Amazon CloudWatch vs. ScienceLogic SL1

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon CloudWatch
Score 8.3 out of 10
N/A
Amazon CloudWatch is a native AWS monitoring tool for AWS programs. It provides data collection and resource monitoring capabilities.
$0
per canary run
ScienceLogic SL1
Score 8.6 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.
$7.50
per month per node
Pricing
Amazon CloudWatchScienceLogic SL1
Editions & Modules
Canaries
$0.0012
per canary run
Logs - Analyze (Logs Insights queries)
$0.005
per GB of data scanned
Over 1,000,000 Metrics
$0.02
per month
Contributor Insights - Matched Log Events
$0.02
per month per one million log events that match the rule
Logs - Store (Archival)
$0.03
per GB
Next 750,000 Metrics
$0.05
per month
Next 240,000 Metrics
$0.10
per month
Alarm - Standard Resolution (60 Sec)
$0.10
per month per alarm metric
First 10,000 Metrics
$0.30
per month
Alarm - High Resolution (10 Sec)
$0.30
per month per alarm metric
Alarm - Composite
$0.50
per month per alarm
Logs - Collect (Data Ingestion)
$0.50
per GB
Contributor Insights
$0.50
per month per rule
Events - Custom
$1.00
per million events
Events - Cross-account
$1.00
per million events
CloudWatch RUM
$1
per 100k events
Dashboard
$3.00
per month per dashboard
CloudWatch Evidently - Events
$5
per 1 million events
CloudWatch Evidently - Analysis Units
$7.50
per 1 million analysis units
No answers on this topic
Offerings
Pricing Offerings
Amazon CloudWatchScienceLogic SL1
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesYes
Entry-level Setup FeeNo setup feeRequired
Additional DetailsWith Amazon CloudWatch, there is no up-front commitment or minimum fee; you simply pay for what you use. You will be charged at the end of the month for your usage.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
Amazon CloudWatchScienceLogic SL1
Considered Both Products
Amazon CloudWatch

No answer on this topic

ScienceLogic SL1
Chose ScienceLogic SL1
The coverage and ease for what we need is just better. Most of the other solutions are just point tools that don't bring many functions together or are missing pieces to be successful.
Top Pros
Top Cons
Features
Amazon CloudWatchScienceLogic SL1
AIOps Features
Comparison of AIOps Features features of Product A and Product B
Amazon CloudWatch
-
Ratings
ScienceLogic SL1
6.9
2 Ratings
8% above category average
Monitoring and Alerting00 Ratings9.02 Ratings
Performance Analytics00 Ratings5.22 Ratings
Incident Management00 Ratings8.52 Ratings
Service Desk Integration00 Ratings9.02 Ratings
Root Cause Analysis00 Ratings4.62 Ratings
Capacity Planning Tool00 Ratings7.42 Ratings
Configuration and Change Management00 Ratings4.62 Ratings
Automated Remediation00 Ratings7.92 Ratings
Collaboration and Communication00 Ratings8.52 Ratings
Threat Intelligence00 Ratings4.62 Ratings
Best Alternatives
Amazon CloudWatchScienceLogic SL1
Small Businesses
InfluxDB
InfluxDB
Score 8.5 out of 10

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Medium-sized Companies
IBM Instana
IBM Instana
Score 9.0 out of 10
IBM Turbonomic
IBM Turbonomic
Score 8.4 out of 10
Enterprises
IBM Instana
IBM Instana
Score 9.0 out of 10
ignio AIOps
ignio AIOps
Score 8.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon CloudWatchScienceLogic SL1
Likelihood to Recommend
8.5
(38 ratings)
8.5
(207 ratings)
Likelihood to Renew
-
(0 ratings)
9.1
(19 ratings)
Usability
-
(0 ratings)
9.0
(13 ratings)
Availability
-
(0 ratings)
9.9
(13 ratings)
Performance
-
(0 ratings)
8.0
(13 ratings)
Support Rating
8.4
(8 ratings)
6.5
(18 ratings)
In-Person Training
-
(0 ratings)
8.3
(5 ratings)
Online Training
-
(0 ratings)
8.6
(5 ratings)
Implementation Rating
-
(0 ratings)
8.1
(78 ratings)
Configurability
-
(0 ratings)
10.0
(7 ratings)
Ease of integration
-
(0 ratings)
7.8
(14 ratings)
Product Scalability
-
(0 ratings)
8.0
(1 ratings)
Vendor post-sale
-
(0 ratings)
8.5
(5 ratings)
Vendor pre-sale
-
(0 ratings)
7.7
(4 ratings)
User Testimonials
Amazon CloudWatchScienceLogic SL1
Likelihood to Recommend
Amazon AWS
Cloud watch is great and essential if you decide to invest in AWS and have any need to monitor the health of all aspects of your VPC resources, or at the organizational level (multiple accounts). Another benefit of the service is constant upgrades at no additional costs; the software evolves to develop modules and interface improvements. For first-time users in AWS, this is going to take a bit to understand, so the learning curve to this metrics environment can seem overwhelming at first glance/use.
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ScienceLogic
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.
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Pros
Amazon AWS
  • It provides lot many out of the box dashboard to observe the health and usage of your cloud deployments. Few examples are CPU usage, Disk read/write, Network in/out etc.
  • It is possible to stream CloudWatch log data to Amazon Elasticsearch to process them almost real time.
  • If you have setup your code pipeline and wants to see the status, CloudWatch really helps. It can trigger lambda function when certain cloudWatch event happens and lambda can store the data to S3 or Athena which Quicksight can represent.
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ScienceLogic
  • 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
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Cons
Amazon AWS
  • Memory metrics on EC2 are not available on CloudWatch. Depending on workloads if we need visibility on memory metrics we use Solarwinds Orion with the agent installed. For scalable workloads, this involves customization of images being used.
  • Visualization out of the box. But this can easily be addressed with other solutions such as Grafana.
  • By design, this is only used for AWS workloads so depending on your environment cannot be used as an all in one solution for your monitoring.
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ScienceLogic
  • 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
  • The reporting feauture is a very untouched area.
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Likelihood to Renew
Amazon AWS
No answers on this topic
ScienceLogic
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).
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Usability
Amazon AWS
No answers on this topic
ScienceLogic
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
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Reliability and Availability
Amazon AWS
No answers on this topic
ScienceLogic
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.
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Performance
Amazon AWS
No answers on this topic
ScienceLogic
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)
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Support Rating
Amazon AWS
Support is effective, and we were able to get any problems that we couldn't get solved through community discussion forums solved for us by the AWS support team. For example, we were assisted in one instance where we were not sure about the best metrics to use in order to optimize an auto-scaling group on EC2. The support team was able to look at our metrics and give a useful recommendation on which metrics to use.
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ScienceLogic
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.
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In-Person Training
Amazon AWS
No answers on this topic
ScienceLogic
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!
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Online Training
Amazon AWS
No answers on this topic
ScienceLogic
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.
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Implementation Rating
Amazon AWS
No answers on this topic
ScienceLogic
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.
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Alternatives Considered
Amazon AWS
I believe that CloudWatch is a better solution to use with AWS services and resources in terms of cost and ease of integration with AWS infrastructure services. But keep in mind that Elasticsearch is better at aggregating application-level metrics. We chose CloudWatch because of its capabilities to integrate and monitor AWS services in almost real-time.
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ScienceLogic
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.
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Scalability
Amazon AWS
No answers on this topic
ScienceLogic
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.)
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Return on Investment
Amazon AWS
  • We were able to set up log streaming, retention, and simple downtime alerts within a few hours, having no prior experience with CloudWatch, freeing up our engineers to focus on more important business goals.
  • CloudWatch log groups have made it relatively easy to detect and diagnose issues in production by allowing us to aggregate logs across servers, correlate failures, isolate misbehaving servers, etc. Thanks to CloudWatch, we are generally able to identify, understand and mitigate most production fires within 10-15 minutes.
  • Choosing CloudWatch to manage log aggregation has saved us quite a bit of time and money over the past year. Generally, 3rd-party log aggregation solutions tend to get quite expensive unless you self-host, in which case you typically need to spend a fair amount of time setting up, maintaining, and monitoring these services.
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ScienceLogic
  • 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.
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ScreenShots

Amazon CloudWatch Screenshots

Screenshot of How Amazon CloudWatch works - high-level overviewScreenshot of CloudWatch Application MonitoringScreenshot of CloudWatch ServiceLens and Contributor Insights - expedite resolution timeScreenshot of Improve Observability with Amazon CloudWatchScreenshot of Visual overview of Amazon CloudWatch

ScienceLogic SL1 Screenshots

Screenshot of Application to infrastructure mapping with APM toolsScreenshot of CRM Business Service MapScreenshot of Mobile Banking Business Service Dashboard OverviewScreenshot of Mobile Banking Business Service Dashboard Availability ViewScreenshot of Mobile Banking Business Service Dashboard Anomalies ViewScreenshot of Business Services Leaderboard Dashboard Overview