Splunk is software for searching, monitoring, and analyzing machine-generated big data, via a web-style interface. It captures, indexes and correlates real-time data in a searchable repository from which it can generate graphs, reports, alerts, dashboards and visualizations.
I didn't get to fully evaluate Logstash as our corporation was already using Logstash, but both seemed like viable solutions to the problem that we were having. I wanted to evaluate Logstash some more, both did seem like they would work for the business needs that we had, we …
Both Logstash and Greylog are open-source solutions that provide similar capabilities to Splunk. They are excellent products in their own right but tend to follow versus lead. Splunk is definitely a leader in the field.
We reviewed a number of different platforms and found Splunk to be the more mature product across the board. Splunk is the market leader and the rest of the industry chances them. We needed a platform from a company with the resources to continue development and meet new …
Splunk offers a simple out of the box setup. The enterprise installation was completed in less than four hours. Pricing for Splunk is high, but the benefits far out way the price impact. Other tools were good but did not offer the various types of integration. Support for the …
Apart from cost, Splunk overcomes and supersedes all other products considering all the features and user experience. Splunk is fast as compared to other products. The results shown in the form of various types of graphs are really helpful while doing comparison with other …
Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
I'm liking the newer products, and I'm looking forward to how they integrate with the overall product when they come together. Just log in and be able to query a large number of systems for similar issues or a unique one. That is a great fit for Splunk Enterprise, looking for a simple case or a simple String or something of that nature across multiple machines. It's a great fit for that to identify issues or particular software, whatever your scenario is, String, to find it across any particular server or group of servers, so that you can update or do a deployment or whatever it is you're looking to do.
Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
We are using Splunk extensively in our projects and we have recently upgraded to Splunk version 6.0 which is quite efficient and giving expected results. We keep track of updates and new features Splunk introduces periodically and try to introduce those features in our day to day activities for improvement in our reporting system and other tasks.
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
You can literally throw in a single word into Splunk and it will pull back all instances of that word across all of your logs for the time span you select (provided you have permission to see that data). We have several users who have taken a few of the free courses from Splunk that are able to pull data out of it everyday with little help at all.
Splunk maintains a well resourced support system that has been consistent since we purchased the product. They help out in a timely manner and provide expert level information as needed. We typically open cases online and communicate when possible via e-mail and are able to resolve most issues with that method.
The online course was simple clear and described the main capabilities of the solution. There is also an initial module that can be done for free so anyone can familiarize themselves with the functionality of this solution. On the other hand, however, there could be more free online courses. Maybe even with a certificate, this would broaden the group of people who are familiar with the platform while increasing familiarity with the solution itself.
Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various searching systems such as Solr or Graylog, or even monitoring solutions built on top of Graphite or OpenTSDB.
A lot of products have natively inside their own dashboards and or their own logging repositories. And each one is difficult to learn or they're too complex or they're not verbose in the sense that they're not easy to mine the data that you're looking for. So that could be anything from the native logging that you find in other Cisco products. It's easier to use Splunk to draw the data that you're looking for as opposed to going to the individual's products themselves to get the logs that you're looking for.
Positive: LogStash is OpenSource. While this should not be directly construed as Free, it's a great start towards Free. OpenSource means that while it's free to download, there are no regular patch schedules, no support from a company, no engineer you can get on the phone / email to solve a problem. You are your own Engineer. You are your own Phone Call. You are your own ticketing system.
Negative: Since Logstash's features are so extensive, you will often find yourself saying "I can just solve this problem better going further down / up the Stack!". This is not a BAD quality, necessarily and it really only depends on what Your Project's Aim is.
Positive: LogStash is a dream to configure and run. A few hours of work, and you are on your way to collecting and shipping logs to their required addresses!
Splunk has allowed developers to diagnose production issues when access of control was taken away from them to be allowed to view items in production environments and I believe that is invaluable.
At times some developers weren't super happy about using it, but it was more of the fact that they were used to having production access and not creating their splunk queries to get information.
Going one place to view logs was very beneficial to have.
