Apache Log4j vs. Check Point Quantum Smart-1 Security Management vs. Datadog

There is multiple reasons. All types are logging messages support not only string msg. We can use parametrized variables for logging Support advance filter for logging like (Data, Markers, Regular Expression) Support Plugin Architecture (We just use the dependency and Layout configuration with minimal config, and this will start to work) Integration support with application server Could enable.

Incentivized

It is very suitable to manage and monitor a large amount of network security information. It is not recommended to use the network information security management of a single firewall device in terms of cost.

Incentivized

Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.

Incentivized

• Integration with java.
• Configure logging levels.
• Customize logging contents.

Incentivized

• Centralized Database
• Detailed and indexed logging
• Securely connects to each device

Incentivized

• The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
• Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
• Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.

Incentivized

• Fixed the vulnerability which is reported which affect many big brand.
• There should be security check to check all vulnerability.

Incentivized

• The user interface is very convenient to use. To say what is missing. It is only not supported in the language system that displays Chinese.

Incentivized

• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

Incentivized

Definitely will not revisit after our issues and, in my opinion, poor support.

Incentivized

There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

The ability to customize logging levels and manage log files is superior to other products we have looked at; due to this we selected to go with log4j.

Incentivized

Far exceeds any testing we were able to think of when testing.

Incentivized

Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.

Incentivized

• Good logging tools we can integrate with minimal resource consumption.
• Ease of understanding.
• Plugin play component Architecture.
• Advance filter support can be used to filter all types of logs and events, which can be further analyzed.

Incentivized

• Reduce personnel management costs
• The elastic expansion capability solves the rapidly changing environment that needs to be changed.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized