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Don't run production workloads without Elastic's observability stack
What do you like best about the product?
Elasticsearch's stack is a must-have for application developers where observability can be achieved through APM's distributed tracing, and logs and metrics acquired through the Elastic Agent. A lot of observability into the system can be seen with minimal application configuration so developers can understand latency, throughput, error rate, and saturation of the system. I wouldn't run a production service without Elastic. I use APM every day to monitor the health of services I'm responsible for. A lot of valuable information comes for-free, but creating custom dashboards is also available.
What do you dislike about the product?
Setting up Elasticsearch and running it for production workloads is non-trivial. Many valuable features require a commercial license.
What problems is the product solving and how is that benefiting you?
Elasticsearch provides observability solutions where keeping applications running in a healthy state is critical. Tools within Elastic like Transforms can create views/dashboards that power decision making.
Scalable, Reliable, and Insightful Platform for Search and Observability
What do you like best about the product?
As a Lead Solutions Architect, I've worked extensively with Elastic over the past few years, and it has become a cornerstone of our infrastructure. From log aggregation to real-time analytics and observability, Elastic consistently delivers high performance and flexibility.
We use Elasticsearch to power dashboards that process large volumes of data from various sources, including MySQL and Elastic Search itself. The ability to create custom indexes, mappings, and use REST APIs like Bulk and Multi Get has made our data ingestion and retrieval seamless. The platform’s support for metrics and aggregations has helped us build meaningful visualizations and improve operational decision-making.
Elastic’s integration with cloud platforms like Azure and AWS has been smooth. We've deployed Elastic Stack in production environments and leveraged its capabilities for distributed search, logging via Logstash, and visualization through Kibana. The training materials and internal documentation have been instrumental in onboarding new team members and scaling our usage.
What stands out most is Elastic’s commitment to innovation. Their recent push into Search AI and generative AI-powered applications, as highlighted in Elastic{ON} events , shows they’re not just keeping up—they’re leading.
Pros:
Powerful search capabilities with support for vector and semantic search
Scalable architecture for large datasets
Seamless integration with cloud and container platforms
Excellent visualization tools via Kibana
Strong community and documentation
Cons:
Initial setup and tuning can be complex for new users
Licensing and pricing models could be more transparent
We use Elasticsearch to power dashboards that process large volumes of data from various sources, including MySQL and Elastic Search itself. The ability to create custom indexes, mappings, and use REST APIs like Bulk and Multi Get has made our data ingestion and retrieval seamless. The platform’s support for metrics and aggregations has helped us build meaningful visualizations and improve operational decision-making.
Elastic’s integration with cloud platforms like Azure and AWS has been smooth. We've deployed Elastic Stack in production environments and leveraged its capabilities for distributed search, logging via Logstash, and visualization through Kibana. The training materials and internal documentation have been instrumental in onboarding new team members and scaling our usage.
What stands out most is Elastic’s commitment to innovation. Their recent push into Search AI and generative AI-powered applications, as highlighted in Elastic{ON} events , shows they’re not just keeping up—they’re leading.
Pros:
Powerful search capabilities with support for vector and semantic search
Scalable architecture for large datasets
Seamless integration with cloud and container platforms
Excellent visualization tools via Kibana
Strong community and documentation
Cons:
Initial setup and tuning can be complex for new users
Licensing and pricing models could be more transparent
What do you dislike about the product?
Cons:
Initial setup and tuning can be complex for new users
Licensing and pricing models could be more transparent
Initial setup and tuning can be complex for new users
Licensing and pricing models could be more transparent
What problems is the product solving and how is that benefiting you?
Faster Incident Response
You can quickly search logs and metrics to identify and resolve issues—minimizing downtime and improving MTTR (Mean Time to Recovery) .
Enhanced System Reliability
By leveraging Elasticsearch’s real-time capabilities and redundancy planning, you ensure that services remain available and performant even under stress .
Cost-Efficient Operations
Tools like LogsDB and Elastic Cloud Serverless reduce operational overhead and hidden costs, allowing you to store more data affordably while maintaining visibility.
Smarter Automation
Elasticsearch integrates well with automation pipelines (e.g., Logstash, Kibana), enabling you to automate routine tasks like log parsing, alerting, and dashboard generation.
Future-Proofing with AI
Elastic’s innovations in Search AI and GenAI observability empower you to monitor and optimize AI workloads, which is increasingly relevant in modern SRE practices.
You can quickly search logs and metrics to identify and resolve issues—minimizing downtime and improving MTTR (Mean Time to Recovery) .
Enhanced System Reliability
By leveraging Elasticsearch’s real-time capabilities and redundancy planning, you ensure that services remain available and performant even under stress .
Cost-Efficient Operations
Tools like LogsDB and Elastic Cloud Serverless reduce operational overhead and hidden costs, allowing you to store more data affordably while maintaining visibility.
Smarter Automation
Elasticsearch integrates well with automation pipelines (e.g., Logstash, Kibana), enabling you to automate routine tasks like log parsing, alerting, and dashboard generation.
Future-Proofing with AI
Elastic’s innovations in Search AI and GenAI observability empower you to monitor and optimize AI workloads, which is increasingly relevant in modern SRE practices.
Scalable & Reliable Solution to Search & Analyze Data
What do you like best about the product?
Support structure and non-structure data. Easy to use and build dashboard. Very scalable. Excellent customer support. Really easy to be integrated with our software tools.
What do you dislike about the product?
I hope I could have more time to catch up with the new features.
What problems is the product solving and how is that benefiting you?
We have large amount of monitoring data that are stored in Elasticsearch database, and we need to build Kibana dashboard with those data. With the integrated solution of ELK that comes with Elasticsearch, it is so easy to collect the data, to do search, to build the dashboard, to create the alerts, and integrate with our own systems for ticketing. We are truly grateful with the features Elasticsearch provides.
Elastic gives you freedoms to create the solution you need
What do you like best about the product?
Elastic has a great community and support that can be talked to and used in order to create and implement solutions. their are a plethera of prebuilt features in the platform such as the security solution that you can leverage and integrate with other platforms in order to create the solution that you need. I am in elastic every day and am able to create and monitor the solutions i need easily in order to perform my job.
What do you dislike about the product?
With Elastic their are many features and some of which start to feel the same but with a different spin. due to the pure amount of features sometimes it appears that something isnt possible but it is you just used the wrong method at the start and now have to go back and change some items around in ingest as an example in order to make it possible. Theirs no 1 way of doing things which sometimes makes it complicated as you know it may be able to be done but you just didnt pick the correct method.
What problems is the product solving and how is that benefiting you?
Elastic is making it easy to search documents and find the information you are looking for. With elasticsearch i am able to search for my documents and find them really easily as well as in a very quick manner. Elastic makes it easy to find data. Elastic also has a good amount of security audit logs that can be used in order to track what is occuring within the instance and monitor to ensure everything is working as intended.
Smooth and Easy to setup
What do you like best about the product?
Pretty easy to install and implement on openshift clusters and also provides quick search on the documents ingested
What do you dislike about the product?
As we are using it for a specific purpose, we are not experiencing any issues as of now.
What problems is the product solving and how is that benefiting you?
Searching through the documents and providing the quick response on the requested data.
Elastic for Security
What do you like best about the product?
The ease of implementation for the entire stack has been the greatest asset of our deployment. The amount of integrations and ability to get data from a lot of locations has been great.
What do you dislike about the product?
Support has been an issue for me lately, I have had to repeat my statements numerous times in cases instead of just reading what was posted. I can't fault 100% elastic as I have had similar issues with other companies as well.
What problems is the product solving and how is that benefiting you?
Solution has provided us a SIEM at a Costpoint that didn't break the bank.
I love Elasticsearch
What do you like best about the product?
I enjoy the comprehensive underlying architecture that Elasticsearch is built on, it's easy to integrate into just about any environment, easy to implement the various capabilities, maintain, and use but difficult enough to master.
What do you dislike about the product?
I don't find anything particularly to dislike, there are things I do not currently utilize(ML) but absolutely plan to incorporate in future deployments.
What problems is the product solving and how is that benefiting you?
Elasticsearch helps my company solve enterprise cyber security analysis.
Love the company.
What do you like best about the product?
Turnaround time, respectful communication.
What do you dislike about the product?
Products aren't always fulfilled. Could provide a more widespread option.
What problems is the product solving and how is that benefiting you?
Log monitoring
Great logging and SIEM platform
What do you like best about the product?
Speed of search. Security features. AI. Dashboards.
What do you dislike about the product?
Support has became less helpful. Cost is high. Many features are buggy at times.
What problems is the product solving and how is that benefiting you?
PCI compliance retention. SIEM. Dashboards. Historical searching.
Senior Software Engineer
What do you like best about the product?
Data ingestion, Dashboards, Snapshots (Frozen Tier)
What do you dislike about the product?
Kibana could be better in of pagination, remembering number of lines selected, instead of defaulting to 25 lines
What problems is the product solving and how is that benefiting you?
We currently have many use cases, like ingesting data from our Banking app which is then used for 3rd level support, customer queries, fraud detection, audit logs, system metrics and monitoring
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