Logstash vs. Sumo Logic

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

SumoLogic is a fantastic log aggregator and analysis tool, a fine alternative to Splunk. Searching is powerful and mostly intuitive and results come fast. If you have application logs in clusters or Kubernetes pods that lose their logs every time they're restarted, Sumo is the solution for you

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

• Sumo Logic allowed for our InfoSec team to ingest logs from our CDN directly, in real-time, instead of massive compressed archives that were sent every two-hours (the only alternative at the time). Sumo Logic had an app for these logs, that allowed us to easily get an immediate payoff from the data, with canned dashboard and saved searches.
• Sumo Logic has a fairly extensive REST API when it comes to log sources, source configurations, dashboard data, searches, etc. Their wiki for the API is usually kept up to date.
• Sumo Logic, during the period of time I had used their product, had added the ability to configure agents via configuration files. This allowed customers to configure their endpoints, and modify the endpoints, with configuration management tools like Chef / Puppet / Salt. Beforehand, the only option was to always make changes either via the web portal or REST API.
• The solutions engineers were extremely helpful, and easily reachable when issues would occur.
• Users at our company found it easy to get started, working on new dashboards, scheduled searches, and alerting. The alerting worked well with our third-party paging tool.

Incentivized

• Since it's a Java product, JVM tuning must be done for handling high-load.
• The persistent queue feature is nice, but I feel like most companies would want to use Kafka as a general storage location for persistent messages for all consumers to use. Using some pipeline of "Kafka input -> filter plugins -> Kafka output" seems like a good solution for data enrichment without needing to maintain a custom Kafka consumer to accomplish a similar feature.
• I would like to see more documentation around creating a distributed Logstash cluster because I imagine for high ingestion use cases, that would be necessary.

Incentivized

• I like the help center, but I think if it had more GUI tools, it could help new users.
• Pulling out data is sometimes hard to read, (Maybe if I knew how to export data better, this would not be an issue for me).
• I would like better know-how on how to create reports that will help our business.

Incentivized

Sumo Logic is very powerful but definitely requires some configuration work to get the most out of it. You can get a certification related to this, but it is definitely not something you can just throw together.

Incentivized

I would give this rating because I attended a free Sumo Logic training at a WeWork in Chicago. I found the training very useful, and I learned a lot of features that I was not aware of before I went to the training. I like the idea that SumoLogic provides free training seminars. I am certified in level1, and I plan on certifying to level2.

Incentivized

I was satisfied with the implementation, as at the time, it was the best way to implement the product with the available feature sets in Sumo Logic. User creation and management became more of an issue during continued use, instead of it being an issue related to deploying the product in our environment.

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

Sumo Logic works very well out of the gate. For a small business it has given us what we need. I worked at a larger company previously, and we produced so many logs we had to create a custom logging service to handle them all. Cost and availability are big issues when deciding between the different services, whether self maintained and hosted, or provided by another company.

Incentivized

I've assisted several OneLogin customers with partner accounts to Sumo Logic. It has always been pleasant.

• Positive: Learning curve was relatively easy for our team. We were up and running within a sprint.
• Positive: Managing Logstash has generally been easy. We configure it, and usually, don't have to worry about misbehavior.
• Negative: Updating/Rehydrating Logstash servers have been little challenging. We sometimes even loose data while Logstash is down. It requires more in-depth research and experiments to figure the fine-grained details.
• Negative: This is now one more application/skill/server to manage. Like any other servers, it requires proper grooming or else you will get in trouble. This is also a single point of failure which can have the ability to make other servers useless if it is not running.

Incentivized

• I can't think of any negative side effects other than it being SO slow sometimes, but compared to Splunk everything is slow
• It's SO much cheaper than Splunk that the time it takes to query information is well worth it
• In the times that we've had Sumo go down or stop logging information, we've found that we'd be absolutely lost without Sumo

Incentivized