go unused. In other words – money wasted.  Let’s use VM Reserved Instances for an example. You’ll want to be certain of your VM size before purchasing because you can’t update the size during the reservation period. There’s an easy way to review your historical VM usage to decide on the best Azure Reservation for your organization. You can do this by:  Go to the Azure portal.  Search for and click on Subscriptions.  Select Billing → Invoices.  Use your most recent invoice or the invoice that best represents an average period of VM usage.  Select Download csv (located under Usage Details).  The file should look something like this:  [caption id="attachment_16229" align="aligncenter" width="512"] Source: Microsoft[/caption] Use this data over multiple periods to calculate your average VM usage. Make sure to consider positive or negative growth for your company as well.  Remember that though VMs aren’t used 24/7, you might still want to switch to reserved instances, especially based on break-even analysis when you compare those pay-on-demand numbers to reserved instance costs.  Use Azure resources or third-party resources like these to project best how much hourly reservation you need so you won’t end up overspending on tools you don’t use.  Purchase recommendations You can don’t need to worry about planning your Azure Reservations approach – Azure will deliver you automated reservation recommendations once you get started. Using data based on your hourly usage over 7, 30, and 60 days, Azure calculates your reservations compared to the pay-as-you-go cost you would have incurred and recommends what quantity you should use to maximize your savings. You typically use 1,000 VMs for all your workloads, though this need sometimes exceeds 1,500. Azure’s calculations will then include estimates of 1,000 to 1,500 VMs. Though if the demand for 1,500 VMs is very infrequent, the calculations might be for only 1,000 VMs. Important things to remember when you receive your purchase recommendations for VMs:  These recommendations are based on individual VM sizes, not the entire size family.  After you commit to a reservation amount, the recommended quantity of scope is reduced that same day. This is because the reserved VMs are now excluded from the resources you can access Azure Reservations.  How to purchase your first Azure Reservation   If you feel based on the information we've provided above that Azure Reservations are a good fit for you, here's how you can go about getting your discounts: Step 1: Determine who can purchase the reservations Before you start purchasing, you'll need to make sure that you're either the Azure subscription owner or that you have access to a reservation purchaser role, like the Enterprise Agreement or Microsoft Customer Agreement billing admin roles.  Pro tip: Enterprise Agreements, Microsoft Customer Agreement Subscriptions, and Pay-As-You-Go Subscriptions are the only roles that support reservations.  Step 2: Determine which scope you should buy Now that you’ve confirmed who can purchase your reservations, you’ll next want to determine your reservation scope. There are three reservation scope options:  Single resource group scope. This option applies the reservation discount only to matching resources in a certain Azure resource group.  Single subscription scope. This option applies the reservation discount to all matching resources in your Azure subscription.  Shared scope. This option means you can apply your discounts to all matching resources used by any subscriptions paid for by the same billing source. For instance, your billing scope would be enrollment if you have an Enterprise Agreement Azure Subscription. In contrast, if you had Pay-As-You-Go individual subscriptions, your billing scope would be all eligible subscriptions.  Step 3: Determine which service you wish to buy reservations for You’ll receive a different percentage discount depending on your chosen service. To get an idea of how much you can save depending on your service of choice, review your options below:   Resource Type One Year Commitment Three Year Commitment Reserved Virtual Machine Instance Savings up to 32% Savings up to 72% SQL Database reserved vCore Savings up to 21% Savings up to 33% Azure Disk Storage reservations Savings up to 5% Not included in offer Azure Synapse Analytics Savings up to 37% Savings up to 65% Azure Database for MySQL Savings up to 42% Savings up to 61% Azure Database for PostgreSQL Savings up to 39% Savings up to 59% Azure Database for MariaDB Savings up to 42% Savings up to 61% Azure Databricks Savings up to 39% Savings up to 61% Azure Cache for Redis Savings up to 33% Savings up to 65% Azure App Service Premium V3 Savings up to 25% Savings up to 40% Azure App Service Isolated Not included in offer Savings up to 40%   Remember, reservation hours cannot be carried forward or accumulated. These are use it or lose it savings. Budget and forecast with care.  Step 4: Make your purchase You know you have the authority to make your purchase, you've selected what you want to buy – now you only need to pull the trigger. You can do that by:  Log into your Azure Portal account.  Navigate to All Services → Reservations.  Select Add from the top menu bar to buy your new reservations.  Select your chosen product using the "Select the product you want to purchase" pane.  Add your product to the cart. Review one last time and make your purchase!  Worried you’re in the wrong place? This is what you should see on step 4:  [caption id="attachment_16230" align="aligncenter" width="461"] Source: Microsoft[/caption] Azure Reservations combined with Azure Hybrid Use Benefit   There’s actually a hack where you can combine Azure Reservations with another discount plan called Azure Hybrid Use Benefit. You’ll need to make sure you’re already a Microsoft Enterprise Agreement customer and that you’re using Software Assurance.  If you check those boxes, you can stack Azure Hybrid Use Benefit (HUB) discounts with Azure Reservation discounts.  Combining these two can help you save up to 80% if you agree to a three-year reservation.  Get 100% visibility into your Azure Reservation Instances spend   Azure Reservations, Azure Savings Plans, and Azure Hybrid User Benefits aren’t the only way to save on your Azure spending. You can save up to 40% by improving your visibility into how much you’re paying in Azure Reservation Instances costs with Anodot.  Anodot’s cloud cost management tools mean you can get detail on your Reserved Instance (RI) Utilization in one page, with details on your purchased RIs and utilization data on current and future reservations. You can get budget projections and data retention periods from 18 to 24 months that show granular hourly changes.  So when we say 100% visibility into your Azure spend, we mean 100% visibility into your Azure spend. We help you make sure that every penny is putting in work! Above is an example of what one of our RI-specific dashboards looks like to ensure 100% utilize for your Azure RIs. Anodot has a Commitment Dashboard which displays all you need to know about your Azure spend, breaking down On demand, Spot, and Savings plans in addition to RIs – all in one place.   Anodot’s dashboards are designed to educate you on how much your spending, how much yoru saving, and, most importantly, how much you’re missing out on. So if you’re worried that you might not be as saving as much as you should with Azure Reserved Instances, our dashboards can help you calculate those exact numbers and configure a strategy to help you save more.  Why Anodot? Demystifying cloud costs for FinOps organizations is what we do. With our real-time anomaly detection and customizable alerts, you never need to worry about overspending. Optimize your budget with AI-powered feedback and don’t worry about even having to lift a finger.  Want a proof of concept? Talk to us to learn how much you can save with Anodot’s tools.  

Managed Service Providers (MSPs) are definitely in a competitive market. If you're checking out Anodot, there's a good chance you're an MSP looking for a partner who can provide the right mix of tools and services to help you stand out to potential prospects. However, landing the client is only the start of the sales cycle. So, how can MSPs keep increasing profits while maintaining the quality that initially won them that business? This blog will explore two sales models that may help keep the revenue flowing in: selling our tool with FinOps support and a FinOps service.  Let’s see how these models stack up and how MSPs can use them to boost their service offerings and drive growth.   What is the Anodot Reseller Model?   The Anodot reseller model lets MSPs expand their service offerings without a huge resource investment. MSPs can establish reliable revenue streams by purchasing Anodot at wholesale prices and selling it at a markup while providing their clients with valuable cloud cost optimization tools. Basically, everyone is happy! The Mechanics of Reselling Anodot Reselling Anodot isn’t just about a handshake and calling it a deal on our end. We equip you with everything you need for success, including training, ongoing support, and optional tips on cost optimization. BONUS: This model is highly scalable, as MSPs can serve numerous clients with a small team, leveraging the tool's automated features to deliver value consistently. Here's a breakdown of the mechanics: Revenue Model: Tied to cloud consumption, allowing for stable income without extensive service hours. Reduced Dependency: The tool reduces reliance on individual consultants, mitigating risks associated with personnel changes. Scalability: Flexibility in support hours enables MSPs to accommodate varying customer demands efficiently. With the Anodot resale model, MSPs can leverage their existing relationships and expertise while minimizing operational hassles. They can expect to deliver valuable solutions that meet their clients' immediate needs and set them up for long-term success. “As a steward of our clients’ cloud spend, we are proud to use Anodot as part of our FinOps toolbox to identify scenarios to continuously optimize cloud environments and eliminate hidden waste. With Anodot, we can ensure every client infrastructure dollar spent is maximized.” Sean Donaldson ~ Protera CTO Selling Comprehensive FinOps Services   Reselling Anodot brings scalability and less dependence on staff, but offering full FinOps services is an alternative sales model that MSPs can utilize. Whether or not you use the Anodot tool, this structure provides customized solutions for financial operations while letting MSPs show off their expertise in managing cloud costs. Exploring the Scope of the FinOps Sales Model This framework expects a detailed analysis of cloud costs, usage patterns, and optimization opportunities. During the initial months of engagement, MSPs work to build a FinOps culture, establish visibility, and implement significant cost-saving measures. What are the ups and downs of implementing this strategy? Potential for Higher Revenue: Offering comprehensive services at a fixed or hourly rate can increase MSPs' revenue—especially when they team up with Anodot! Clear Value Attribution: Clients see the value of the service coming from the MSP, which boosts their credibility. Challenges of Sustained Engagement: Maintaining momentum after the initial optimization phase requires ongoing monitoring and strategic communication, which can be challenging depending on the workload. While this model requires considerable resources, it helps MSPs build stronger client relationships and position themselves as trusted advisors. Tip: By integrating Anodot, MSPs can provide a well-rounded approach that boosts cost efficiency and enhances customer satisfaction. Aligning Customer Expectations with Service Delivery   At the end of the day, MSPs count on their customers' satisfaction and loyalty for their revenue. We've looked at how our reseller model stacks up against a FinOps service model, but let’s take it a step further and see how they both aim to deliver the best success for their customers. Managing Expectations Reselling Anodot makes it easy to communicate service offerings and expected outcomes. Clients get a clear value proposition, and MSPs can use the tool's features to deliver reliable results. However, FinOps services need clear goals and timelines because clients want and need to see real savings and efficiency gains. No matter which model you pick, keep these guidelines in mind: Expectation Setting: Clearly outline the scope and benefits of each model to align with client objectives. Ongoing Communication: Regular updates and progress reports foster transparency and trust. Flexibility and Adaptability: Be prepared to adjust services based on client feedback and evolving needs. Ultimately, both approaches focus on MSP customers, but with Anodot, you can expect quicker and easier reports for that all-important customer retention. Scaling Your FinOps Services with Anodot   Anodot Enhances Scalability: While this model requires considerable resources, it helps MSPs build stronger client relationships and position themselves as trusted advisors. However, scaling these services effectively across a large client base can be a challenge. Integrating Anodot with your FinOps services solves this problem. Anodot's automated features and machine learning capabilities allow MSPs to deliver consistent value and optimize costs for a growing number of clients, maximizing the return on investment for both the MSP and the client.   Choosing the Right Model for Your MSP   Both the Anodot resale model and FinOps services have unique benefits for MSPs. Choosing between them depends on the MSP’s goals, resources, and clients. Hopefully, our quick overview helps clarify the differences so MSPs can tailor their offerings to provide maximum value for their clients and grow their business. As a quick reminder, here are the findings: For MSPs seeking a scalable, low-risk option, reselling Anodot enables rapid expansion without significant resource investment, allowing MSPs to tap into the growing demand for cloud cost optimization tools. MSPs prioritizing building strong client relationships and offering customized solutions might find comprehensive FinOps services a better fit (just remember to keep accountability as a key focus with this model). Regardless of the chosen model, MSPs should prioritize customer satisfaction, ongoing communication, and continuous improvement. By doing so, they can position themselves as trusted partners in the cloud cost optimization landscape, deliver lasting value to their clients, and achieve sustainable growth. Interested in our reseller program? We’d love to have you on board! Let’s connect so you can partner with us and start saving and earning in the cloud.

Green Operations (GreenOps) is an approach to creating an eco-friendly cloud. The aim is to minimize energy waste, increase renewable resources, and decrease their carbon footprint on the planet. Several public cloud providers are aiming to become carbon-negative. By 2030, Google Cloud plans to operate on carbon-free energy around the clock. Microsoft Azure has committed to being carbon-negative by 2030, and AWS aims to run its operations on 100% renewable energy by 2025. This guide will cover GreenOps' key concepts and how to integrate them to cut costs and lessen environmental impact.   What is GreenOps, and how does it make a sustainable cloud?   GreenOps integrates eco-friendly practices into cloud and business operations to minimize the ecological impact of technology use. This approach helps businesses leverage the power of the cloud while reducing energy consumption, optimizing resource utilization, and supporting renewable energy initiatives. Adoption rates for GreenOps have been rising steadily. In 2024, the focus on cloud cost management, sustainability, and GreenOps is expected to increase by 35%, greatly impacting cloud resource use and energy efficiency. Let’s go over and see what these strategies look like.   Principles and Practices of GreenOps GreenOps involves implementing several sustainable practices: Energy Efficiency First, it's about optimizing data centers and IT infrastructure to consume less energy. This involves leveraging FinOps practices to identify cost-saving opportunities by reducing unnecessary cloud resource usage.  GreenOps principles guide energy efficiency enhancement, making your cloud setup leaner and greener. By doing so, you not only help the environment but also significantly cut down on energy bills. (It’s a win-win for both financial and environmental sustainability!) Resource Management Next, GreenOps emphasizes reducing waste and promoting recycling within the organization. Implementing FinOps strategies ensures that cloud resources are used efficiently, minimizing digital waste. Together, these practices support both cost-effectiveness and environmental responsibility. Sustainable Sourcing Finally,  all products and services must be sourced from environmentally friendly suppliers. Select cost-effective yet sustainable vendors who provide transparency in their operations and promote green practices.   [caption id="attachment_16062" align="alignnone" width="725"] Source: Greenpixie[/caption]   Combining FinOps and GreenOps   Blending FinOps and GreenOps strategies benefits organizations by optimizing the cloud's financial performance and environmental sustainability. Aligning financial management with sustainability goals helps control cloud spending and reduce the carbon footprint, ensuring resource efficiency, cost savings, and enhanced corporate responsibility.  So, what kind of benefits can be expected from this combo?  With over 30% of cloud use estimated to be wasted, the urgency for GreenOps is greater than ever. Benefits of Integration    Cost Savings Optimizing data centers and cloud infrastructure can help companies achieve significant energy savings. For instance, Google’s data centers utilize AI to reduce cooling energy use by up to 40%​.  Environmental Impact Implementing GreenOps can cut cloud data center energy use by 20-40%, bringing substantial environmental and cost advantages. This is done via resource optimization and energy-efficient infrastructure, lowering operational costs and enhancing sustainability. Operational Efficiency Right-sizing and auto-scaling cloud resources help companies use only what they need, boosting resource efficiency and cutting costs. Organizations that implement these practices can see an increase in resource utilization from 10-15% to 50-70%​​. Regulatory Compliance As many regions have already passed regulatory standards for environmental sustainability and others are considering future rules, you can keep pace with the game if you start implementing GreenOps policies now. Your compliance and legal teams will thank you for helping them dodge future penalties and other legal issues. We’ll go into more detail below about the new regulations entering the scene and how you can avoid potential legal fines—and help the environment!   Recent Environmental Regulations and GreenOps   Environmental regulations in Europe have been on the rise since the early 2010s. For example, EU regulatory reporting requirements like Germany's Energy Efficiency act which requires a 26.5% reduction in carbon emission levels from 2008 to 2030 is a big incentivizer for companies to adopt GreenOps solutions. But the most recent initiative you should be aware of is CSRD.  The EU’s CSRD (Corporate Sustainability Reporting Directive) is driving major changes in GreenOps. The CSRD drives changes in company behavior to bring sustainability on part with mandated disclosure efforts, and went into full effect January 5, 2023. Approximately 50,000 companies in EU Member States had until July 2024 to incorporate these mandates. Penalties for non-compliance are determined by state and can result in fines.  The process of determining if a company is included in CSRD’s scope is complex. We recommend you consult your legal department to determine if your organization is included. There are a few general guidelines you can review to get an idea of if you should be worrying about CSRD or not:  Does your company have securities listed on an EU-regulated market? If your company has securities listed on certain EU stock exchanges like Euronext Dublin, then you may need to be CSRD-compliant.  Is your company considered a medium or small organization? If your company has less than €25 million in total assets, net turnover less than €50 million or less than an average of 250 employees, you might need to be CSRD-compliant.  Is your company the parent company of a group considered a large organization? If not, then you may need to be CSRD-compliant. Regulation Description Impact on Organizations How GreenOps Can Help CSRD (Corporate Sustainability Reporting Directive) (EU, January 5, 2023) Requires large companies in the EU to disclose environmental impact alongside financial data. Increased reporting requirements and potential fines for non-compliance. Streamline data collection and reporting for environmental metrics. Optimize resource management to reduce environmental impact. Germany's Energy Efficiency Act (2015) Mandates a 26.5% reduction in carbon emission levels from 2008 to 2030. Incentivizes companies to adopt energy-efficient practices. Identify and implement energy-saving measures. Track & report energy consumption data. Future Regulations Anticipated environmental regulations at regional, national, and international levels. Potential compliance challenges and increased operating costs. Proactive adoption of GreenOps practices can help mitigate risks and costs.   If you do think you may need to be CSRD-compliant and haven’t yet started on the process, GreenOps is the way to help your FinOps organization… but that’s not to say that you can seamlessly start integrating FinOps and GreenOps at the drop of the hat.    Pain points with GreenOps and solutions     So far, integrating a GreenOps strategy into a FinOps framework for cloud services looks like a win, but like any new cultural shift, there are bound to be challenges.  So, be prepared for these potential roadblocks when introducing GreenOps to the cloud.  Overcoming Common Challenges Cultural Resistance Employees may resist changes to learn new skills and adapt to new processes, especially if they already have a rhythm in their cloud environment. Solution: Foster a culture of sustainability and financial accountability through training and communication. Engage employees by highlighting the long-term benefits of GreenOps and FinOps, including cost savings and positive environmental impact. Encourage participation and feedback to ensure everyone is on board with the changes. Complexity Managing both FinOps and GreenOps can be complex in the cloud. The integration requires managing multiple aspects of cloud operations, from cost optimization to sustainability practices, which can be overwhelming without the right tools and processes. Solution: Utilize automated tools and technologies to simplify FinOps processes. Implementing cloud management platforms that can streamline operations and reduce the burden of manual management. Tools that provide real-time data and insights can help make informed decisions quickly and efficiently. Measurement Difficulties Measuring the impact of GreenOps and FinOps initiatives can be challenging. It involves identifying the right metrics, tracking progress in complex cloud environments, and ensuring data accuracy. Solution: Establish clear metrics and regularly review progress. Define specific, measurable goals for financial and environmental performance. Track energy consumption, carbon footprint, cost savings, and resource utilization. Regular reviews and adjustments based on data insights will help maintain the effectiveness of these initiatives.   How is Anodot assisting in GreenOps practices?   As mentioned before, juggling various operational frameworks in the cloud can be challenging. Your company might be just getting the hang of FinOps and worry that adding another operational layer could disrupt cloud efficiency. But, as a certified FinOps cost management platform, we can help.  With Anodot, we can provide the tools for FinOps in the cloud, allowing you to concentrate on cloud sustainability without sacrificing cost efficiency and optimization. Establishing Sustainable FinOps through Greenpixie Integration We’re partnering with Greenpixie to seamlessly integrate cloud carbon emissions data into our FinOps platform, paving the way for an innovative solution in sustainable cloud management. Through this collaboration, we will unify cost and carbon emissions data within a single interface using Greenpixie's ISO-verified methodology. This integration will give engineers precise insights to minimize cloud inefficiencies and environmental footprint. With this partnership, we aim to offer customers: An integration for precise, real-time emissions data Optimization of cloud operations and promotion of sustainable practices Alignment of cloud efficiency with environmental responsibility Solutions to assist organizations in safeguarding the planet and their profits Effective tackling of global sustainability challenges Read more about our collaboration for sustainable FinOps.   Harnessing Today's Anodot Platform for Eco-Friendly Operations   With continuous monitoring and deep visibility, businesses gain the power to align FinOps, DevOps, and Finance teams to reduce their total cloud bill and implement GreenOps strategies effectively.  Here's how: Cloud cost dashboard: Multicloud Visibility—Anodot seamlessly combines all of your cloud spend into a single platform. Monitor and optimize your cloud cost and resource utilization across AWS, GCP, and Azure.  Eliminate Waste: Anodot’s easy-to-action savings recommendations enable your DevOps team to easily implement spending and service changes that can drive significant savings.  Allocate Costs: See cost causation and allocate spend by service, business unit, team, and app with deep visibility across AWS, Azure, GCP, and pod-level Kubernetes.  Enable FinOps: Avoid bill shock with near real-time alerts and insightful, ML-driven forecasting.  Granular Insights: Detailed tracking of spending and usage across Kubernetes clusters provides insights that no other cloud optimization platform offers. This allows businesses to identify under-utilization at the node level and optimize resource use, directly supporting sustainability efforts. Not using FinOps yet, or need a partner to maximize your efforts? Let's chat.   Conclusion GreenOps + FinOps = Sustainable Cloud   Organizations are starting to be mindful of how their operations contribute to carbon emissions and are working on reducing their carbon footprint. At first glance, working in the cloud may not appear to have a significant impact on the environment. However, powering data in the cloud consumes substantial energy, and inactive cloud resources result in wastage. If you're diving into GreenOps, understanding your FinOps and cloud costs can reveal where cloud waste occurs. And having a partner who can show you that insight can greatly help your cloud become more green.  Together, let’s do our part and make a more sustainable cloud!

Trying to refine your org structure and already using VMware Tanzu CloudHealth? You might have stumbled across the word FlexOrgs. If you have, you’re likely scratching your head and wondering what FlexOrgs are and, more importantly, if they can help you.  Still unsure how to get started? Don’t worry. We have the answers to your FlexOrg questions (and more!). Our FlexOrgs in a nutshell guide should give you an idea of what to expect and see if it’s the right choice for your cloud environment. What Are FlexOrgs?   FlexOrgs is a VMware Tanzu CloudHealth-specific feature that helps manage user access, sharing, and delegation across your organization’s hierarchy.  The following are some of the key components of FlexOrgs: Role Documents: These documents define user permissions within certain platforms (ex: view-only, edit, or create).  Organizational Units (OUs): Each OU gets its assigned cloud infrastructure resources, representing different parts of your organization (e.g., teams, business units, etc.).  Users: Anyone who has access to your Tanzu CloudHealth platform. User Groups: Multiple users who have similar OU responsibilities. User groups help define FlexOrg relationships. For example, here’s a breakdown of how you can build out your hierarchy with a TLOU (Top-Level Organizational Unit) and other hierarchical child OUs:  [caption id="attachment_16051" align="alignnone" width="725"] Source: VMWare[/caption]   How Do FlexOrgs Work?   If you’re looking to build out or optimize a pre-existing FlexOrg, you’ll want to follow these steps:  Determine who belongs where in your organizational units (OUs), role documents, and user groups. Ask yourself who fits where and who needs what levels of permissions. Consider how many tiers your organization requires and how you should define each tier. Keep in mind things like security (who should have access to what documents), and visibility (who needs access to what documents). Determine where you want to pull your data. If you’re using a CSP, review your platform of choice. AWS, Azure, and GCP all have the ability to build an organizational structure, so make sure you’re not duplicating someone else’s work. If you’re using an IDP or an SSO service, you can recreate that structure in Tanzu CloudHealth and simplify things.  Review your account, subscriptions, and projects. Make sure you’re familiar with your assignment strategy. Accounts and users should flow much smoother via FlexOrg's organizational hierarchy. Consider your organization's goals. Make sure you’re clear on what your organization is trying to accomplish. Do you want better delegation, user visibility, or security? These should inform how you build your FlexOrg. Assign cloud resources. Next, you’ll want to assign your cloud resources (like your GCP or AWS accounts) to your OUs.  Create user groups and assign role documents and permissions. Final step! Create your user groups and use your brainstorming from step one to assign users. You should assign permissions based on your role documents.   Drawbacks of using FinOrgs   While VMware Tanzu CloudHealth's FinOrgs feature simplifies cloud structure and tag organization, it's not as flexible as some other tools on the market. Limitations include: Perspective Building: To view tags in cost reports, you must construct a Perspective. However, these mappings may take up to 24 hours to load fully. Restricted Scope: Perspectives can be built using only tags, resources, accounts, and specific services. Separate Systems: Business Mapping and Cost Allocation are managed in different sections, adding layers of complexity. For MSPs and Enterprises needing to respond promptly to cloud environment changes, slow load times and multitasking with tags and allocation could raise manual workload, which is not ideal in a FinOps organization.   Why You Should Migrate from CloudHealth to Anodot Feature CloudHealth Anodot Supported Infrastructures VMware, AWS, Azure, Google Cloud, K8s, Alibaba, OCI AWS, Azure, Google Cloud, K8s Virtual Tagging, Cost Categorization, and Cost Allocation Preconfigured, customization reporting for each persona Preconfigured, customizable reporting for each persona FinOps Culture and Root Cause Analysis Builds your FinOps culture and enables drill-in root cause analysis Builds your FinOps culture and enables drill-in root cause analysis Showback and Chargeback Yes Yes Rightsizing Savings recommendations Very few basic recommendations across primary services, automatable, savings projections, inaccurate, and inflated. Reduce waste and maximize utilization with 40+ savings recommendations highly personalized to your business and infrastructure Forecasting and Budgeting Inaccurate forecasts frustrate many customers AI-driven forecasting ensures high-certainty predictions at various levels of detail Anomaly Detection and Management Set up email alerts for detecting deviations from historical trends. No distinction between noise and impact activity Fully-automated AI not only detects anomalies in real-time but the root cause as well. Feature alerts the appropriate teams prompting quick response and resolution Extensibility Multiple fractured APIs hinder data accessibility Single, robust, easy-to-use API Ease of Use Not user friendly or instinctive interface Intuitive and responsive display Pricing Unpredictable pricing taxes customers at 3% of cloud spend, offered at low cost by MSPs Single, robust, easy-to-use API Company Status CloudHealth Technologies was acquired by VMware in August 2018. Then, Broadcom acquired VMware in November 2023, resulting in delays to product development and innovation for its users Anodot has recently doubled the size of the team supporting our FinOps product, MSPs, and publishes a public-facing roadmap that promises rapid innovation Good news - if you need a tool similar to FinOrgs but require flexibility and agility to respond in a fast-paced cloud infrastructure, Anodot's Cloud Center is designed for FinOps organizations aiming to lessen admin overhead and automate processes. Anodot's Cloud Center: A More Comprehensive Solution Anodot's Cloud Center offers a more comprehensive and flexible approach to cloud cost management compared to FlexOrgs. It provides a unified platform for visualizing and analyzing your cloud costs, enabling you to gain deeper insights and make data-driven decisions. Key Advantages of Cloud Center: Unified View: Easily visualize your cloud costs across different departments, teams, or lines of business. Automated Filtering: Automatically filter data based on your selected view, providing tailored insights for each group. Enhanced Flexibility: Enjoy greater flexibility in creating and organizing cost categories compared to FlexOrgs. Integration with Existing Tools: Seamlessly integrate Cloud Center with your existing cloud infrastructure and tools. Scalability: Easily scale Cloud Center to accommodate your growing organization and cloud resource needs. How Cloud Center Works Cloud Center leverages advanced analytics and machine learning to provide actionable insights into your cloud costs. By mapping your organizational structure to your cloud resources, you can: Identify cost-optimization opportunities: Pinpoint areas where you can reduce spending without compromising performance. Allocate costs accurately: Ensure that costs are allocated fairly across different departments or teams. Track usage trends: Monitor your cloud usage patterns to identify anomalies and optimize resource allocation. Why Choose Anodot? Comprehensive Solution: Anodot offers a comprehensive suite of FinOps tools, including cost optimization, anomaly detection, and user access control. Scalability: Easily scale Anodot to accommodate your growing organization and cloud resource needs. Flexibility: Anodot's flexible approach allows you to adapt to changing business requirements. Expert Support: Benefit from Anodot's team of FinOps experts who can provide guidance and support. Conclusion If you're looking for a more powerful and flexible solution to manage your cloud costs, Anodot's Cloud Center is the answer. By providing a unified view, automated filtering, and enhanced flexibility, Cloud Center empowers you to make data-driven decisions and optimize your cloud spending. It’s Time to Upgrade from FinOrgs to a Flexible Cloud Center   FlexOrgs is a great start when your organization is still trying to define roles and permissions in the cloud, but if you’ve mastered hierarchy and are ready to move on to cloud cost optimization, cost anomaly detection, and user access control specifically for cost data, Anodot is for you.  Curious about Anodot and the services we offer? Talk to us to learn how much you can save with Anodot’s tools.