The solution is scalable. It’s great for enterprise-level organizations.

We have 30 to 35 engineers on the solution right now.

Since the tool runs on a SaaS model, it can be scaled horizontally and vertically. I rate the scalability a ten out of ten.

The solution is scalable, but it was challenging onboarding users to ScienceLogic even if we gave them an AD and put them in an AD group. The user would log in, fail, and their profile would lock. It would then create a nonfunctional profile, and we would have to go to that profile and assign them a read-only, administrator, or power user level. Then, we would have to give them access after they logged in or tried to log in and failed. It was an issue for several years and made it difficult to onboard new users. ScienceLogic should have a good access control model that does not rely on just locking the user out. We had about 30 users that actively used the solution, but about five to eight were administrative users.

The scalability of ScienceLogic could improve, it should be easier. The cloud versions could be easier but the on-premise version is not simple.

Administrators only use the solution directly whereas we have approximately 20,000 endpoints using it. Depending on the company's growth will decide if we will increase usage of the solution.

The scalability is good in that you can always add more users. There's no limit to the number of users. I'm not sure the exact amount of people that are using it right now as everyone has access to a lot of tools. IN my team, however, only three people use it currently. 

When we were doing this transition phase, three of us worked, but later we had a team of 12 because the project started working. 

We began receiving numerous requests for user creation, followed by your adding of devices, discovering devices, fixing issues with PowerShell, and fixing issues with other connectivity. 

We used to have infrastructure issues from time to time. For example, the database layer is ScienceLogic's main layer; everything fails if it fails. We had some Docker issues at times. Everything will come to a halt if Docker is not running. The application is stopped.

We had to create ScienceLogic support cases. Then we had to sit with them, figure out what was wrong, and troubleshoot. We had a lot of other things, a lot of other work that gradually began to pile up in our queue. 

Then there was a team that was solely responsible for reporting, every day we would pull out a report and see how many servers were collecting data and how many were failing to collect data. 

We had to troubleshoot why the ones that were failing to collect data were failing to do so. There were numerous BAU-related activities. 

When doing a project activity, you don't need many people at first, but when you start working at a BAU level, you definitely need a team of at least ten.

As a tool, it is quite effective, but there are a few issues here and there, that we have to look into. 

We also have this Azure environment, that we have to ensure is scalable, has high scalability, and high availability, and that you don't have an issue with all of those things. It all depends on how you intend to build your infrastructure. When it comes to scalability and high availability, I don't believe there will be any problems because we are using the cloud, which should be properly planned.

The tool has medium scalability. I rate the scalability a seven out of ten. We have more than 1000 users. I use the product every day. We might increase the usage if we get more add-ons.

Scalability is good, we can increase the number of users we want. 

The footprint and complexity of ScienceLogic can require significant memory, CPU, and disk space. This can lead to overloaded servers and components, resulting in a sluggish user interface.

A total of 400 users are using this solution.

I rate the solution’s scalability a six out of ten.

Adding resources is easy and accessible in ScienceLogic. You can customize and monitor and can have automated management. You can write automation scripts with the right level of access and send alerts and notifications. It is a built-in feature, but only some have access to it.

In my team, we have 25 ScienceLogic admins. In the AIOps team, we have another 50 users. Its scalability is a seven or eight out of ten.

We have not encountered any scalability issues yet. We have grown from monitoring 100 devices to upwards of 500. The system doesn't seem to be experiencing any problems.

I have no problem scaling ScienceLogic.

The product has outstanding scalability. We did not see many issues around that so far.

We’re a growing cloud services provider, and set out to build a framework that would provide the scalability we needed to support future growth. ScienceLogic provides scalability beyond our current needs.

Use the professional services proposed solution to support private MIBs, we are encountering what appears to be poling time outs, which creates false positives. We are still working through this issue.

We currently have 20,000+ systems in our primary ScienceLogic system and general performance is acceptable. We would like better scalability in the time-series performance data storage.

ScienceLogic continues to grow with us. There is a feedback loop between our companies which allows both of us to improve. They learn from issues we experience, and we believe they build that into new product improvements. They listen to customers and make meaningful updates based on their needs.

We have not had any scalability issues. However, we only have a few thousand elements. This is something I will continue to watch as it grows.

Yes, however our issues were due to not understanding the size of our environment and the group that originally sized the product was providing bad information. As we have increased the amount of devices and the range of those devices we have run in to scaling issues which will most likely cause us to stand up a brand new instance of ScienceLogic to meet our needs. This is not a solution we are excited about but it is a solution none the less

Scalability looks fine, but we didn't have to extend it so far. We haven't looked at our possibilities regarding scalability.

Shouldn't encounter any issues - when we are ready, or it is necessary, a global manager function will help us manage multiple deployments from a single interface.

No issues with scalability.

No issues with scalability. We have pushed our server beyond whats recommended and it is still chugging along fine.

Scalability is key. One of the biggest challenges that you have with monitoring systems is just simply dealing with what I call the signal-to-noise ratio. There is a tremendous amount of data coming in and the system needs to be able not only to scale to address the full install base that we need it to, but it also needs to be able to ingest all of that data and bubble it up to our monitoring teams in a way that is understandable and actionable so that we are really able, as I said, to separate the signal from the noise. Their platform really enables us to do that.

We have never faced any issues with scalability. 

We are using this tools for approximately 50 customers.

No issues in tools.

No.

Scalability is pretty easy. You have few different option of hardware (Dell) that you can use to expand your system by adding more collectors or expand your database.

The only scalability issues I've encountered have been due to bugs in my hardware. When I have followed heir published hardware recommendations and used reliable hardware I have seen no scalability issues.

There was a few issue involving the quantity of devices to be monitored, including the interfaces, versus the amount of collectors required. Larger quantities of interfaces was the biggest issue but just required recalculating how many devices per collectors were necessary.

As it relates to scalability : if you follow all the rules, take time to read the manuals, its infinitely scalable in my opinion. That said we haven't had any issues with scalability :)

We have found this solution to be quite scalable and at this price point it seems to be intended for enterprise level customers.

No.

Yes - scaling for thousands of servers requires a significant footprint of collectors to handle the load.

The scalability and performance is excellent. We use it globally.

Yes.