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Unlocking the Power of Data with Fast Search and Analytics
What do you like best about the product?
1. Near real-time search
2. Hugh Scalability
3. In our scenario, it helps us to centralize logs and metrics from different systems into one searchable platform, helping our IT ops and security teams troubleshoot issues quickly.
4. It supports full-text search, filters, geospatial queries, and many more, all in the same engine.
2. Hugh Scalability
3. In our scenario, it helps us to centralize logs and metrics from different systems into one searchable platform, helping our IT ops and security teams troubleshoot issues quickly.
4. It supports full-text search, filters, geospatial queries, and many more, all in the same engine.
What do you dislike about the product?
1. High resource usage - It is high CPU and memory hungry product.
2. It is quite expensive and complex to manage at scale
2. It is quite expensive and complex to manage at scale
What problems is the product solving and how is that benefiting you?
1. It collects logs, metrics, and traces from apps, servers, firewalls, etc. into one platform.
2. It provides real-Time Analytics
3. Root cause analysis in minutes, doesn't take hours/days.
4. Centralized SIEM-like function for threat visibility.
5. Can handle increasing data from Yotta’s hyperscale environment.
6. Elasticsearch turns raw data into actionable insights in real-time — helping us run, secure, and scale our datacenter operations with speed and confidence
2. It provides real-Time Analytics
3. Root cause analysis in minutes, doesn't take hours/days.
4. Centralized SIEM-like function for threat visibility.
5. Can handle increasing data from Yotta’s hyperscale environment.
6. Elasticsearch turns raw data into actionable insights in real-time — helping us run, secure, and scale our datacenter operations with speed and confidence
My Experience with Elasticsearch
What do you like best about the product?
Elasticsearch is awesome for fast and flexible search. It’s great at handling huge amounts of data and giving near-instant results. You can search, filter, and analyze text, numbers, logs pretty much anything. It’s super helpful for building search engines, monitoring systems, and real-time dashboards. Speed, scalability, and powerful full-text search.
What do you dislike about the product?
Elasticsearch is powerful but not always easy. It can throw errors that are hard to trace, especially with complex queries. Setup and scaling take effort, it uses a lot of resources, and security features are limited unless you pay.
What problems is the product solving and how is that benefiting you?
Elasticsearch helps spot errors and inaccurate X-ray details quickly. It makes it easy to track which technologist used single, double, or triple exposures. The data is searchable and organized, so issues and patterns are easier to find and fix.
Elasticsearch for Observability
What do you like best about the product?
We run Elastic on Kubernetes and have run up to 20 separate elastic clusters throughout the world. Three years ago we invested in the ECK operator and consolidated 9 of those elastic clusters down to 3. ECK has increased our confidence to run fewer, larger environments with multiple node pools and greater flexibility.
What do you dislike about the product?
Elasticsearch can be a bear to tune for performance, at scale, on a budget. Like any database, it's resource hungry. Additionally, the company has work to do to keep up with modern-day vulnerability management practices and remediation schedules.
What problems is the product solving and how is that benefiting you?
As a platform team, we deploy self-hosted Elastic in multiple configurations: vector search, observability, SIEM, and unstructured document storage.
AI Logging Power House
What do you like best about the product?
The bulk logging features and an ability to index, store and search data with ease
What do you dislike about the product?
Complexities involved in having ready out of the box solution for deep dive Observability and log based metrics and insights.
What problems is the product solving and how is that benefiting you?
A single Logging Repository store for IOT workloads and thousands of stateless infra elements used in our product architecture.
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.
Nice product
What do you like best about the product?
Easy of use, reliable and good customer support
What do you dislike about the product?
Dashboard with using big index takes time to load
What problems is the product solving and how is that benefiting you?
Showing visualization from the data
Elasticsearch – Fast, Flexible, but Needs Care
What do you like best about the product?
I’ve been using Elasticsearch for a while now, and the first thing that consistently impresses me is its speed. No matter if I’m searching through logs, text, or analytics data, it delivers results incredibly quickly once it’s properly configured. I also like how well it scales; adding more nodes allows it to handle larger and larger workloads smoothly.
I also appreciate its flexibility. Elasticsearch supports everything from simple keyword searches to more advanced aggregations, autocomplete, and even fuzzy matching.
I also appreciate its flexibility. Elasticsearch supports everything from simple keyword searches to more advanced aggregations, autocomplete, and even fuzzy matching.
What do you dislike about the product?
Elasticsearch is not particularly plug-and-play. There is a noticeable learning curve, especially when it comes to configuring clusters, tuning shards and replicas, and maintaining stable performance as your data volume increases. If you don't size your setup correctly, it can also become quite resource-intensive.
What problems is the product solving and how is that benefiting you?
I mainly use Elasticsearch as an enterprise search tool. It’s where we send a ton of data — logs, records, documents — so people can quickly find what they’re looking for. Instead of digging through raw databases, we can just search and get results instantly.
Before Elasticsearch, searching across big datasets was slow and frustrating. Now it’s basically instant. It handles millions of records without breaking a sweat, and the results are super accurate.
The biggest win for us is speed and scale — things that used to take forever now take seconds. That means faster troubleshooting, better insights, and less wasted time for the team. It just makes working with large amounts of data way more practical.
Before Elasticsearch, searching across big datasets was slow and frustrating. Now it’s basically instant. It handles millions of records without breaking a sweat, and the results are super accurate.
The biggest win for us is speed and scale — things that used to take forever now take seconds. That means faster troubleshooting, better insights, and less wasted time for the team. It just makes working with large amounts of data way more practical.
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.
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