Logz.io in Boston offers their enterprise-grade log analytics application, oriented towards providing data security and eliminating the need for capacity management.
$0
1 day of log retention.
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
Logz.io
ScienceLogic SL1
Editions & Modules
Log Management - Community
$0
1 day of log retention.
Log Management - Pro
$.92
per ingested GB. 7 days retention.
Distributed Tracing - Pro
$5
Per million spans.
Infrastructure Monitoring - Pro
$12
per month per 1000 time-series metrics.
Log Management - Enterprise
Custom
Cloud SIEM - Enterprise
from $1.49
per ingested GB. Price includes Logz.io Log Management
No answers on this topic
Offerings
Pricing Offerings
Logz.io
ScienceLogic SL1
Free Trial
Yes
No
Free/Freemium Version
Yes
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.
More Pricing Information
Community Pulse
Logz.io
ScienceLogic SL1
Features
Logz.io
ScienceLogic SL1
AIOps Features
Comparison of AIOps Features features of Product A and Product B
It is appropriate for companies that focus on developing extremely simple applications. The great visibility it provides makes it ideal to avoid problems that may affect the entire business or company thanks to the fact that it is capable of emitting dozens of alerts in a short time. Sometimes the search behavior becomes slow and inefficient, which can be uncomfortable.
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.
Alerting - Logz.io allows you to set up numerous alerts and define the specific conditions to trigger these alerts, such as the number of occurrences over a specific period of time and severity.
Notifications - The supported integrations with Slack and OpsGenie make it easy to set up alerts to specific groups or users, like those in a particular Slack room or OpsGenie group. This is good to reduce noise and limit initial notifications to those who really need to get it.
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.
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).
Am really exited to use the reports generated especially AWS Cost and Usage Reports function tracks your AWS usage and provides estimated charges associated with your account so that we can reduce the data costs to a greater extend. This integration allows you to ship logs from your AWS Cost and Usage Reports to your Logz.io account.More amazing features awaits you in Logz.io account.
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)
In the past, my team has been able to get in contact with Logz.io quickly and easily to address our questions about the product to see if it could fully meet all our needs. Some of the features we needed at the time were not available, but were on the Logz.io team's roadmap to implement in the future. I found their team to be friendly, professional, and helpful
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.
Graylog and Microsoft System Center lacks infrastructure management and logging, proper analytics is done only on Logz.io. The customer support is also really great for Logz.io, we are really pleased with their support and timely action. The migration was also easy and took us hardly a day to set up and run the solutions.
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.)
