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 …
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
