Data Center Real-User Monitoring (DCRUM), discontinued vs. ScienceLogic SL1

Dynatrace Network Application Monitoring (NAM), formerly DCRUM, has improved greatly compared to when it was DCRUM; however, it still needs a lot of improvement in end-to-end flow capture with regards to network monitoring. Its alerting and integration capabilities are very good and easy to use. But it still needs a lot of tweaking in usability.

Incentivized

Appropriate if you are setting up a monitoring suite in new Infrastructure Environment. Definitely NOT suited for Migration Projects. ScienceLogic SL1 cannot cater to a lot of monitoring requirements which already would have been configured in old monitoring suite. Plus, limited support for customizations and having to go to "Feature Requests" route makes in extremely complicated.

Incentivized

• Dynatrace Network Application Monitoring (NAM), formerly DCRUM, is very useful to find the network packet flow across applications
• It shows the application behavior in terms of end-user performance
• It integrates very well with other Dynatrace components

Incentivized

• Best overall coverage of montioring different technologies.
• Easy to use in any environment
• Customizable being able to generate your own reports, dashboards, DA's, RBA's, etc.
• Have very good out of the box integrations with other monitoring solutions such as ServiceNow
• Always improving and regularly releasing new versions and upgrades to the system/DA's.
• Interactive community

Incentivized

• Its configuration requires a lot of technical and business knowledge to drive monitoring expectations to dashboards.
• DCRUM needs a robust monitoring architecture to store, analyze and visualize all collected data.
• DCRUM can't monitor the latest Microsoft Exchange versions.

• Creating powerpacks from scratch for new devices may be straightforward but will rarely be easy. Rewarding when completed, but not easy.
• Developer documentation needs a rethink. While the information may be there (it isn't always) it is not easy to find. This is not helped by using different terms for the same things.
• A developer console/dashboard for monitoring data collection from powerpacks instances without having to switch webpages or have to monitor multiple webpages.

Incentivized

We migrated away from our 20-year-old homegrown solution and have no back-tracking capability. ScienceLogic is demonstrating new capabilities that we would not have been able to do on our own using our legacy system.
We understand the capabilities of competitors based on our bake-off selection where ScienceLogic won on capabilities and future near-term potential (expandability, platform growth). We know that those competitors are not really close to where we have been able to push ScienceLogic (as a partner).

Incentivized

Best of breed.

We use ScienceLogic SL1 in our organization to serve effective monitoring solutions to our external customers. Our customers depend upon us for critical events/alerts related to their IT infrastructure gears and using SL1, we're able to provide them with a proactive monitoring solution that resolves an issue before an impact is noticed by the customer. There are very few monitoring solutions that can cater to a variety of Cloud platforms like Public Cloud (AWS, Azure) and private cloud simultaneously and SL1 addresses this business problem very well

Incentivized

Science Logic SL1 provides the option of Distributed deployment where multiple instances of each appliance can be deployed to manage the load and availability. SL1 provides a High Availability feature for Database Servers and Data Collection. If one of the Data Collectors in the collector group fails, it will automatically redistribute the devices from the failed Data Collector among the other Data Collectors in the Collector Group. The high availability feature for the Database server ensures that SL1 performs failover automatically to another server without causing the outage to the application.

Incentivized

The performance is entirely dependent on the complexity of the environment/network being used to host the platform. Outside of those factors, the platform runs very efficiently and quickly out of the box. We have integrations with other platforms and neither seem to take a hit from our moderate API usage. Any issues with performance would be experienced by choices made in infrastructure or complexity of things built by the customer to display in the GUI (overly complicated and cluttered dashboards for example)

Incentivized

The only thing missing for a 10, would be if they texted or called you back.

So far, it's good as part of my overall experience, except for a couple of use cases. The support team is well knowledgeable, has technical sound, and is efficient. When support escalates to engineering, the issue gets stuck and takes months to resolve.

Incentivized

When I joined our company, I did not know about the in person training at firts. Logging onto the SL University, I realised that there were different sessions being held at different times throughout the year. The training itself was good, but being in a different time zone, made it difficult to attend, but the sessions that I attended was great!

Incentivized

There are a lot of educational materials and courses on the SL1 training site (Litmos university). However the recording quality is sometimes not very good - screen resolution is low. There is a lack of professional rather than user-oriented documents and there are mistakes in documentation and education is not well structured.

Incentivized

Along with the purchase of the solution, we purchased a statement of work with their Professional Services organization to meet our outcomes and fill our critical gaps. The PS team was outstanding, very professional and allowed us to screen share while they built our integrations. In many cases they would teach us how they did certain things within the platform.

Incentivized

Nagios can't trace real user transactions from a front-end tier through a backend-tier,;with Nagios you only can monitor server availability and hardware issues. Riverbed is commonly used to determine networking issues without considering real user transactions impact on an application stack.

We evaluated a couple of other competitive products in the IT infrastructure observability domain; however, we found that ScienceLogic has a slight edge over the others for us. We encountered a cost barrier, as managing too many customers with an MSP setup was a costly affair, and several solutions did not offer an MSP solution at that time.

Incentivized

Our deployment model is vastly different from product expectations. Our global / internal monitoring foot print is 8 production stacks in dual data centers with 50% collection capacity allocated to each data center with minimal numbers of collection groups. General Collection is our default collection group. Special Collection is for monitoring our ASA and other hardware that cannot be polled by a large number of IP addresses, so this collection group is usually 2 collectors). Because most of our stacks are in different physical data centers, we cannot use the provided HA solution. We have to use the DR solution (DRBD + CNAMEs). We routinely test power in our data centers (yearly). Because we have to use DR, we have a hand-touch to flip nodes and change the DNS CNAME half of the times when there is an outage (by design). When the outage is planned, we do this ahead of the outage so that we don't care that the Secondary has dropped away from the Primary. Hopefully, we'll be able to find a way to meet our constraints and improve our resiliency and reduce our hand-touch in future releases. For now, this works for us and our complexity. (I hear that the HA option is sweet. I just can't consume that.)

Incentivized

• It has reduced the number of war rooms as well as the number of people involved to address issues.
• It helps in utilization trending for network capacity.
• It has prevented poor solutions from hitting production.
• When the various business units launch own initiatives such as third party tools or new platforms, it's become extremly easy to detect.
• The reports help in the field of continuous improvement as any changes are immediately discovered and can be compared to history. Deviations from what you have decided as a tolerance corridor can be used to trigger alarms, both positive and negative.

• Identified Major Incidents at least 50% of times when it happens
• Prevented Major Incidents due to alerting for basic IT Infra level issues at least more than 60% scenarios
• Provides ability to monitor large variety of IT Infra level devices and services