Logstash vs. Logz.io

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).

Incentivized

Logz.io is an effective solution if your alerting needs are fairly straightforward and you don't need long-term retention of logs with easy access. If being able to maintain easy access to logs longer than this is necessary, another solution might be better. If you need a high degree of precision with alerting triggers and the ability to suppress alerts, you will need to combine Logz.io with an integration to get this or you might consider a different solution.

Incentivized

• 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.

Incentivized

• Well documented and easy to set up.
• Their alerting mechanism is really great especially when it comes to application monitoring.
• Our data analysis in Kibana is made easy with the solution for Logz.io.
• The issue checking and fixing is escalated quickly and is reported in time.

Incentivized

• It is heavy i.e., intensive as of now. Need to reduce overhead to save CPU/RAM consumption
• Need to be more Kubernetes-friendly. Should support auto-scaling and K8s observability
• Initial configuration is still complex. A seamless config procedure is still required

• Its price can be very high, so you should have good control of it to avoid exaggerated figures.
• Some functions can be confusing.
• It has limits to create subaccounts, which is a big problem for large companies.

Incentivized

Really easy to use and ship the logs Good customer support Easy integration with the modules

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

I initially struggled trying to ensure the correct data was returned in the Kibana search, but I found it overall easy to use. Some of the UI is not as seamless as I'd expect, like changing the environment completely resets your search criteria and filters, which is annoying since it's a common use case to search something in multiple environments

Incentivized

Their support team is the best in the world! They supported us in most of the critical times and helped to resolve the issue in real time. Also their email support is well maintained and never a mail is missed unanswered. Kudos to the support team of logz.io for maintaining professionalism.

Incentivized

Implementation of logzio is easy. Exporting the logs with filebeat agent is our main key source.

Incentivized

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.

Incentivized

Logz.io is more affordable, less work to maintain, and has more features. It was an easy choice. After my last team had to manage their own ELK stack, this was a no brainer. It helps us be focused on our core competencies.

Incentivized

• 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!

Incentivized

• about the investment, this tool is helping in our day to day activities
• easy to troubleshoot the errors
• simple and powerful

Incentivized