Elasticsearch vs. Logstash vs. Sumo Logic

Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.

Incentivized

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

• As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
• Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
• Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.

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

• Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
• Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
• Schema changes require complete reindexing of an index

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

• 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

We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.

Incentivized

To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.

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

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

We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.

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

Do not mix data and master roles. Dedicate at least 3 nodes just for Master

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

As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.

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

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.

• We have had great luck with implementing Elasticsearch for our search and analytics use cases.
• While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
• We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.

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

• 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