Instana, an IBM company since the December 2020 acquisition, provides APM services for SOA, microservices, containerized applications and Kubernetes, and cloud native applications, as well as discovery and monitoring for IT assets.
$18
per month per Managed Virtual Server (MVS)
ScienceLogic SL1
Score 8.9 out of 10
Enterprise companies (1,001+ employees)
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.
N/A
Pricing
IBM Instana
ScienceLogic SL1
Editions & Modules
Essentials
$18
per month per Managed Virtual Server (MVS)
Standard
$75
per month per Managed Virtual Server (MVS)
Self-Hosted
$93.80
per month per Managed Virtual Server (MVS)
No answers on this topic
Offerings
Pricing Offerings
IBM Instana
ScienceLogic SL1
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Required
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.
We chose IBM Instana for its very affordable price, the ease of use of the solution, which was perfectly suited to our needs and specifications, and the feedback from our teams, who had no trouble getting to grips with it in a very short time.The IBM Instana solution is very …
IBM Instana provides 60 seconds granularity whereas the other products use time series data IBM Instana automatically detects the Service Endpoints which helps us trace all the calls pinpointed to service endpoints. IBM Instana provides complete Auto Discovery with no …
Automatic application discovery with one agent installation instead of manual configuration for each application and multiply agents for each technology stack.
Automatic tracing for application calls without the need to add complex configuration and application instrumentation.
Senior Manager - Performance & Reliability • Information Technology
Chose IBM Instana
1- ROI is higher as the budget is much less than other 2- the way of calculating license is much better and fit us and this affect the ROI 3- the ease of implementation
The primary reason we choose IBM Instana was that is was compatible with nearly all of our apps without requiring any modifications to our code. We are really happy that we decided to adopt IBM Instana.
IBM Instana meet LMRA requirements, as IBM Instana is more useful to deep-dive each transaction from Real-user monitoring itself when compared to other APM's in the market. Also gives more flexibility especially from the support perspective to identify bottlenecks and to …
As a DevOps engineer, I've explored various Application Performance Monitoring (APM) tools, including New Relic for real-time insights, AppDynamics for code-level visibility, Dynatrace for AI-driven monitoring, Datadog for comprehensive observability, Splunk for log management, …
Splunk is also a wonderful tool for log analysis and operational troubleshooting however auto discovery and dependency flow creation makes Instana standout. We have to do a lot of preprocessing to ingest and format data in Splunk and then write complex queries for gathering the …
We chose IBM Instana for several reasons, and the most important one is that we didn't have to make changes in our code for nearly all of our applications for it to work. We are happy with the decision we made to use IBM Instana.
We have used them and for the moment we have chosen IBM Instana first of all because of the price because it is accessible and it works in terms of the results we have obtained, also the way of presenting the schemes and the performance of the systems is very good.
Superior value for money, simpler license approach with automated functions (installation, detection, update, and alarm). Nothing can stop IBM Instana's footprints in the international market as it progressively gains strength and grows in the market. With fair and inexpensive …
New Relic has it's own perks but when it comes to large infrastructure, we always face some issue at stability but IBM Instana never fails here. In my opinion, Inbuilt dashboard and inbuilt alerting feature what makes IBM Instana better than compared to other tools. I think …
In my experience, they both have independent strengths and shortcomings, though I have found IBM Instana to be much better for general monitoring and setting up alerts to get ahead of any problems. Contrastly, I think humio/falcon has been easier to use when it comes to …
ScienceLogic SL1 supports large scale of IT Infrastructure devices and vendors. Was the single tool providing multiple functionalities at same time and allowed to remove additional legacy tools used for monitoring. Allowed integration with incident management and CMDB. Allowed …
From a capability perspective they stack up very similar but from a look and feel, ScienceLogic SL1 one is miles behind the curve on all three. We chose SL because we already had elements of the service in place on our infrastructure from our previous MSP so they were a …
I see great potential and infact i do strongly beleive it offers even beter capabilities than the traditional tools out there but again it comes down to how well you have trained us on how to unlock these capabilities. I suggest incentives for techs for providing feedback for …
Geneos is more complicated and 'heavy' to setup. It requires a lot of expertise in setting up. Also the dashboards are not great. ScienceLogic SL1 works well for customer facing dashboards.
Entuity was lacking a lot of custom reporting and also the out of the box automation and RBA was also less. Our customers were mainly looking for devices which are next gen like sdwan which Entuity doesn't support. When it come to ScienceLogic SL1 it will support all sets of …
Galileo analyzes storage arrays and backups more thoroughly, but SL1 is much better for host and network monitoring. SL1 has some storage monitoring features for some storage arrays, but they are not as detailed.
I was not part of the team selecting ScienceLogic SL1. Our goal was to increase event visibility in our server environment. We were using scripting which created many false events. SolarWinds is primarily used in the Network space to monitor network gear.
Agentless product that can integrate easily with other product and also allow us to automate tasks, example closing tickets when events are cleared automatically which user interactions.
Just because Science logic provides much more better enhancement and getting improved everyday. The autonomous integration and overall customization provided by the SL1 Platform is outstanding. In every sections be it in Monitoring or checking system logs and provide the best …
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.
ScienceLogic SL1 has a greater understanding and maturity on what Infrastructure monitoring needs to be and has to include at a decent price point for what it offers compared to its competitors.
ScienceLogic SL1 comparing with ITM/Netcool monitoring has better price. It's more easy to implement and mange ScienceLogic SL1 then other monitoring tools.
With enterprise IT assets in a multitude of ecosystems, cloud infrastructures and sometimes still left stuck in a legacy on prem architecture, IBM Instana makes it easy to get the right data to drive development and / or DevSecOps processes with tangible input from the target environment itself.
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.
I believe that the "live" option in monitoring does not truly update the status in real-time, thus I must manually update to feel comfortable.
The call analysis tool might be improved, third-party resources are restricted, and the pricing is slightly more than competitors in comparable categories.
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.
Instana has been able to fulfill our all requirement and provide out of box solution for multiple component like AWS RDS Monitoring and real time alerting setup on basis of that. it is also easy to integrate with other open-source alerting and monitoring tools which makes it easier to incorporate into our solutions
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).
IBM Instana totally alters our monitoring approach since it increases the stability of the system and simplifies the process of problem solving. And since it helps to lower the degree of alert exhaustion that we experience, it is a total game changer for us.
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
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.
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.
As a DevOps engineer, I've explored various Application Performance Monitoring (APM) tools, including New Relic for real-time insights, AppDynamics for code-level visibility, Dynatrace for AI-driven monitoring, Datadog for comprehensive observability, Splunk for log management, Stackify Retrace for error tracking, and Raygun for crash reporting. Each tool offers distinct features, and the choice depends on specific use cases, technology stacks, and organizational needs. Thorough evaluations, considering factors like ease of use, integration capabilities, and scalability, help in selecting the most suitable APM solution for effective application monitoring in a DevOps environment.
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.
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.)
Let's me monitor and pinpoint issues across multiple critical systems and applications that work in tandem, reducing drastically, the time in identifying root cause and solving the issues.
Let's me deep dive into issues found with a lot of detailed information about particular requests , and find proper solutions by my own research or even with Gen AI assistant using Watson.x or you could prompt your AI solution of choice as well.
All systems fail at some point, so IBM Instana gives stakeholders ease that large complex and critical systems that affect the very livelihood of people is being observed with pinpoint precision and that issues are addressed promptly and with compass pointing north towards the problem's root cause and solutions.
