Logstash vs. SentinelOne Singularity

Logstash is a must in an ELK stack, which I am sure is going to be the #1 case. At any point when you have several sources, Logstash can be the common point to aggregate, and categorize those data. Then send this new data to its destination. Very handy. It is free and open source. It may not be appropriate to analyze data-sets dependent on each other but from a different data source. Reason being Logstash works on data at hand, and not wait for other data to arrive. It would be unwise for Logstashh to handle complicated, long-running transformations because this is injected and ejected. The faster you do it, the safer.

Incentivized

It works extremely well for investigating the root cause analysis of events because you can see so much detail into what was happening before, after, and around the detective incident. A weak point would be when the AI gets a little over-aggressive or doesn’t quite understand the use case for specific tools. Our RMM tool was detected as a pup.

• Plugin ecosystem allows modular extensions.
• Tight integration into the Elastic.com products of Beats and Elasticsearch, so minimal setup is required when using those tools.
• Filter plugins are powerful for extracting and enriching input data.

Incentivized

• SentinelOne provides excellent protection against known and unknown attacks to our endpoints.
• The recovery option provides a fast, first line of defense against ransomware and other system damaging attacks.
• SentinelOne requires minimal administrative support making it a very cost effective and efficient solution.

Incentivized

• Memory: Logstash is a HOG, if you are deploying it on commodity (i.e. cheap and old) hardware: You will need at least 2GB, just for Logstash. So don't expect to run your entire ELK stack on one AMD Athlon machine.
• Overlap: Logstash fills in an area of the ELK stack that makes the most sense: as a log file transformer / shipper. However, if you start breaking that stack, with the addition of other components- you start seeing where features of Logstash may be implemented or solved in the additional components much easier (or better, or to a higher degree of resolution)
• More Overlap: Since my team employs Syslog-ng extensively- Logstash can sometimes get in the way (and this may be a problem for DevOps stacks overall): You can configure Syslog to record certain information from a source, filter that data, and even export that data in a particular format. Logstash will pick that data up, and then parse it. However, if you don't keep your Syslog-ng configuration files, and your Logstash configuration files in sync, your results will not be what you expected, and this will translate into (sometimes) hours/days of work, hunting down a line item in a configuration file.

Incentivized

• Possibly for compatibility with legacy Windows OS's and non Windows OS's.
• Some settings are greyed out and unable to change but I believe this is to protect you from making a bad configuration change.
• Could do better with reporting at the base level subscription.

Incentivized

Reliable for simple installation and above all efficient

Incentivized

As I said earlier, for a production-grade OpenStack Telco cloud, Logstash brings high value in flexibility, compliance, and troubleshooting efficiency. However, this brings a higher infra & ops cost on resources, but that is not a problem in big datacenters because there is no resource crunch in terms of servers or CPU/RAM

There are some minor issues with the platform that can be mildly frustrating, but the overall performance, peace of mind, and ROI make it worth using. The management console is intuitive and easy to learn, the endpoint clients are simple but give IT professionals enough data to make management easy and simple

Incentivized

Their support is good and quick to respond. The one issue we faced was when a non-protection issue arose there was a lot of dancing around trying to figure things out. This was frustrating as it took significantly longer to figure out issues. Lots of repetitive log gathers, screen caps, uninstalls that never seemed to resolve issues. Eventually, the product would be updated and the issue seemed to be resolved, but seemed to be the only solution.

Incentivized

MongoDB and Azure SQL Database are just that: Databases, and they allow you to pipe data into a database, which means that alot of the log filtering becomes a simple exercise of querying information from a DBMS. However, LogStash was chosen for it's ease of integration into our choice of using ELK Elasticsearch is an obvious inclusion: Using Logstash with it's native DevOps stack its really rational

Incentivized

In the distant past we had used iSensor through Dell. I can't say much about iSensor because we never really had it show any incidents or activity or reports. It might be better these days but from what I can tell, SentinelOne is the Gold Standard currently.

Incentivized

• It is very difficult to give any figures on ROI, as it depends on many factors, and in a Telcocloud environment, it is much complex to find out; however, I would give some points below on ROI
• ROI based on flexibility is very high, as it reduces the time to find RCA
• ROI based on integration is very high because it supports multi-vendor environments, avoiding vendor lock-in & works across multi-cloud setups
• ROI on resource consumption is less because Logstash in 2-3 times more resource-intensive as compared to its lightweight alternatives resulting in latency

• SentinelOne has already proved its value by stopping attacks that would have gone otherwise unnoticed until much later in their infection process.
• The Vigilance team has provided quick response to threats that were not easily contained via the automated response SentinelOne's agents provide. This has given us a significant piece of mind.

Incentivized