ScienceLogic is a system and application monitoring and performance management platform. ScienceLogic collects and aggregates data across and IT ecosystems and contextualizes it for actionable insights with the SL1 product offering.
$7.50
per month per node
Splunk Infrastructure Monitoring
Score 8.7 out of 10
N/A
SignalFX is Real-Time Cloud Monitoring and Observability for Infrastructure, Microservices and Applications. SignalFX was acquired by Splunk in August 2019. SignalFX Infrastructure Monitoring provides real-time cloud monitoring and observability platform for infrastructure, microservices and DevOps. A new SignalFX product, SignalFx Microservices APM, was released March 2020 to detect issues, provide real-time app troubleshooting, and future-proof expectations.
$15
per month
Pricing
ScienceLogic SL1
Splunk Infrastructure Monitoring
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
ScienceLogic SL1
Splunk Infrastructure Monitoring
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Required
No setup fee
Additional Details
ScienceLogic SL1 offers four tiers:
SL1 Advanced – Application Health, Automated Troubleshooting and Remediation Workflows
SL1 Base – Infrastructure Monitoring, Topology & Event Correlation
SL1 Premium – AI/ML-driven Analytics, Low-Code Automated Workflow Authoring
SL1 Standard – Infrastructure Monitoring – with Agents, Business Services, Incident Automation, CMDB Synchronization, Behavioral Correlation
To get pricing for each tier, please contact the vendor.
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.
Splunk Infrastructure Monitoring is well suited for any complicated environment where you have apps and servers across multiple clouds and platforms and products. If you have a data centre where all your apps and servers are in one single network, you could probably get away with older solutions. But for any modern, complex, hybrid-cloud microservices environment, Splunk Infrastructure Monitoring is a must-have.
SignalFX handles historical metric aggregation exceptionally well, providing a multifaceted approach to event detection based on anomalies.
SignalFX's cost is incredibly flexible with their pricing model of DPM (data-point per minute) vs the traditional "per host" model that most monitoring SaaS use.
SignalFX support is responsive and knowledgeable, very eager to help solve your immediate problems.
SignalFX integrations is vast and constantly growing, making adoption easy even when multiple different open-source technologies are used in your stack.
More freedom to create custom dashboards as on the previous versions we could do much more
The Performance TAB windows is too small and cannot be resized or maximized when looking at reports for "Overview", "File System" and any of those items.
There are not enough widgets to create stunning dashboard in AP2
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).
Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net
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
I find that learning the interface can take some time. We need a better show-and-tell on how the Teams pages, Dashboard Groups, Dashboards and charts delay. Advance SignalFlow is sometimes hard to build. Some better samples of advanced SignalFlow would be helpful. For example, Splunk SPL has a vast resource of examples.
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.
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)
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.
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!
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.
Love to use Science logic tool as our first monitoring tool to provide services to the customer. Auto restart feature in Sl1 will allow us to get event when those crucial services has not started after server reboots and also minimize the P1's that we have as a result of that.
Science logic SL1 is so user friendly and it's really easy to navigate between function. I would recommend Sciene logic SL1 to all of them who are looking for really useful monitoring tool and expecting easy way of managing it.
They’re not for the same purpose but we’re using NewRelic and Honeycomb for monitoring purposes. NewRelic is used for HTTP client monitoring for system related throughput, error, database and external client monitoring. Honeycomb is used to monitor actual HTTP request/response values. Splunk [Infrastructure Monitoring] is used for real-time application related throughout and error monitoring.
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.)
Once a powerpack is developed and configured for a device for one customer, it is easy to deploy the same powerpack on a second customer estate and configure specifically for that customer without having to reinvent the powerpack. This saves time and therefore money.
Once the customer estate tuning is complete, the Operations team have come trust the alerts. This is especially true when transient or self-correcting alerts are automatically cleared without ops team involvement, but a record is still available for audit and debugging purposes. This saves time and therefore money.
When setup correctly, it provides good visibility into applications, devices and whole customer estates. This saves time and therefore money when issues arise.
Caused us to get a lot of spam when we redeployed apps and old instances stopped sending metrics. Muting alerts solves this, but people often forget to do it or do it incorrectly.
Helped us find historical info about instances/apps.
