Elastic Observability vs. StackState

We can use this Elastic Observability in our business problems such as Creating internal/operational efficiencies issues, customer relations/service, and business process outcomes issues. This product has a lot of features for the above problems. But this product may be having some issues when charting purposes. But it can adjust for that purpose.

Incentivized

StackState is suitable for 1000+ hosts. Sometimes specific applications can take higher development time. Well suited for hybrid platforms to build end to end service alarms and service views. Advanced UI navigation might require some training. It is not a simple download and deploy software. It will require development in an agile model. Where newer versions are deployed to suit exact client requirements. Support contract with the StackState Engineer for development of use-cases is required and very useful.

• Open source code base
• Community support
• Is fast in processing

Incentivized

• Giving observability of the entire IT stack
• Custom alerting options.
• Ingesting many different types of data.
• Requesting new features is encouraged and they often add them quite quickly.

• Difficult to setup/maintain
• Search pattern bar could be more user-friendly
• Premium subscription features are very expensive

Incentivized

• Can't think of anything yet.

Some elements of the product haven't had the usability upgrade yet and can be a bit technical. This is to be expected as they are trying to solve complex problems. I am sure that in the future, steps will be made to simplify this as well for the users / administrators / developers of the platform.

It's swift, they're thinking along with us. It's a "collaboration approach" rather than a (traditional) customer-supplier relation. Out new ideas are taken in concern and often ends up in enhancements of StackState

Splunk is a very good product but the licensing costs are high; we utilise the best of both worlds by using both products for slightly different purposes. We put the voluminous data with simple use cases in Elastic where it doesn't cost too much and can be searched quickly while putting the less voluminous data with more complex use cases in Splunk so we can take advantage of Splunk's very comprehensive but often much slower SPL search query language

Incentivized

• Cost management.
• Good customer increment.
• Time management.

Incentivized

• Increased visibility of all resources in cloud to 100%.
• Deviated stages are able to detect problems before their occurrence. However, [it] needs tunings for false alarms.