Amazon CloudWatch is a native AWS monitoring tool for AWS programs. It provides data collection and resource monitoring capabilities.
$0
per canary run
SolarWinds Loggly
Score 5.1 out of 10
Mid-Size Companies (51-1,000 employees)
Loggly is a cloud-based log management service provider. It does not require the use of proprietary software agents to collect log data. The service uses open source technologies, including ElasticSearch, Apache Lucene 4 and Apache Kafka.
$79
per month/billed annually
Pricing
Amazon CloudWatch
SolarWinds Loggly
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
Standard
$79
per month/billed annually
Pro
$159
per month/billed annually
Enterprise
$279
per month/billed annually
Offerings
Pricing Offerings
Amazon CloudWatch
SolarWinds Loggly
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
With 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.
Free trial for Standard and Pro plans for 14 days with all features.
If you use any AWS services, CloudWatch is the natural choice to monitor & troubleshoot your workload. Thankfully, for most AWS services, CloudWatch is either built-in or very easy to set up. However, being proficient in browsing & tracking the log events would take some training & practice. Having some experienced people on the team would help immensely, especially in spreading the skill to the rest of the team.
SolarWinds Loggly is great for capturing and organizing logs from 3rd party sources such as NGINX. Without SolarWinds Loggly it's really difficult to manage the logs overtime, find traffic patterns, and identify issues before they become a problem. Anyone who is routinely searching through massive log files could quickly benefit from the SolarWinds Loggly and it's capabilities.
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.
Modern: Loggly is modern: Dashboards, realtime information and the ability speak many different data sources and environments makes it an attractive choice
Configurability: Loggly gets log parsing right: by allowing you to in real time- filtering of log data, tagging and identifying data sources
DevOps friendly: Loggly is very Componentized: You can have an instance of Loggly running that will Monitor your Linux instance, in addition to all of it's services, as an example. Also, you can start/stop Loggly, without affecting your other components
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.
Once the logging limit is exceeded, there are no logs period. Unexpectedly noisy logs often correlate with services misbehaving and potentially leading to disruption. An outage is an awful time to lose visibility into the entire system of apps. Some ways to bridge this gap would be appreciated.
Filtering by tags is not intuitive in the web interface. You may believe that you are performing the same search and filter as last time since the tags entered are the same, however, this is often not the case. The reliable way to know that you have the same filter is to bookmark the URL. This lack of ease in usability results in devs using Loggly less than they could and implementing logs less effectively during development time (since they don't consider themselves likely to view them anyway).
Would like to see a way to onboard our less experienced devs to using Loggly effectively.
Although the tool itself is easy to integrate and is readily available for use, it has its limitations. The key limitations of cloudwatch are with respect to cost incurred on log retention and log querying. While for key use cases this is sufficient, for more advanced use cases, Amazon CloudWatch doesn't work out. Also, obviously it is tightly coupled with AWS, which makes you look away if you need a single tool for all monitoring
Loggly's easy setup, very good customer support, and intuitive interface make Loggly very easy to use. User access management is also very easy as we can tailor the experience for each of our developers to access the information they need without having to wade through other information. While there was a slight learning curve in how to view the logs the way some specifically wanted, everything was possible and quite easy to do.
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.
The support team have been great when we have logged tickets or had issues, most of the time it is down to user training, however we have had a couple of bugs that they have been able to iron out for us.
We use Cloudwatch for simpler monitoring, but these metrics and logs often feed into bigger ecosystems across our organization. The metrics and logs in Cloudwatch allow our developers quick and easy access to the data they need whilst easily integrating the same data into more prominent platforms for wider analysis, including Service desk support, SecOps, and ITOps monitoring within the organization.
I actually couldn't get anybody from Datadog to engage with me, the main problem we had was that our devices couldn't connect to an encrypted port, but we didn't want to send our logs in plain text over the internet. We implemented an on-net log aggregator which then connects to Loggly over encrypted UDP. In theory Loggly made this particularly easy providing configuration snippets for most of the common log services (e.g. rSyslog, syslog-ng). Unfortunately the documentation was out of date and none of the provided configs worked, fortunately they were close enough that combined with our own syslog-ng experience we were able to get it up and going relatively painlessly. The choice then of going with Loggly, backed by an industry favourite in Solarwinds was a no brainer.
Loggly has alerted us to several bugs, ranging from major to small to "would have been a major problem under load."
It's great having our disparate logs collected and the alerts we have set up around them let us know recently that somebody used an incorrect document to generate a mass email. Users were trying to log in with the link provided but getting 401s and I have an alert configured to tell me about high numbers of 4xx errors.
Metrics and alerts around metrics have given us peace of mind that automated fulfillment systems aren't going off the rails and costing us hundreds of dollars.
