Elastic Stack

Pros: Handles a ton of traffic without issues given enough hardware

Cons: Hardware requirements might be too much for little deployments.

Pros: Using elastic stack I can easily track my application logs.

Cons: I liked almost all the features but there is still scope in the dashboard.

Pros: I really like how multiple inputs can be managed at the same time.

Cons: The multiple versions of API and multiple possible format make it quite hard to get the correct one - mostly when a new release is out and user is pushed to use it - without proper support.

Pros: Elastic search is very fast, it returns the results within a few milliseconds. We can connect Logstash and Kibana very easily with Elastic.The filters in Kibana are very good. We can sort the data as needed.

Cons: I don't think there is anything to dislike about Elastic.

Pros: I mostly like the Elastic Search queries. Those follow a certain standard and work very well. Data retrieval is very easy and fast in Elastic Search.Visualizing data thru Kibana is very smooth and straightforward. It supports a couple of inbuilt dashboards to represent the data nicely.

Cons: Nothing to dislike about Elastic Stack. The only thing is configuration and setup should be correct. It could take some time for beginners.

Pros: Natural language processing like stemming, removing stopwords, multilingual search, tokenized storage etc.

Cons: When there is a large text searches, the elastic search sometime crashes. This needs to be optimized.

Pros: Widely-supported, almost a pioneer software for logging. Even now, most logging tools actually leverage ELK under-the-hood for their analysis or collection.

Cons: Pattern-matching needs to be more user-friendly, it would be best if they were able to leverage conventional regex usage instead of their custom format. Elastic RegExp queries must match the entire string and take a bit of learning, see here for syntax documentation: [SENSITIVE CONTENT]

Pros: Lightening fast, we built BI dashboards and the 5 years reports data gets populated within seconds that would otherwise takes hours traditionally database or BI tool

Cons: Very Big learning curve, first tie deployment takes very long time to make it work perfectly and then optimize it. need very good technical expertise

Pros: Provides a large and powerful set of features suitable for many different data-dependent areas. Superb support.

Cons: Depending on use case it might be quite difficult to use - the most intuitive solution might not be the best at all.

Pros: It is very easy to deploy using docker containers and Kubernetes support. It's very easy to query a high volume of data and get results in seconds. Its easy-to-use UI is self-explanatory and also the forum support and documentation are quite helpful.

Cons: Sometimes it crashes in between. Query structure is somewhat completed, and can be made simple with more specific examples to use directly in projects.

Pros: 1.Allows Faster searching and query operations 2.Provides with easy data visualization for analysis 3.Support for multiple data sources 4.Good SDK support for quick integration with application 5.Scalable as per the requirement with support of kubernetes

Cons: 1.UI is simple ,could be made more robust and dynamic 2.Calculations and processing speed can be further improved 3.Proper usage knowledge is required when using it on scalable platforms

Pros: Managing application logs have become very easy with the help of Logstash, Elastic, and Kibana (ELK) since we can use the dashboard to visualize the performance and spot errors and performance issues. This has made my business move more faster and agile.

Cons: The cost may not be suitable for very small-scale companies but otherwise, I would say all the features are amazing.

Pros: It has all the funtionalities I need for incident management. You can browse logs and create dashboards in order to help visualize the data

Cons: Honesty, I cannot point anything that I don't like. It's perfect for my day to day job

Pros: It is good to store and monitor logs with Kibana.

Cons: The elasticsearch version management is bad because next version could have critical changes from previous.

Pros: Die search engine ist der Hammer. Die Software funktioniert gut, zuverlässig und performant.

Cons: In 4 Jahren hat 3 mal der Firmensitz gewechselt, letztes mal ins Ausland. Cowboy-Manieren beim Vertragsverlängerung - friss unsere AGBs (in Business-English) oder stirb. Ständig wechselnde Ansprechpartner. Rechnungen mit wechselnden Kontoverbindungen.

Pros: I use it for syslog and network monitoring. Data analysis and graphical representations are great.

Cons: Elk installation steps can be made easier.

Pros: The fact that it is easy to set up and use.

Cons: The platform seems to be a bit slow for me in decent usage

Pros: One of the best features I like is that Elastic built their own kubernetes operator to extend the k8s orchestration and make it easy to deploy, scale, change, secure and configure hot-warm infrastructures. Their operator saves a ton of time during configuration. I have deployed stacks on different k8s architectures like Azure Kubernetes Service, Amazon Elastic Kubernetes Service and small on prem clusters with microk8s without issues. When we reach performance thresholds we add more elastic nodes and ECK secures and joins it to the cluster and in minutes we can leverage the extra compute. A lot of changes that are done after going to PROD are non-disruptive since ECK is aware of the main node and makes sure to pass the master role before the main one is re-deployed. I have also migrated Elastic Cloud Enterprise deployments running on bare metal and the stability of ECK is unmatched.

Cons: Currently it is not recommended or supported for a PROD cluster to do its own self monitoring so you have to deploy a monitoring cluster. In cloud scenarios this adds costs and extra complexity so it will be great to have this feature supported.

Pros: We are using ELK Stack SIEM, a scalable aggregation engine that helps us find patterns in our data as well as provides a wide array of customizable analytics and reports. With Elastic Stack, we have a better understanding of flaws and security issues, particularly memory tier support that ensures the security of our data and networks.

Cons: It is very challenging and time-consuming to upgrade cluster node roles and data replication.

Pros: Provides great features for log ingestion, normalisation and visualisation. Has a free open source tier which can be used to cover many use cases. Visualisation options are diverse and powerful. Solid community support in forums.

Cons: Initial setup can be tedious and is rather complex. The provided security ruleset tends to produce many false positives and requires fine tuning. Log ingestion options are not entirely covered by the web user interface.

Pros: 1. End to End Solution of enterprise logs with services such as Logstash, Elastic and Kibana. 2. Strong User Community and support. 3. Easy to use and implement. 4. Proactive updates on possible downtimes. 5. Dashboards for easy navigation.

Cons: 1. Cloud performance is slower than on premises installation. 2. It crashes in between which delay things sometimes.

Pros: the very powerful search engine I search around 5 million log in a second only. Very nice real-time dashboard, I can integrated with other software and see all the view of network traffic, traffic flow very well.

Cons: well I would say, it's pretty good already, but still some function need to use command alot.