NetApp Cloud Insights Reviews

The primary use case for Cloud Insights is to provide visibility into our storage groups and other products we don't natively have access to. It gives a lot of behind-the-scenes knowledge about what was happening with the internal personalization group. We had access to their environment to back it up and assist them with the REST situation. 

NetApp Cloud Insights helps with login monitoring and troubleshooting. Previously, if we had performance concerns or needed to interface with other groups and their products, a task that should require only one or two people turned into a six-person job.

Cloud Insights allowed us to do some diagnostics and poke around before we took it to the other groups. We can say, "Here's where we see our bottlenecks are and what the potential impact will be. The solution enabled us to have a better response and be more intelligent about the decisions we're trying to make.

You can locate the full stack of your compute. We use private channel switching, so we can look at the intermediate stack and say which UCS blades are connected through what ports. We can see the links between devices without having to go to a separate panel for Cisco, VMware, etc. We can look at everything through a single pane of glass. 

It takes around 15 minutes to get everything inventoried once we get the on-premises data collector configured and running. We had to ensure it had all the credentials we needed to import them. We let it collect and come back, then it's all there. It did an excellent job of integrating quickly. It was honestly impressive.

Cloud Insights is excellent for pinpointing problem areas like issues with switches and back-to-back overruns on ports tied to our UCS fabric and interconnected storage. It was challenging to determine what was a problem, and no one could give us a solid answer, including Cisco, our architects, or Oracle.  If you do not see a problem, then it isn't a problem. However, just because something isn't a problem today that doesn't mean it won't be a problem tomorrow. We're still working through architecting our own solution to get rid of that, but Cloud Insights did help pinpoint that within an hour of us being in it, reporting, and poking around.

We're using it for monitoring and managing all of the NetApp storage in our environment, both in the cloud and on-prem. We are expanding it to use it with our virtualized environment and with our in-house storage environments.

It's allowed us to tag storage with applications and business units, so that when we have a requirement to migrate data for an application, we can quickly identify all of the storage that the application utilizes.

The solution also provides a single tool for cloud-based architecture, such as microservices and containers, as well as on-premise infrastructure. We're not fully utilizing that part of it yet, but we're in the process of starting down that road. It's provided us with the ability to better manage the storage and to report on it to management. We're able to show them, via dashboards and reports, how the storage is being utilized and what the return on investment is.

And when it comes to the solution's ability to quickly inventory our resources, figure out interdependencies across them, and assemble a topology of our environment, it's very powerful. Because it's SaaS, a lot of the upfront work is being done for us. We're spending less time managing the application and more time getting the data we need out of it.

NetApp Cloud Insights advanced analytics for pinpointing problem areas are outstanding. When we have a performance issue for a specific piece of storage, a volume, or an application we can graphically show the business units, the application owners, how the storage is performing relative to the performance that they're seeing on their clients or on their servers. It helps us to pinpoint where issues may be, whether they are with storage, the network, on the clients, or with the application itself.

The advanced analytics have also enabled us to look at trending and detect

• where issues are
• where we would have to do load balancing to keep performance from being degraded
• where we are running out of space in a given data center or storage node.

The advanced analytics help to reduce the time it takes to find performance issues as well because we run reports that look at trending. We can see where performance issues have not yet occurred, but that if we keep going in the direction we're going, we will have performance issues. That way we can proactively take action to ensure that we don't have any problems. We mitigate them before they happen. It's hard to quantify how much time it saves us, because it's very easy to see the problems before they occur, as opposed to dealing with them once they have occurred. It saves the businesses from having issues and keeps the entire environment running more smoothly.

In addition, the solution helped us to right-size workloads. It has shown us where we have issues, where storage growth has exceeded what is manageable. We've then worked with the business units and the application owners to break the data up into more manageable sizes, so that not only do they continue to get the performance that they need, but we're able to manage the storage without being backed into any corners that we can't get out of. Keeping the data broken into smaller pieces allows us to move it around to ensure that they get the performance they need. We're also able to ensure that the applications that require the highest level of performance get it. And those that don't have those high requirements can be put on lower power, with throughput storage that meets their needs, but without consuming horsepower on the fastest storage where they don't need it. Overall, it provides us with better utilization of the infrastructure.

The right-sizing has also reduced costs because we can more intuitively allocate resources and spend money on upgrades only where they're needed. Instead of just throwing more hardware at an environment, we can do it very selectively, based on the needs of the environment, needs that we are able to analyze through the reports that Cloud Insights provides to us. If I had to make an educated guess, it has reduced our costs by 20 to 25 percent.

Our primary use case is for holistic infrastructure monitoring, monitoring the stack from VMware down through SAN Fabrics and into the storage.

We've been OCI customers for many years before going to Cloud Insights. We didn't specifically implement Cloud Insights to address anything in particular. It quickly identifies if there's an actual problem in the infrastructure. 

Oftentimes, application folks claim performance issues, and Cloud Insights makes it easy to confirm or refute that.

It's a significant time saver. Having all the metrics in one place prevents the need to manually collect data, saving days or weeks of time.

NetApp Cloud Insight's ability to quickly figure out independencies across the assembled topology of our environment is its secret sauce. As long as I plug in the individual pieces of the infrastructure stack, it's able to figure out the rest and determine the relationships between VMs, Hypervisor servers, fiber channel ports, and what the SAN fabrics are doing, even down into the storage. 

I can sit there and click through all the way from a VM down to individual disks on the SAN and look at performance. I don't have to train it about what the relationships are; it figures it out.

Insight has helped to right-size workloads because it's really easy to go in and start looking for excesses. Just the other day, I found a virtual machine that had eight processors hanging off of it that was averaging 0.025% CPU load over the past 30 days. It was very easy to go in and get that kind of data. It's great at that.

We use it primarily to look at both performance and security around our NetApp Filers. I know it can expand to other entities within the NetApp, but we really focus on looking at our Filers and using Cloud Secure to see potential ransomware attacks, unauthorized changes to files, and deletions.

It's a SaaS solution hosted by NetApp.

Before we started using Cloud Insights, there wasn't really a good solution if something bypassed our firewalls and was sitting in dormant mode. In that situation, it was difficult for us to find it before it was too late. This solution gives us an opportunity to proactively see abnormal behavior before it hits a Zero-day attack.

We used to have a weekly file audit which was scripted, so there wasn't a whole bunch of time lost using that. But the difference is around the gap between when the file audit would last run versus this as a more real-time solution. If we had to collect the data the way this service is doing so, we couldn't really put a value on that because it is a real-time solution.

It also provides a single tool for cloud-based architectures, such as microservices and containers, as well as on-premises infrastructure. We've looked at pointing the data collectors at various entities, whether it's an HCI solution or a NetApp Filer or even some of our cloud instances. The flexibility of being able to look at various resources, whether they're cloud or something that is on-premise, is a huge benefit. Having all those data collectors in one location and being able to compare that information is invaluable.

The solution’s ability to quickly inventory our resources, figure out interdependencies across them, and assemble a topology of our environment—the performance and metrics and dashboards for doing that—is amazing. We're able to see and compare things like latency, and overlay latency between what may seem like two completely separate systems. If they're running, you can do comparisons on them, so when a particular application is running and it's causing influxes on both sides, it helps you dig into queries and application performance overall. The relational portion of this solution is beneficial.

It provides us with advanced analytics around being able to overlay data and compare various storage entities, their latencies, and overall performance, to gauge whether an application is performing well. It helps us see if it's something with policies or an actual, physical limitation of the solution we're using. Being able to look at overall IOPS and then drill down is super-beneficial. And the advanced analytics have definitely helped us with tuning SQL and looking at how we have our SQL LUNs or volumes laid out; whether we want to separate them by log and data, or other options. It helps with load balancing and overall performance of those high-storage, intensive applications.

In addition, the advanced analytics have helped to reduce the time it takes to find performance issues. They've helped with identifying applications that are causing latency and that may be affecting other applications. The analytics help with root cause analysis. One example is looking at nodes that are in high demand and being able to say, "Okay, this node is showing to be in higher demand than another node," and knowing we may need to move some of the load over so that, performance-wise, we have a better plane and everything correlates better. From a troubleshooting perspective, NetApp Cloud Insights saves at least 10 hours of my storage admin's time per week.

It has also helped to right-size workloads. From a helpdesk perspective, we've seen ticket volume go down by at least 10 percent, and that was happening right after a data center move where, obviously, there was a spike. Directly after starting to use Cloud Insights and the associated Active IQ to monitor the storage, it helped bring down the time to identify storage nodes that were heavily affected or needed to have some adjustments made. The right-sizing has only reduced soft costs. The cost perspective of storage is a long-term thing where you say, "Okay, I've been able to move stuff over and have deduplication rates increase." But that takes a while.

We primarily use Cloud Insights to provide monitoring and dashboarding to our customers. 

All our production clusters are in Cloud Insight. It provides a single pane of glass, giving us visibility into the environment, which allows us to understand if any issues are going on across any of our clusters.

The main issue we were looking to address was the lack of visibility across all the clusters in one single view. We're using Cloud Insight's Unified Manager. It has improved our ability to support and see the immediate status of the entire environment. If we have a critical incident, we can quickly see these issues and loop in monitoring teams and other teams. For example, if our app team thinks there are issues in the environment, we can quickly see if anything related to storage is part of the problem.

It improved our organization by unifying all the various support teams. We all have the same view of what's happening in the environment. The dev team knows what storage is used or not, and we can quickly move on to other activities. Cloud Insights provides a single tool for containers and other cloud-based architectures, but we're not using some of those things, such as Kubernetes. We're primarily leveraging the monitoring and reporting.

The solution does a great job of inventorying our resources. It allows us to put the tags on the devices. The process is fast. It also gives you the dependencies. I can dig down into all the related components. Cloud Insight's advanced analytics feature does a good job of highlighting the areas where there might be issues in the future.

The main benefit of NetApp Cloud Insights is that it's agentless. It just collects information from the SNMP protocol.

We had NetApp ONTAP installed and we paired with VMware. The biggest challenge for any company is to find the bottleneck on the Edge of the technologies, like between VMware and NetApp. Both products have great reporting and monitoring tools, but whenever it comes to finding issues on the Edge between those products, you can hardly identify whether it's a storage issue or whether it's a virtualization issue. NetApp Cloud Insights greatly blends the performance data, approximates, links together the performance usage from the VMware and NetApp perspectives, and provides you a single pane of glass in terms of the reporting and monitoring through the virtual machine to the hardware storage.

You can find any major bottlenecks or any issue points you need to work on. In any IT infrastructure, whenever you improve, like if you buy faster storage, then you move bottlenecks from storage to the network or to the servers. The biggest challenge is to find where that bottleneck is to resolve the issue. I personally found NetApp Cloud Insights very useful in this sense because we were a heavily virtualized environment.

We were a heavily virtualized environment with the NFS Protocol, as our storage main Storage Protocol, we were able to easily nail, locate, and resolve some performance issues using Cloud Insights, which would have been very hard to identify. 

The biggest challenge though is the licensing model for Cloud Insights. For example, for our environment, the price of purchasing was close to the price of the storage itself, which is why we didn't actually pursue using Cloud Insights further. 

Cloud Insights has helped us to optimize Cloud spend by removing inefficiencies and identifying abandoned resources in VMware. There were a bunch of older virtual machines that were powered off and they were just left there, forgotten to be decommissioned. That was costing us premium storage space.

Our storage team uses the solution to monitor security vulnerabilities and forecast capacity. 

The visibility and assistance with security vulnerabilities are valuable. For example, last year we had an issue with log forgeries but it was easy to fix because the dashboard highlighted the issue and provided solutions.  

It is for long-term tracking of performance information. I am also looking at the interaction between NetApp systems and non-NetApp systems.

It's only really being used for the storage, and to a limited extent, our VMware.

It is maybe being used once or twice a day at most. We're not using it actively. We are just using it in kind of a testing phase.

It is good for giving an overview of the systems and for tracking long-term trends. It is handy for root cause analysis, e.g. it can eliminate whether storage is the cause of an issue.

The solution’s ability to quickly inventory our resources, figure out interdependencies across them, and assemble a topology of our environment is good. However, I am making limited use of this.