Sold by: Solve DevOps
Deployed on AWS
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This product has charges associated with it for seller support. Latest Elasticsearch 9.1.1 pre-configured on Ubuntu 24.04. Enterprise search, real-time analytics, and observability in one powerful platform. Deploy in minutes.
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Overview
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Elasticsearch Login
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Elasticsearch Welcome
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Elasticsearch Dashboard
This is a repackaged open source software product wherein additional charges apply for support with guaranteed 24/7 availability. Transform your data into actionable insights with Elasticsearch 9.1.1, the world's most popular enterprise search and analytics engine. This production-ready AMI combines the latest Elasticsearch with Ubuntu, delivering a secure, scalable, and high-performance search platform.
What is Elasticsearch?
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. It provides:
- Lightning-Fast Search: Millisecond response times across billions of documents
- Real-Time Analytics: Analyze data as it arrives with near-instant results
- Scalable Architecture: Grow from a single node to hundreds seamlessly
- RESTful API: Simple JSON-based interface for all operations
- Full-Text Search: Advanced querying with relevance scoring
Why This Image?
- Latest Version: Elasticsearch 9.1.1 with all security patches
- Production Optimized: JVM tuned, heap sized, and kernel parameters set
- Security First: X-Pack security enabled with TLS/SSL ready
- Ubuntu 24.04 LTS: 5-year support with latest performance improvements
- Quick Start: Pre-configured and ready to index in under 5 minutes
Features:
- AWS-Optimized Performance: Elasticsearch 9.1.1 configured for AWS VMs with Premium SSD support, accelerated networking, and availability zone awareness
- Enterprise Search Platform: Power intelligent search across AWS services and custom applications with millisecond response times
- Unified Analytics Engine: Combine logs, metrics, and traces from AWS CloudFormation, applications, and infrastructure in one scalable platform
Real-World Use Cases:
Enterprise Search:
- Power intelligent search across:
- E-commerce product catalogs
- Knowledge bases and documentation
- Internal company data and wikis
- Legal document repositories
- Media and content libraries
Log Analytics & Observability:
- Monitor and analyze:
- Application logs and errors
- Infrastructure metrics
- Security events and threats
- User behavior and clickstreams
- IoT sensor data
Business Analytics:
- Drive insights from:
- Customer behavior patterns
- Sales and revenue metrics
- Inventory and supply chain data
- Marketing campaign performance
- Real-time dashboards
Industry-Specific Solutions:
Healthcare: Patient record search, clinical trial matching, research papers Finance: Fraud detection, transaction monitoring, compliance reporting Retail: Product recommendations, inventory search, price monitoring Media: Content discovery, metadata search, audience analytics Government: Public record search, case management, citizen services
Getting Started:
Launch Instance:
- Choose instance type (recommended: 4GB RAM, 2 CPU)
- Configure security group (ports 5601, 9200, 9300)
- Launch with your key pair
First-time Configuration
- Access your instance over SSH to view first-time configuration instructions.
- Access Elasticsearch ssh -i your-key.pem ubuntu@your-instance-ip
Quick Commands:
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Check cluster health: curl -X GET "localhost:9200/_cluster/health?pretty"
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Check version: curl -X GET "localhost:9200"
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Create an index: curl -X PUT "localhost:9200/products"
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Index a document: curl -X POST "localhost:9200/products/_doc" -H 'Content-Type: application/json' -d' { "name": "Laptop", "price": 999.99, "description": "High-performance laptop with SSD" }'
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Search: curl -X GET "localhost:9200/products/_search?q=laptop"
Ready to power your search and analytics? Click "Continue to Subscribe" to get started.
Highlights
- AWS-Optimized Performance: Elasticsearch 9.1.1 configured for AWS VMs with Premium SSD support, accelerated networking, and availability zone awareness.
- Enterprise Search Platform: Power intelligent search across AWS services and custom applications with millisecond response times.
- Unified Analytics Engine: Combine logs, metrics, and traces from AWS CloudFormation, applications, and infrastructure in one scalable platform.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
t3.large Recommended | $0.0068 |
c5.metal | $0.0068 |
t2.large | $0.0068 |
m5.24xlarge | $0.0068 |
m4.xlarge | $0.0068 |
m5.12xlarge | $0.0068 |
m4.10xlarge | $0.0068 |
m5.xlarge | $0.0068 |
m5.2xlarge | $0.0068 |
m4.16xlarge | $0.0068 |
Dimensions summary
You pay by the hour for the software running on your chosen EC2 instance type. The 38 dimensions map directly to AWS instance sizes across the t2, t3, c4, c5, m4, and m5 families. Each family targets a different balance of compute, memory, and general-purpose use. Within a family, larger sizes carry more CPU and memory and bill at a higher hourly rate. You are not committing to a fixed term. Pick the instance that fits your workload, and your cost scales with the size and hours you run.
Top-of-mind questions for buyers
You pay one hourly software rate for each running instance of the analytics stack. The rate is tied to the EC2 instance type you launch. Larger instance sizes carry more CPU and memory and bill at higher hourly rates. Billing counts each hour the instance runs.
The hourly software charge applies only while the instance runs. A fully stopped instance does not accrue the software rate. Stopped instances may still incur AWS storage fees for attached volumes, but those are separate from this listing's per-hour software charge.
You get an Elasticsearch and Kibana analytics stack built from open-source components, packaged as a cloud image. Support is provided at the vendor's discretion. Updates and patches are supplied as available. The software runs on the EC2 instance family and size you select.
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Vendor refund policy
Cancel Anytime.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Updates to the latest Security Patches for Elasticsearch, Kibana and Ubuntu
Additional details
Usage instructions
Getting Started:
- Provision an EC2 instance with the right capacity for your needs. For smaller installations we suggest; t3.medium.
- Access your Server using the IP Address issued by AWS for the initial setup. Default Username: ubuntu
- Instructions on how to get Kibana token are available on first SSH access.
- Enjoy the Power of Ubuntu.
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Esse Wognin
Data analysis has improved and reporting now tracks live business performance and resolution time
Reviewed on Apr 11, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Solve DevOps Elasticsearch and Kibana is using Kibana to pull reports, do data analysis, and track and monitor data about the business we are doing currently, as Kibana provides us with live data, and we can see how the transactions are doing.
I use Kibana for data analysis because it has a database of transactions that happened in the past or even today. For example, if today I want to review how one business that we are supporting is currently doing, I will pull out a report with specific items that I want to see on that report.
Something that I love about Kibana is that every analysis I run can be saved, allowing me to look at the transactions performance or the success rate and also those I can use to look at the fail rate. When I want to analyze something, I just have to change the name of the business.
What is most valuable?
The best features of Solve DevOps Elasticsearch and Kibana, in my opinion, include the graph, which I find very useful.
What I appreciate most about the graphs in Solve DevOps Elasticsearch and Kibana is the visualization, which is very easy for even someone who is a beginner in data analysis to use, and the customization also helps in making my work seamless.
Another aspect I forgot to mention about Solve DevOps Elasticsearch and Kibana is the AI Assistant, which is very good for assisting with data indexing, analyzing APIs, generating sample datasets, creating visualizations, and troubleshooting errors.
Solve DevOps Elasticsearch and Kibana has positively impacted our organization by improving our full-time resolution time and SLA, because it supports me in troubleshooting and handling reconciliation issues effectively.
Since I started using Kibana, I can say that it has improved our relationship with our partner because we are able to provide a solution in less than an hour with troubleshooting and data visualization, maintaining our SLA at 90% and ensuring customer satisfaction remains at 100%.
What needs improvement?
Regarding improvements for Solve DevOps Elasticsearch and Kibana, I feel that the full service of the AI Assistant could be available on the free version, and I think it would be beneficial to have tutorials to help users navigate the application.
I recommend that the application be made more intuitive and user-friendly, as I found it confusing the first time I was using it, and improvements in the user experience would help beginners.
For how long have I used the solution?
I have been working in my current field since 2022, as I joined the company in October 2022, and I am still working there until now.
What do I think about the stability of the solution?
Solve DevOps Elasticsearch and Kibana is very stable, and I can access it at any time of the day, with the support team always responsive whenever I need assistance.
What do I think about the scalability of the solution?
In terms of scalability, Solve DevOps Elasticsearch and Kibana can handle a large set of data very efficiently, and I would rate it a nine because it supports simultaneous access for multiple users analyzing different datasets.
How are customer service and support?
The customer support for Solve DevOps Elasticsearch and Kibana is perfect; they are always available and respond promptly whenever I reach out.
I would rate the customer support an 8 out of 10.
Which solution did I use previously and why did I switch?
Previously, I used advanced Excel, but I found it to be very limited, as Kibana has made it easier for me to analyze large sets of data with just a few clicks to get the graphs and visualizations I need.
What was our ROI?
I can see a huge return on investment with Kibana, as it saves time and money by eliminating the need to hire more people due to its ability to efficiently handle data analysis.
Which other solutions did I evaluate?
My company decided to provide us with Solve DevOps Elasticsearch and Kibana, so I did not evaluate any other options before choosing it.
What other advice do I have?
I would advise others looking into using Solve DevOps Elasticsearch and Kibana to go for it, as it has significantly improved our working conditions by saving time and effort and is easy to use, making it possible to train new users easily to become data analysts. I would give this product an overall rating of 8 out of 10.