ScienceLogic is a hybrid IT infrastructure monitoring tool that is designed to help organizations digitally transform their companies by making the management of complex, distributed IT services easier. Using the solution’s discovery techniques, users can find everything they need in a network, gaining visibility across all vendors and technologies that are run in the cloud or data centers. In addition, the ScienceLogic solution can help users seamlessly monitor and manage cloud environments, monitor network resources, manage storage, and monitor app health and performance.
The pricing for ScienceLogic is based on factors such as the number of endpoints and monitoring points used. It is not based on a usage basis but rather on the storage that is being utilized. The licensing is straightforward and easy to understand, with no hidden charges.
The use of ScienceLogic has resulted in improved visibility and assistance on the platform, leading to a positive return on investment. The monitoring tool may not provide immediate ROI, however, in the second or third year, it helps resolve incidents and enhance visibility.
The primary use case of ScienceLogic is as a hybrid monitoring solution for infrastructure and cloud environments. It is used for discovery, relationship mapping, and integration with CMDB and ticketing systems.
The product is used to integrate relationship mapping to CMDB in real-time, automate incidents, perform incident automation, and automate data center tasks. It is also used for remediation and diagnostic-level automation. ScienceLogic is used for monitoring and orchestrating remediation, as well as for monitoring network devices and performing granular discovery.
It is used as a reporting tool to provide inventory details and as a source of truth when the CMDB is not updated. ScienceLogic is primarily used as an IT infrastructure monitoring tool by the IT team to monitor the server, database, and cloud environment.
The most valuable features of ScienceLogic include its patented technology called Dynamic Component Mapping, which works with CMDB and offers flexibility for developing automation use cases. It is a Python-coded tool that can be integrated with application monitoring tools.
Other valuable features include AI and machine learning capabilities, the power pack that allows integration with third-party tools, the ability to create event management solutions, the agentless monitoring feature based on SNMP, and the highly flexible graphs that enable precise information input.
It also has good monitoring capabilities across various environments, excellent scalability, and the ability to monitor UPSs and power supplies in data centers.
Improvements needed for ScienceLogic include:
1. Enhanced education and support for strategic partners to expedite deployment and reduce reliance on ScienceLogic's professional services team.
2. Simplification of the implementation process for easier integration.
3. Addressing limitations in application monitoring and providing integrated monitoring for market-leading applications.
4. Improving performance and stability, especially when dealing with a large volume of monitoring.
5. Streamlining customization of templates and providing better professional support.
6. Resolving bugs that often arise with new releases.
7. Increasing self-service capabilities and reducing dependencies on ScienceLogic's engineers for tasks like connecting to external platforms.
8. Improving user-friendliness and understanding of ScienceLogic's unique architecture.
9. Enhancing notification features to proactively alert users about issues and changes in data collection.
10. Providing more detailed documentation and information about the backend workings of ScienceLogic.
11. Offering more pre-built Power Packs or scripts to meet customer requirements.
The initial setup for ScienceLogic is relatively easy and straightforward. It can be implemented as a monitoring tool within a few weeks, depending on the size of the infrastructure.
The setup process involves deploying different components such as collectors, data collectors, message collectors, admin portal, and database layer. The deployment time varies based on the number of servers, with smaller deployments taking less time.
It is recommended to have some level of engineering expertise and involvement during the rollout. The setup can be done using a dedicated appliance or a virtual machine.
ScienceLogic is highly scalable, with the ability to be horizontally and vertically scaled. However, some users mentioned that the scalability could be improved, especially for the cloud versions and on-premise version, which is not as simple.
It is suitable for enterprise-level organizations and can accommodate a high number of users. However, onboarding users to ScienceLogic has been challenging, causing difficulties in creating functional profiles for new users.
Customers have experienced some challenges during the implementation process and have relied on the support team at ScienceLogic for assistance. They appreciate the prompt and pleasant support provided by ScienceLogic, with support available around the clock.
However, some customers feel that the support lacks knowledge at times. Those with premium support generally have good customer service, although there have been instances where the urgency of requests has been lowered, resulting in delayed responses.
The solution of ScienceLogic is considered stable by most reviewers. They rate the stability as good, reliable, and rarely experiencing issues. That said, some mention that there have been some stability issues in large environments.
The pricing for ScienceLogic is based on factors such as the number of endpoints and monitoring points used. It is not based on a usage basis but rather on the storage that is being utilized. The licensing is straightforward and easy to understand, with no hidden charges.
The use of ScienceLogic has resulted in improved visibility and assistance on the platform, leading to a positive return on investment. The monitoring tool may not provide immediate ROI, however, in the second or third year, it helps resolve incidents and enhance visibility.
The primary use case of ScienceLogic is as a hybrid monitoring solution for infrastructure and cloud environments. It is used for discovery, relationship mapping, and integration with CMDB and ticketing systems.
The product is used to integrate relationship mapping to CMDB in real-time, automate incidents, perform incident automation, and automate data center tasks. It is also used for remediation and diagnostic-level automation. ScienceLogic is used for monitoring and orchestrating remediation, as well as for monitoring network devices and performing granular discovery.
It is used as a reporting tool to provide inventory details and as a source of truth when the CMDB is not updated. ScienceLogic is primarily used as an IT infrastructure monitoring tool by the IT team to monitor the server, database, and cloud environment.
The most valuable features of ScienceLogic include its patented technology called Dynamic Component Mapping, which works with CMDB and offers flexibility for developing automation use cases. It is a Python-coded tool that can be integrated with application monitoring tools.
Other valuable features include AI and machine learning capabilities, the power pack that allows integration with third-party tools, the ability to create event management solutions, the agentless monitoring feature based on SNMP, and the highly flexible graphs that enable precise information input.
It also has good monitoring capabilities across various environments, excellent scalability, and the ability to monitor UPSs and power supplies in data centers.
Improvements needed for ScienceLogic include:
1. Enhanced education and support for strategic partners to expedite deployment and reduce reliance on ScienceLogic's professional services team.
2. Simplification of the implementation process for easier integration.
3. Addressing limitations in application monitoring and providing integrated monitoring for market-leading applications.
4. Improving performance and stability, especially when dealing with a large volume of monitoring.
5. Streamlining customization of templates and providing better professional support.
6. Resolving bugs that often arise with new releases.
7. Increasing self-service capabilities and reducing dependencies on ScienceLogic's engineers for tasks like connecting to external platforms.
8. Improving user-friendliness and understanding of ScienceLogic's unique architecture.
9. Enhancing notification features to proactively alert users about issues and changes in data collection.
10. Providing more detailed documentation and information about the backend workings of ScienceLogic.
11. Offering more pre-built Power Packs or scripts to meet customer requirements.
The initial setup for ScienceLogic is relatively easy and straightforward. It can be implemented as a monitoring tool within a few weeks, depending on the size of the infrastructure.
The setup process involves deploying different components such as collectors, data collectors, message collectors, admin portal, and database layer. The deployment time varies based on the number of servers, with smaller deployments taking less time.
It is recommended to have some level of engineering expertise and involvement during the rollout. The setup can be done using a dedicated appliance or a virtual machine.
ScienceLogic is highly scalable, with the ability to be horizontally and vertically scaled. However, some users mentioned that the scalability could be improved, especially for the cloud versions and on-premise version, which is not as simple.
It is suitable for enterprise-level organizations and can accommodate a high number of users. However, onboarding users to ScienceLogic has been challenging, causing difficulties in creating functional profiles for new users.
Customers have experienced some challenges during the implementation process and have relied on the support team at ScienceLogic for assistance. They appreciate the prompt and pleasant support provided by ScienceLogic, with support available around the clock.
However, some customers feel that the support lacks knowledge at times. Those with premium support generally have good customer service, although there have been instances where the urgency of requests has been lowered, resulting in delayed responses.
The solution of ScienceLogic is considered stable by most reviewers. They rate the stability as good, reliable, and rarely experiencing issues. That said, some mention that there have been some stability issues in large environments.
By implementing ScienceLogic, organizations can:
ScienceLogic Features
ScienceLogic has many valuable key features. Some of the most useful ones include:
ScienceLogic Benefits
There are many benefits to implementing ScienceLogic. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the ScienceLogic solution.
A Senior Infrastructure Architect says, “ScienceLogic can offer both serverless connectivity and agent connectivity. The stability of ScienceLogic is great.”
A Senior Consultant at a tech services company mentions, “It is very easy to configure because we are using an agent-less version. You can very quickly implement a collector for monitoring device servers.”
ScienceLogic is the #1 ranked solution in top Unified Communications Monitoring tools, #5 ranked solution in top Event Monitoring tools, #5 ranked solution in top IT Operations Analytics tools, #7 ranked solution in top Server Monitoring tools, #8 ranked solution in top AIOps tools, #13 ranked solution in top Cloud Monitoring Software, #19 ranked solution in Infrastructure Monitoring tools, and #20 ranked solution in best Network Monitoring Tools. PeerSpot users give ScienceLogic an average rating of 8.4 out of 10. ScienceLogic is most commonly compared to Dynatrace: ScienceLogic vs Dynatrace. ScienceLogic is popular among the large enterprise segment, accounting for 68% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 22% of all views.Kellogg Company, Booz Allen, Cisco, Red Bull, Fidelus, Telstra, Comcast, CSC, Peak 10, HughesNet, Hosting, Datapipe, US Army, Equinix, Rite Aid, Carbonite, Sybase, Carpathia, AT&T, ePlus, Dimension Data, Virtustream, Boeing, Honeywell