Hyperglance Reviews

Hyperglance provides us a great and visible intuitive agentless, self-hosted dashboard which also provides us real-time visibility into the cloud resources we have, making it very easy for our users whether they are technical or non-technical. Hyperglance also provides us interactive diagrams and filterable inventory which allows our teams to quickly search and analyze. The teams can export the cloud data, reducing the complexity of managing multi-cloud environments.

Our main use case is to manage the resources across AWS, GCP, and Kubernetes. We manage and visualize the boards using Hyperglance and optimize the cost of the cloud by reducing waste through using the lean model.

Hyperglance features help in codeless automation, which means we can fix common issues and optimize resources without doing any coding.

Hyperglance has positively impacted our organization by helping us with agentless and self-hosted deployments, which has saved 38% time for deployments that we used to do manually. The automated process has saved us time and money as we cut resources. In the metrics we have tracked, we have saved 22% in costs.

The time and cost savings from Hyperglance have allowed our team to focus on other projects and improved our workflow. Hyperglance has helped us save on cost, improve efficiency, and reduce manual work while enabling real-time compliance checks with very good features. We have saved a lot of time and resources by reducing the manual work which the new team needs to do. Now the team is occupied in other work and they are more productive, providing us more user stories in the organization.

The learning curve can be a challenge for new users, which is something that can be improved. Apart from that, everything else is really good.

In my organization, we have been using Hyperglance for the last three and a half years.

Hyperglance is definitely stable, and we have not faced any kind of downtime, challenges, or bugs.

The scalability of Hyperglance is definitely good, as it allows you to add resources—2,000, 3,000, 5,000, 10,000—depending on the licensing and billing model we use. It is a scalable product that can handle as many users as you want.

The customer support experience I had was very good; I had an interaction with the customer support last month, and the agent was professional and prompt, solving our problem within 25 minutes.

Negative

Before Hyperglance, we did not use any other solution; this is the first time we are using this service, and prior to that, there was nothing we used.

My experience with the configuration process was very good; our technical team was able to configure it quickly within three days, and there were no reported outages or problems that we faced with that.

I have seen a return on investment with Hyperglance, as time was saved by 79% and money was saved by 22%.

The metering and billing experience with Hyperglance is really good because it provides us with a pay-as-you-go model. The number of resources we needed depends upon that which is a great thing, providing us with a great ROI on the amount invested. The initial setup was really good with no extra or hidden costs involved.

My experience with Hyperglance's licensing and setup cost was really good; they were able to renew the licenses very well. As soon as we paid, it was renewed without any further delay. Since it is a pay-as-you-go model, we can choose how much we want at a time, which is a great aspect.

We did evaluate other options before choosing Hyperglance, including Turbonomic by IBM, Flexera Cloud Management Service, AWS Cost Explorer and Budgets, and Azure Cost Management. Out of those, we found Hyperglance to be exceptionally good, which is why we chose it.

The security features and automated recommendations in Hyperglance have helped us significantly. Six months back, there was a security breach happening on the server. Hyperglance alerted us in real time through the inbuilt monitoring alert on the rule which we set. We were able to implement advanced security and prevented the attack, saving us a lot of time and money.

Hyperglance integrates well with other AWS services I use. The integration is positive, as it can easily integrate with other services across all cloud providers. It can help in exporting reports to external tools such as Excel and ensures that the data is safe, handling multiple cloud environments, and it can integrate with multiple tools as well. The integration is very good, and I am happy with that.

My advice for anyone looking into using Hyperglance is that if you are looking for a dedicated product depending on cloud complexity and automation requirements that can support multi-cloud environments, you should definitely go for it, as the billing experience and metering experience are really good. Hyperglance charges you for what you use, not what you do not use, which is the main thing to consider when choosing Hyperglance. I would give a rating of 10 to the customer service.

Hyperglance: Up to 5000 Resources [Pay as you go] is used in our organization to visualize, manage, and optimize multi-cloud infrastructures. It is very efficient and effective while we do that. Cloud cost optimization is what we use it for in the primary way, along with resource visualizations, and security and compliance monitoring. Ensuring that the cloud infrastructures meet the industry security and compliance standards is something very useful that Hyperglance: Up to 5000 Resources [Pay as you go] provides.

Hyperglance: Up to 5000 Resources [Pay as you go] helps businesses monitor their cloud cost in real time by visualizing where money is being spent and identifying opportunities to reduce waste. It also provides actionable recommendations to optimize cloud expenses. This is especially valuable in environments with complex and large-scale deployments, allowing us to track and manage the cloud spending across multiple cloud providers such as AWS, Azure, or GCP.

Managing resources across multiple cloud platforms in a single interface is a significant advantage with Hyperglance: Up to 5000 Resources [Pay as you go]. In our companies, we are using multiple cloud providers to avoid vendor lock-in, and this allows us to manage and optimize resources across all these platforms in one place.

The cost optimization and management features of Hyperglance: Up to 5000 Resources [Pay as you go] are quite beneficial. Other than that, resource visualization and management are valuable, and the security features including security monitoring and compliance are also something good. Automated evaluations for optimizations and multi-cloud resource management are some of the main features which have been helpful.

Hyperglance: Up to 5000 Resources [Pay as you go] has positively impacted our organization through cost reduction for data workloads. In our company, we are running large-scale data tasks, such as machine learning models training on AWS EC2 instances, and we noticed escalating costs over time due to high-performance instances being used for non-intensive tasks. Hyperglance: Up to 5000 Resources [Pay as you go] provided a visual representation of our cloud resources and usage, showing which EC2 instances were underutilized or overprovisioned. It recommended resizing the instances based on actual usage, which led to a reduction of 30% to 35% in cloud spending. The company was able to optimize instance types for data preprocessing and training, significantly lowering the compute cost without sacrificing performance. This helped our projects to keep within budget.

Hyperglance: Up to 5000 Resources [Pay as you go] needs to make the user experience more effective, especially for data science and tech teams. There are a few key areas for improvement. The current limitations in Hyperglance: Up to 5000 Resources [Pay as you go] are heavily focused on cloud environments and may not offer the same visibility in hybrid infrastructure. Better hybrid integrations can be added, for example, with data centers, local storage, and private servers. More granular resource-level metrics for data science applications would excel the visualization for cloud resources. The cost forecasting and budgeting tools are available, but the predictive analytics can be improved.

In my current field, I have been working for two and a half years. Earlier I was an intern, and I have converted to full-time in the past nine months.

Hyperglance: Up to 5000 Resources [Pay as you go] scales well for our team. The resource scale pricing available through AWS Marketplace seems good. The UI performance, resource count pricing, and the initial setup complexities were very good. As our project size grows, Hyperglance: Up to 5000 Resources [Pay as you go] helps us to keep them under control from a financial perspective. We will need to monitor how quickly our infrastructure is growing and then ensure our implementation is also resourced, planned, and handled with clarity.

Customer support for Hyperglance: Up to 5000 Resources [Pay as you go] is proactive and helps us to achieve everything. Even with simple questions, they help us to work through things, and the support has been very proactive. Customer support is very active and good, and I would rate it a nine out of ten. It is very supportive, and the team has helped us from setup through any issues we face.

Positive

We switched from a different company to Hyperglance: Up to 5000 Resources [Pay as you go] for better resource visibility and optimization. The previous solution had streamlined cloud cost management, but Hyperglance: Up to 5000 Resources [Pay as you go] offered more simplified compliance and security monitoring. We made the switch for cost savings, efficiency gains, and real-time visibility.

The subscription fee for Hyperglance: Up to 5000 Resources [Pay as you go] was around $180 to $200. We have been using the enterprise plans for our organization. We have around 5,000 per month, and we can spend more because the scope of usage requires different support levels. With GCP, we used it on different platforms, and the cost was around 3,000, depending on the size of the team we are working with and the complexity we are building.

The other options we considered were Cloud by VMware, AWS Cost Explorer, Azure Cost Management and Billing, and Spot.io, which is Spot by NetApp. However, we started with Hyperglance: Up to 5000 Resources [Pay as you go].

Wherever cloud is being used and teams want to make efficient compliance in that particular organization, Hyperglance: Up to 5000 Resources [Pay as you go] is effective for the entire team because it has everything from real-time instances to clusters and storage, and everything would be covered. I would rate this product a nine out of ten.

My main use case for Hyperglance is visualizing cold cloud infrastructure and monitoring resources across the environment to identify security risks or configuration issues. It helps make complex cloud environments easier to understand and manage.

A specific example of how I use Hyperglance for monitoring risks or managing my cloud environment is using it to visualize our cloud infrastructure and identify security misconfigurations such as storage resources exposed to the public internet. The visual maps help me understand how resources are connected, spot potential risks, and prioritize fixes. It also makes it easier to monitor infrastructure changes and keep cloud environments secure and organized.

I also find Hyperglance useful for getting a clear overview of cloud resources, understanding dependencies, and identifying unused or misconfigured resources. It helps teams attribute issues faster, improve visibility across the cloud environment, and manage infrastructure more efficiently.

Hyperglance has positively impacted my organization by improving cloud visibility, making it easier to understand infrastructure connections, investigate configuration issues, and identify potential security risks. It reduces the time spent manually checking resources and helps teams spot ideal infrastructure and potential cost savings. Although I haven't tracked exact savings or time reduction, the biggest benefit is having a clear overview of the cloud environment and being able to prioritize issues more efficiently.

Hyperglance has impacted my team's workflow by making collaboration easier through a shared visual view of cloud infrastructure. Instead of spending time checking resources separately, team members can understand dependencies, identify potential configuration issues, and focus on the same priorities. It speeds up troubleshooting by making it easier to trace problems across connected resources. Although I haven't measured a specific reduction in incidents, the improved visibility helps the team take a more proactive approach to cloud security and maintenance.

The best features that Hyperglance offers are its visual cloud infrastructure mapping, real-time resource visibility, security risk identification, and dependency tracking. I especially value how it makes complex cloud environments easier to understand, helps identify misconfiguration, and allows teams to troubleshoot issues faster. It also helps with cost optimization by highlighting underused resources and improving overall cloud management.

Hyperglance's visual mapping specifically helps my team by making it easier to understand how cloud resources are connected and quickly identify potential security risks or misconfigurations. For example, if a server is publicly exposed or has an unexpected connection, the visual view helps the team investigate the issues faster. Its cost visibility is also useful for spotting underutilized resources and opportunities to reduce unnecessary cloud spending.

I would like to see more advanced cost-saving recommendations, clearer alerts for critical security risks, and automated suggestions for fixing configuration issues. A feature that estimates potential cost savings before making changes would also be helpful. Overall, Hyperglance makes cloud infrastructure easier to visualize, monitor, and manage efficiently.

Hyperglance can be improved by adding more automated security remediations, smarter alerts for critical risks, and clear recommendations for reducing cloud costs. A dashboard showing cost trends, potential savings, and security issues in one place would be helpful. I would also appreciate better integration with popular cloud management ticketing tools, customizable reports, and easier tracking of improvements over time.

One feature that I would really appreciate is an AI-powered recommendation system that not only identifies cloud security risks and cost inefficiencies but also suggests step-by-step fixes. It would also be helpful to have customizable alerts based on risk severity, better reporting for management, and automatic tracking of resolved issues. These improvements could help the team spend less time on manual checks and more time on important cloud infrastructure tasks.

I have been using Hyperglance for one year.

Hyperglance is stable, and I have had a good experience with it.

The scalability of Hyperglance for managing growing cloud environments is evident through its visual mapping, which helps teams monitor resources and understand dependencies across multiple cloud accounts and environments from a centralized view. I would like to see continued improvements in dashboard performance, large-scale resource discovery, and filtering capabilities to make managing very large and complex environments even easier.

The customer support was fantastic. I would rate the customer support 10 out of 10.

We did not use any solutions before Hyperglance.

We have not measured Hyperglance's ROI in terms of money saved or staffing reduction. However, the main benefit appears to be the time saved when investigating cloud infrastructure issues, better visibility into security risks, and easier identification of underused resources. It has helped the team prioritize problems and manage the cloud environment more efficiently. Tracking investigation time and avoiding incidents and cloud spending before and after implementation would help with measuring quality and actual return on investment.

My experience with pricing, setup cost, and licensing was good, and the setup was easy. Since I already have experience, it was easier for me to set up an account.

I would recommend Hyperglance 9 out of 10.

I give Hyperglance 9 out of 10 because its visual cloud mapping, infrastructure visibility, and security monitoring make managing complex cloud environments much easier. It has helped me understand resource relationships and identify potential issues quickly. I did not give it a perfect 10 because I would appreciate more advanced AI-powered recommendations, smart alerts, and clear cost-saving recommendations with measurable savings. These improvements would make it an even more complete cloud management solution.

Regarding Hyperglance's AI capabilities, I think it could be valuable for identifying cloud security risks and improving infrastructure management. However, strong governance and security controls are essential, including role-based access, data privacy, audit logs, and clear expectations for AI-generated recommendations. I would also appreciate human approval before any high-impact changes are applied automatically. Overall, transparency, compliance, and control over automation would make me more confident in using its AI features in a production environment.

Regarding Hyperglance's AI capabilities, I think it can be useful for identifying potential cloud risks, analyzing infrastructure dependencies, and highlighting configuration issues. However, accuracy and reliability are critical, especially when dealing with security alerts and cost recommendations. I would appreciate clear explanations behind AI-generated findings, fewer false positives, and recommendations validated against real-time cloud data. Human verification for critical actions would also be helpful to build trust and ensure reliable results in a production environment.

Hyperglance is primarily deployed in my organization to visualize and manage infrastructure across public environments with support for multi-cloud and hybrid cloud visibility. In our setup, I would describe the deployment as public cloud, focusing on monitoring cloud resources, infrastructure dependencies, security risks, and costs from a centralized dashboard.

We use AWS as our cloud provider for public cloud deployment.

I would recommend Hyperglance to teams that need better visibility into complex cloud environments, especially those managing multiple accounts or cloud platforms.

I use Hyperglance my organization for real-time cloud visualization and managing FinOps applications.

In real-time cloud visualization, we use the interactive diagrams for full infrastructure including managing VMs, network, and all dependencies. It helps us understand which applications or VMs are connected where, and it eliminates the need for manual documentation.

Hyperglance also helps us use custom dashboards and reports as it provides multi-cloud dashboards and billing support for managing different cloud environments in a single place.

The best features are real-time cloud visualization, advanced FinOps management, automation, security, and custom dashboards and reports.

For automation, Hyperglance provides a codeless rules engine that can auto-fix issues through info tagging and stopping idle instances. It also integrates with Slack and Jira.

At my organization, Hyperglance has positively impacted us by saving costs as it identified unused resources that we could delete, which saved us money. Better visibility is provided as it offers a single plane for multiple cloud environments and provides real-time dashboards.

It has saved considerable time for managing multiple cloud environments, with cloud costs reduced by 30%.

Hyperglance can be improved by providing a less steep learning curve. The UI is powerful, but it is complex for beginners. I faced issues initially, and the initial setup takes time.

The initial setup requires significant time, and you need a basic understanding of Hyperglance from the start.

I have been using Hyperglance for the past two years.

Hyperglance is stable in my experience.

Scalability is good as Hyperglance supports multiple cloud accounts, clusters, and subscriptions. Workload can be distributed across the architecture, and it can handle any number of resources at enterprise scale. It can be used by large enterprises and government organizations, as we have multiple clients from the government and enterprise sectors.

Customer support is excellent as they are always available to help and provide quality support.

Initially, we were using solutions like VMware and others, but we found Hyperglance to be better, with the main purpose being cost savings.

When I joined my organization, Hyperglance was already in use from the start, so I do not have much information about the transition.

The initial setup takes considerable time, and you need a basic understanding of Hyperglance from the start.

We required fewer employees, and our time was saved as it helps in managing multi-cloud environments. Cloud costs have been reduced by 20 to 25%.

I do not have information about the licensing, but the setup cost was somewhat less than other comparable tools.

I purchased Hyperglance through the AWS Marketplace.

If others are considering using Hyperglance, they can easily switch as it will reduce their costs and provide cost benefits. They will also gain additional benefits as it will help them manage their multiple resources in a single plane. I rate this product 9 out of 10.

Our main use case for Hyperglance is cloud analysis, which helps us visualize the infrastructure and serves as a cost-effective cloud management system for our organization.

We initially faced an issue with AWS where costs were very high and tracking dependencies was difficult. We switched to Hyperglance to have a single view of the cloud, which addresses costs, architecture, and dependencies together. This allows us to consolidate our cloud infrastructure from AWS and Kubernetes into one unified location.

Hyperglance provides visibility that creates a unified view of the entire cloud system, allowing us to debug much faster than we were able to initially. With this visibility, new engineers being onboarded find it easier to understand the infrastructure. Cost optimization is also a significant benefit we gain from Hyperglance, as we are able to see unused resources, which aids in budgeting.

Beyond easier onboarding and faster debugging, Hyperglance automatically identifies idle servers, reducing costs by shutting them down and creating Jira tickets automatically.

The unified view offered by Hyperglance is a huge benefit that we have been able to see. These features stand out for us because it becomes easier to make decisions when all of the information is in a single, simple, unified view. This simplicity makes it easier to debug and for new team members to understand the infrastructure, as they can see budget costs and consider options regarding budgeting, ultimately increasing capacity and speeding up decision-making.

Hyperglance is greatly scalable because, as soon as we scale it to a greater architecture or a larger number of servers, it quickly identifies unused resources, making debugging faster and enhancing budget tracking. We also receive automatic anomaly alerts, so I would say it performs very well in terms of scalability.

Hyperglance has a multi-cloud visualization system and automates many things; however, a downside is that the user interface feels somewhat complex when you start. When we first began using Hyperglance, the user interface felt complex initially, but once you become familiar with it, it becomes easier to use. It is powerful, but it is not very easy for a beginner to adapt to.

The user interface of Hyperglance might feel complex in the initial stages, and I would also say that it can be somewhat expensive for small teams or early-stage startups. Hyperglance could be costly for someone with simple infrastructure. Therefore, I think the cost aspect and the user interface could be improved.

Hyperglance is a powerful tool when it comes to cloud operations, functioning as a control system. However, for an early-stage startup that does not have much reliance or is not heavily dependent on cloud operations, it might not be a good option for them. If the cost could be reduced and onboarding made a little easier, early-stage startups would benefit greatly from Hyperglance.

I have been using Hyperglance for nine months.

Hyperglance is stable in its performance.

I have not faced any issues that required customer support, so I cannot comment on that. However, I think the product is really good, and we have not had many issues that would necessitate support.

Initially, we were using AWS before switching to Hyperglance.

We have seen a return on investment from Hyperglance, as we are now able to identify waste very efficiently. We have achieved approximately twenty percent cost reduction due to the shutdown of idle servers, and we have also seen approximately eight to ten percent improvement in time, providing significant benefits from Hyperglance.

The cost was pretty steep, and we were not initially very certain about taking Hyperglance due to its price. However, it is a very powerful tool, and I have not been the one handling the pricing and licensing aspects.

I evaluated other options before choosing Hyperglance, but I cannot elaborate on this as I am not familiar with those specific options.

My advice for others looking into using Hyperglance is to first assess their team's needs. If there is a small team that does not rely heavily on cloud services and does not need multi-cloud complexity, they might be fine without it. However, if they have a heavy reliance on cloud services and need visibility, automated shutdown of idle servers, and budget tracking, I would definitely suggest Hyperglance. Although it might be complex initially, once you become familiar with it, it is an excellent tool.

For Fintech teams or those who rely heavily on cloud services, Hyperglance might be a great tool, even though the user interface might feel complex at first. I would rate this review a seven overall.

Cloud Inventory & Visualization: I can visualize my cloud environment, such as AWS, Azure, or GCP, with up to 5000 resources mapped in an easy-to-understand topology. Cost & Resource Optimization: I am able to identify unused or under-utilized cloud resources to reduce waste and lower costs. Multi-Cloud Management: I bring all of my cloud service providers’ resources under one view, instead of using each provider’s separate consoles.

Common ways organizations say it improves their operations include offering clearer visibility across cloud assets, which helps reduce manual audits and the risk of misconfigurations. It strengthens security and compliance posture, which is especially valuable for regulated industries. Cost optimization with up to 5000 resources can meaningfully impact medium environments, and troubleshooting and collaboration are faster.

The cloud topology visualization is particularly valuable because this visual map dramatically reduces time spent tracking interdependent services. Security posture and risk insights help reduce security risk and ease audit preparation. Cost and resource optimization are useful for teams looking to lower monthly cloud bills without guesswork. Alerts and continuous monitoring actively keep teams informed instead of relying on regular manual checks.

There are areas that users often want improved. Deeper automation and remediation reduce manual effort and accelerate the resolution of common problems. More contextual and actionable topology maps improve clarity and make maps genuinely actionable for teams with mixed workloads. Customizable dashboards and reporting are needed because teams have different priorities, such as security versus cost versus uptime, and want dashboards tailored to them.

I have been using the solution for 2 years.

I used native cloud tools, like AWS Config and Azure Security Center, before. There was limited cross-cloud visibility because many teams start with native tools per cloud provider but struggle to get a unified multi-cloud view. Switching provides centralized visibility across AWS, Azure, and GCP. Some platforms provided lists and reports but not intuitive relationship maps. Teams switch for better visualization of how resources connect.

To estimate the setup cost, I consider my current billable resource count, including instances, databases, and network resources, plus expected growth over the next 12 months. I choose a tier that comfortably covers that without frequent upgrades. Often the ROI from visibility, security posture, and cost insight outweighs raw licensing costs. TCO gives a better picture than monthly fees alone.

I evaluated native cloud provider tools because they are free or low-cost and built into each cloud provider. However, users find limitations because they are siloed per provider and do not offer strong cross-cloud visualization or consolidated insights. I also evaluated Cloud Management Platforms (CMPs) for full multi-cloud governance, cost, and security features. Users consider feature breadth versus complexity and pricing, as some are more expensive or harder to set up. Security-focused tools were evaluated for their focus on security posture management. Often, they are stronger in security depth but weaker in visualization and cost insights.

It is important to clarify whether your priority is security, cost optimization, architecture visibility, or operational efficiency. Hyperglance provides all these, but the configuration and use depend on your goals. I advise being realistic about resource growth and investing in good onboarding. A thoughtful setup, including account connections, tagging strategy, and alerts configuration, pays off quickly because early misconfigurations can delay value.

I use Hyperglance for multi-account AWS infrastructure mapping, network dependency visualization, and compliance hygiene. I use it to maintain live topology diagrams across client member accounts and catch orphaned resources such as unattached EBS volumes and idle Elastic IPs.

Before Hyperglance, my team at Accenture India spent hours every sprint manually redrawing architecture diagrams in Visio or Lucidchart for client reviews. Those diagrams were outdated the moment our CI/CD pipelines deployed changes. Hyperglance runs in our shared-services VPC and maps everything automatically across 40+ AWS member accounts using IAM cross-account roles. It completely removed the manual diagramming chore and helped us spot misconfigured route tables and security groups before client audits.

The self-hosted deployment is the biggest advantage for us. Because the appliance runs entirely on an EC2 instance inside our VPC, no configuration data or credentials leave our boundary, which made InfoSec sign-off easy with strict banking clients. The graph visualization is also great. Clicking an EC2 instance to immediately trace its ENIs, security groups, route tables, and connected VPC endpoints makes network troubleshooting much faster than clicking around the AWS console. Linking AWS Cost and Usage Reports (CUR) directly to visual nodes is also very handy for tagging audits.

The web canvas gets sluggish when rendering large accounts with 5,000+ resources simultaneously unless I apply account or VPC filters first. Also, the embedded PostgreSQL database on the appliance can fill up disk space quickly in environments with heavy autoscaling, so I had to manually expand our EBS volume. Having built-in disk retention alerts in the UI and a more intuitive visual builder for custom rules would be great improvements.

I have used the solution for 1-2 years.

I used manual tools like Lucidchart and Visio alongside custom Python/Boto3 scripts and AWS Config. I switched because manual diagrams couldn't keep pace with fast cloud deployments, and maintaining custom scripts across dozens of accounts became an unnecessary overhead.

Make sure to factor in the underlying EC2 compute and EBS storage costs alongside the Marketplace license. For multi-account workloads, don’t run it on the smallest instance. Give it at least an m5.xlarge and 100 GB gp3 volume so the database runs smoothly. The license cost usually pays for itself quickly once you use the waste-detection rules to delete idle IPs and abandoned snapshots.

I evaluated Lucidscale and a few SaaS-based CSPM platforms. I chose Hyperglance because our enterprise client policies strictly prohibited external third-party SaaS engines from scanning their environments. Hyperglance’s self-hosted, agentless model was the cleanest fit.

Deploy your cross-account IAM roles using CloudFormation StackSets across your AWS Organization from day one instead of adding accounts manually. Also, keep the appliance in a private subnet behind an internal ALB or VPN since it holds a full map of your cloud architecture.

My main use case for Hyperglance includes cloud inventory and its mapping, security posture management, architecture documentation, troubleshooting complex environments, and conducting compliance and operational audits.

Recently, I used Hyperglance during a cloud cost review after noticing a spike in AWS. It was quick to visualize unused EC2 instances and attached EBS volumes or over-provisioned resources across multiple accounts. Instead of tracing dependencies in the AWS console, we used the infrastructure map to identify orphan resources and clean them up, which reduced monthly costs and improved visibility for the ops team. Another standout use case was troubleshooting a connectivity issue between application tiers in AWS, where Hyperglance's dependency mapping made it much easier to trace security groups, subnets, and resources.

One of the things we found especially useful with Hyperglance is how it helps bridge the gap between technical and non-technical teams. The visual infrastructure maps make it much easier to explain our architecture, auto-dependencies, and risk areas during reviews or planning sessions. While using Hyperglance, it has also been valuable for onboarding new team members because they can understand the environment much faster without digging through multiple cloud resources.

For others who are looking into Hyperglance, I suggest starting with a clear use case. It delivers the most value when you focus on specific problems such as cloud cost optimization, dependency mapping for troubleshooting, or improving governance and compliance visibility.

One of the features that stands out the most for me is cost optimization, along with agentless and self-hosted deployment. When talking about cost optimization, Hyperglance identifies idle resources, right-sizing opportunities, and also has automated security and compliance checks and frameworks such as CIS, NIST, PCI DSS, and AWS Well-Architected. Many enterprises appreciate that the agentless and self-hosted option allows them to run it inside their own environment rather than relying on a free managed SaaS product.

Hyperglance has mainly helped us improve visibility and understanding of our cloud infrastructure. It also helps to find unused or over-provisioned resources that are easy to miss otherwise. From an operational perspective, onboarding new engineers and explaining the environment to stakeholders has become much easier because the infrastructure is visualized clearly instead of being spread across disconnected tools.

Some dashboards and visualizations can become cluttered at scale, so I believe more flexible filtering and cleaner navigation would help.

I have been working in my current field for the last one and a half years.

We have seen measurable improvements in a few areas since adopting Hyperglance. The biggest impact has been on operational efficiency and cloud cost visibility. For example, during a recent infrastructure review, we identified several underutilized EC2 instances, unattached storage volumes, and outdated test resources that were overlooked across multiple AWS accounts. Cleaning those up reduced our monthly cloud spend by roughly ten to fifteen percent. On the operational side, troubleshooting time has improved noticeably because engineers can trace dependencies and visualize architecture much faster instead of manually piecing information together from native cloud consoles.

Hyperglance's AI capabilities appear fairly reliable when it comes to infrastructure dependency mapping and identifying optimization opportunities because it is working from live cloud and configuration and telemetry data rather than purely generative AI outputs. In our experience, the recommendations around unused resources, topology relationships, and governance issues have generally been accurate and actionable. I rate Hyperglance a nine out of ten.

My primary use case with Hyperglance is gaining end-to-end visibility of our cloud and OpenShift infrastructure, and it helps us automatically discover resources, visualize architecture, monitor compliance, and identify cost optimization opportunities from its single dashboard.

Beyond just visualization, the main value Hyperglance brings is having a single source of truth for the environment, which helps reduce operational overhead, improve cloud governance, support compliance requirements, and enable better cost control. Automated infrastructure visualization reduces the effort required for documentation and audits.

The best features of Hyperglance are its real-time cloud visualization, cost optimization capabilities, compliance monitoring, and automation, with the standout aspect being that it combines architecture visibility, FinOps, security, and governance into a single platform that significantly improves visibility, troubleshooting, compliance management, and cost control for large cloud or OpenShift environments.

What I appreciate most about Hyperglance is that its real-time cloud visualization and automation features help make my day-to-day work easier by preventing human error and saving significant time. For example, the automated infrastructure visualization eliminates the need to manually create and maintain architecture diagrams, which can quickly become outdated. Having an accurate, real-time view of dependencies helps the team avoid mistakes when making changes or troubleshooting issues.

Beyond the technical features themselves, the biggest benefit is efficiency, as Hyperglance automates tasks that would otherwise require manual documentation, inventory tracking, and compliance reviews, saving time, improving accuracy, reducing the likelihood of configuration mistakes, and allowing engineers to focus on higher-value work instead of infrastructure discovery and reporting.

The biggest positive impact of Hyperglance on my organization is operational efficiency because it centralizes infrastructure visibility, cost management, and compliance monitoring into a single platform, which reduces manual effort, improves the accuracy of infrastructure documentation, helps identify unused resources, and supports proactive governance, allowing teams to spend less time on administrative tasks and more time delivering business value.

The main challenge I see with Hyperglance is not functionality but usability; it provides a lot of valuable information, but new users may need time to learn how to navigate and interpret the data effectively. Improvements in dashboard customization, advanced analytics, and deeper integrations would make the platform even more powerful.

The main improvement I would suggest for Hyperglance is making onboarding easier through guided setup, interactive tutorials, and role-specific dashboards. Hyperglance already provides powerful visibility and governance capabilities, but simplifying the learning process would help teams adopt the platform faster and maximize its value sooner. Additionally, predictive insights and business-level reporting would further enhance the user experience.

My advice for others looking into using Hyperglance would be to clearly define your objectives before implementing it. Whether your primary goal is cloud visibility, cost optimization, security and compliance, or governance, having clear priorities will help you get the most value from the platform.

I have been using Hyperglance for the past two to three years. I use Hyperglance primarily for cloud management and FinOps platform management. Additionally, I use it for the unified multi-cloud view where it provides a single plane where I can manage my different types of Kubernetes clusters in a single interface.

The best features Hyperglance offers in my experience are real-time 3D visualization, FinOps and cost optimization, no-code automation, and unified cloud view.

I find myself relying on the unified multi-cloud view the most, as it helps us to manage and keep monitoring on our different types of Kubernetes and other clusters at a single platform.

Hyperglance has impacted my organization positively in many ways; we got a single view of our multiple cluster managements, and it also improved our security. It helped us with our self-hosted security as many software-as-a-service tools cannot. Hyperglance provided a self-hosted own cloud where we can manage our self PVC and virtual network, so that our data never leaves our environment.

From my perspective, Hyperglance can only improve its UI/UX design.

They can improve their dashboard as well, as their dashboard has a lot of customization limits, so they can improve it.

The reason I did not give it a 10 is that they also need some improvements like resource handling; they can effectively manage environments, and also for licensing purposes.

Hyperglance is stable.

Hyperglance's scalability is good, but some users report that it has a lag and slow loading time when visualizing a large resource count.

Customer support is very good.

I did not evaluate other options before choosing Hyperglance, as we have been using Hyperglance from the start.

Before choosing Hyperglance, I did not evaluate any other options.

If others are looking into using Hyperglance, my advice is that they can switch. I gave this review a rating of 9.