We are fully satisfied with the usage and support, rating it 8 out of 10. I recommend NGINX for managing traffic due to its multiple functionalities like load balancing, proxy management, and caching.

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My advice to anyone who is evaluating Elastic Search is to explore the user-friendly website and navigate to the documentation or resources section. Start with a basic overview of the components, and how they work together, and try simple tasks like searching or detecting. The key is to begin with something straightforward. Utilize the documentation to understand how to get started and explore the various integrations Elastic Search offers. Overall, I would rate it as an eight out of ten.

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Overall, I would rate the solution a seven out of ten. The free version is not very useful.

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The main reason we opted for it is because the installation is straightforward, and maintenance is made easy as they handle that aspect for you. The extensive knowledge base offers substantial assistance, making it less reliant on individual expertise. I believe it's a solid product, especially for beginners. While it's not free, it's well-suited for more complex tasks. Keep in mind that for intricate functionalities, you might need to develop and create tools beyond what Elastic Cloud offers. If you're considering a cloud-based solution for schema-less documents, Elasticsearch is a solid choice. On the other hand, if you have the resources to handle on-premises installation, I would recommend it for companies with the capability to manage the deployment themselves. Overall, I would rate it eight out of ten.

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If you're interested in using Elasticsearch as a search tool and for cloud data integration, comparing it with alternatives like Amazon Cloud Search or Azure Search is valid. Many cloud service providers that offer text-search services are utilizing Elasticsearch. They've implemented best practices and resolved a myriad of issues experienced by companies using Azure, AWS, or GCP. 

These providers have integrated Elasticsearch into their cloud offerings effectively. Choosing their services might be preferable due to lower operational costs on your side. 

In case of any disaster or issue, their development and DevOps teams are available to support you. However, if you face limitations, like client requirements prohibiting data storage in public or private clouds, then deploying Elasticsearch on-premises would be your alternative.

I would definitely rate it an eight out of ten,  which is very good. The reason is the active community continuously working on it, and the support from contributors and the support team is notable. Because Elasticsearch is very specific in its use cases. 

It excels in text-based search and creating dashboards for application logs. It provides results and functionality that are hard to find in alternative tools. So, if you have a use case that fits, Elasticsearch is a great service without any direct alternatives.

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We are a customer.

I'm not sure which version we're using. I'm from the development team. The people who are doing the configuring work would know the version.

I'd rate the solution seven out of ten. It is a good solution, yet not quite perfect.

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I'm using the latest version of the solution. I started with version 7.1, and now I use 8.6.

I'd recommend the solution to other users. 

I'd rate the solution nine out of ten. The features and tools are overall very good. 

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I would rate it a nine out of ten for now. It has a lot of features compared to other solutions. Its comprehensiveness and range of features are what make it stand out for application monitoring. I highly recommend it. It's very good because it's efficient, highly scalable, and has high availability. Additionally, cost-effectiveness is crucial in Nigeria due to exchange rates. Organizations need solutions that are affordable, and Elasticsearch fits the bill. I would absolutely recommend it to any organization. View full review »

When using the solution, it is important to understanding indexing concepts and the proper way to search logs from a visualization point of view. These two items work together internally to produce logs that can be filtered to specifications. 

I rate the solution an eight out of ten. 

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I rate this solution a seven out of ten. Because it is open-source, there is no technical support provided by the vendor, so we are moving to enterprise subscriptions for each of these products. We are allowed free licenses and implement enterprise or commercial licenses and the production of protections.

An original criterion selects the software stack because they have to be good tools, but they all have to be open-source. Nobody considers it because the original team that started the project worked in an investigation organization and was closer to open-source software.

They are not clear regarding the support of their solution when they go into production. That's why we are updating the licenses to interpret license subscriptions and assume their support for each software component.

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Elastic Enterprise Search is an open-source solution.

I rate Elastic Enterprise Search a ten out of ten.

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I would recommend the solution to others. 

I'd rate the solution nine out of ten. 

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My advice to others is for them to make sure this solution satisfies their business needs because there are many solutions and providers, with a lot of options. There are solutions that have a lot of features that the business might not need and it is not good for the business to waste money on features not used. It was recommended by many peers not to seek many options in a solution that you are not going to use, and to concentrate on what is needed.

I rate Elastic Enterprise Search a seven out of ten.

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I rate Elastic Enterprise Search a nine out of ten.

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I'd rate the solution nine out of ten. 

I'm a customer and end-user. 

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I would rate the product a nine out of ten. 

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Logstash seems to have a very small capability to report errors, and that makes it difficult to troubleshoot. It would be nice to get some indication so as to save time.

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Try it out. There is little to lose but time.

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With the power of Kibana, we can easily and dynamically analyze and summarize our log data. The internet has information about all the technical solutions. I bought some courses from Udemy for Elastic Search. I also got some documents from Elastic Search. The documentation for Java is very good. It was sufficient to learn as a developer.

I could integrate my products to Elastic Search easily. I use the default index for my solution, and it works very well. Elastic’s indexing policies are very good. I do not need any indexed operations for my solution. Overall, I rate the tool a nine out of ten.

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We use the solution's live data analysis for operations purposes. The solution also has a monitoring aspect. ElasticSearch is like a middleman between the PRTG and ITSM tools. It is easier to pass the information about the metrics or the full logs of the cloud platform you are ingesting in the solution instead of giving the output to PRTG.

The solution is deployed on the cloud in our organization. Elastic Search is something that comes after the projects are done. After implementing the project, we use the solution to have that project monitored. I would recommend the solution to other users.

Overall, I rate the solution an eight out of ten.

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I'm just a customer and an end-user.

Our company is always using the latest updates.

I'd advise new users that you need to do a POC or get a test installation. It's free of charge. It's important to ingest a lot of data so that you get a feeling of scalability and performance. To put something in your lab, for example, is very helpful. It's only when you have data in the system, that you can see the benefits of the Elastic environment.

I would absolutely recommend the solution to others. I'd rate it at a nine out of ten. I've been pleased with its capabilities overall. 

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You can spin up Elastic ELK Elasticsearch fully-managed service either on AWS, GCP, or Azure, or have your own on-premises installation and dockerize it. Whereas the AWS Elasticsearch is available only on AWS. That's the hosting difference.

Elastic ELK Elasticsearch comes with a support-only subscription, and there are a lot of updates happening. Kibana is constantly improved and there’s a new release every two weeks.

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I would rate the product a nine out of ten. 

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One time, we had a remote customer who was complaining about response time, and we couldn't figure out where the problem was located. We created a small setup, just one node of Elastic Search, and we started using it to ingest the network traffic that was going from that customer to our main site. Once we started ingesting the network traffic, we saw exactly what the problem was. We were able to solve the problem, and it only took us an hour.

What sets this solution apart from its competitors is the innovation. For example, look at the number of releases they're doing. About every three to six months, you have a new release with new features, and it's great. The good thing is that even if you don't like the innovation, you still follow an upgrade line, which means you don't lose anything from the past. You just keep getting new stuff pumped into Elastic Search. As a result, it's becoming more like an overall operational solution, when before, it was just a place where you dumped your logs.

My advice to new users of this solution is to start with a specific use case that's a simple or complicated problem that you want to address. Start with that use case, address it straight away, and keep expanding. For example, we started with a network traffic use case, then expanded into Syslog management of a network device. Next, we expanded to an event management server, and then we went into application management. Now we are in security logs, and it keeps expanding.

I would rate this solution as a seven out of ten because there is still a lot missing regarding network management. Also, machine learning is still not clear to me. A lot of the things in machine learning can be addressed straight away with other features, like a watcher or alerting. At this point, I don't see the benefit of machine learning when it comes to IT infrastructure.

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For anyone considering implementing this solution, I would say take a good hard look at your own infrastructure resources and scalability as you have to future proof everything. Whether it's scale or increase in customers building up through your actual hardware and your network infrastructure. You need to know it's capable of performing the tasks needed, because sometimes you outgrow yourself. So, I would say look at your resources and how it can be scaled.

I would rate this solution a nine out of 10. 

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I would advise others to first know Linux because it would most probably be on Linux. If you're good at Linux, you will be good at this as well.

I would rate ELK Elasticsearch an eight out of ten.

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By integrating Deepgram insights with the product, we've gained visibility into logging, service behavior, and cost optimization.

I rate Elastic Search a nine out of ten.

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I would rate Elasticsearch as eight out of ten. 

Elasticsearch provides a lot of possibilities. You need to understand your requirements and how Elasticsearch can fulfill them. Somebody might be looking at a simple keyword service or attribute tagging. If you don't understand exactly what you're looking for, you'll get lost in their options and waste a lot of time.

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I rate the solution seven out of ten.

In cases where the memory of the nodes is exceeded, you will need to manually step in to delete some data, otherwise, the solution maintains itself automatically with little need for human intervention.

The forced merge and forced resonate features reduce the data size, increasing reliability.

The open source license is not enough when dealing with a large amount of data. The production license is required when you have larger requirements.

I recommend the solution to anyone who needs to integrate a lot of old systems into a data lake.

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The most important thing to keep in mind is that it is not as they advertise on their site. If you want to scale up and are looking for a big deployment, you must read everything. You also need support from the company itself. 

I would rate ELK Elasticsearch a seven out of ten.

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I rate Elastic Search an eight out of ten. You can use the product if you are looking for value for money. 

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It is a good choice, but you have to take your time to learn it. Its learning curve can be hard. 

I would rate it an eight out of 10.

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I'm just using it as a customer

We tend to use the latest versions of the solution. We try to upgrade it on a regular basis.

I'd advise other companies considering implementing the solution to get a team in that knows the product and try to take advantage of their knowledge. It will help reduce the pain of the learning curve.

I'd rate the solution eight out of ten.

I would not give it a ten because of the steep learning curve. I know what the product is, but many do not, and for them it will be quite difficult to get started without becoming very frustrated in the process. 

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Elastic Enterprise Search is a very good solution and they should keep doing good work.

I'm a very satisfied customer because almost everything I need comes out of the book. You already have machine learning, alerts, the ability to search, APIs, inbuilt security, and integration to third-party authentication.

I rate Elastic Enterprise Search a ten out of ten.

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I would tell potential users that they have to locate the data source and understand the data. They will have to decide on whether they have to go for a NoSQL or a relational database. 

If it's NoSQL, then what kind of data are you seeing? If it's more textual data, then you're going to read more. So, I would recommend Elasticsearch. Otherwise, you have other databases like MongoDB and Cassandra.

On a scale from one to ten, I would give ELK Elasticsearch a seven.

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The solution suits medium to large companies better. I rate it a nine out of ten. 

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The ELK open source stack is rich in features but lacks the essential security features.

ELK is one of the best open source alternatives for log management. If alerting and security features can be built by the team internally, on top of the stack, then the product is for sure going to add a lot of value to business.

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I would rate this solution 8 out of 10.

I would recommend Elasticsearch if you don't have bigger budget limitations to use other enterprise solutions or if you want to avoid the vendor lock-in.

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While I cannot say for sure, as our organization is structured so that we work in silos with everyone looking after his own infrastructure, I would estimate that we have approximately 200 employees making use of the solution.

My advice to others who are considering implementing the solution is that they first make a plan to figure out how they wish to cluster the solution and the amount of data that must be ingested. Much planning would be involved. It would be wise to start with the open-source solution, which comes with many advantages, and to move on to the Enterprise version if there should be a need for dedicated support. 

I cannot posit whether management will wish to take this route, although this is definitely worth considering, as we are talking about a fully robust infinite solution across the board. 

I rate ELK Elasticsearch an eight out of ten.

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For anyone who is looking into implementing this solution, the only tip is to get your models for the type of actual use that you are looking at upfront in order to have a good run.

I would rate ELK Elasticsearch a seven out of ten.

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I like this solution, but it has too much hands-on time required tweaking to get it up and running.

I have no plans to continue using this product. Currently, I am focused on SIEMonster because I signed a partnership and I would like to sell a total product. It doesn't make sense to spread across multiple products. 

I would like to earn money out of it, so I'm focusing currently on SIEMonster.

I think that Elasticsearch is a good product and cheaper than Splunk.

When I check Gartner, I don't see mention of Elasticsearch, it seems they need to make some improvements.

I would rate this solution a seven out of ten.

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For anyone looking to implement a monitoring product with almost no cost or at a cheaper price, I would suggest the ELK stack. However, it does require a high skill set because of the difficulty with implementation. 

I would rate this solution a six out of 10. 

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The distributed installation is the way to go.

I would rate ELK Elasticsearch a nine out of ten.

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The solution has a lot of features. They have machine learning jobs they can implement, I'm not there yet, but I can use anomaly detection to see there are various processes that can find users that aren't supposed to log onto certain machines. All of these features are visual and graphical. I can show it as a bar chart, a pie chart, I can Instagram, or I can split chart. The power to see everything on the front end is so much more powerful.

I rate ELK Elasticsearch a ten out of ten.

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In general, we have many advantages from the features of Elasticsearch, but there are questions mostly about money, not about technical features, that are of concern.

I would rate Elasticsearch eight/nine out of ten. We have enough possibilities and features with Elasticsearch for our business requirements.

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I give it a seven out of 10. They don't provide user authentication and authorisation (shield) as a part of their open source version.

Nice to implement, they have nicely written documentation.

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Elasticsearch is open source.

I rate ELK Elasticsearch an eight out of ten.

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You can test the product for your use case on their user free trial, they offer a seven or 14-day free trial, You can put it up on cloud and just push your data to check if your use cases are being handled or not. It's a quick test of the waters. 

I would rate this product an eight out of 10. 

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My advice for anybody considering this solution is that it is an easy to use tool, but for work that is not complex. If on the other hand, the work is more complex, with more data and perhaps a clustering environment, then they may have to consider something more stable and more robust.

I would rate this solution a seven out of ten.

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I would recommend those wanting to implement this solution use integrators or consultants. However, we did not have any problems with the installation it can be difficult.

I rate ELK Elasticsearchan eight out of ten.

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We have some devices that are managed by AWS and we have our own information with switches that are self-hosted.

ELK Elasticsearch is a product that I recommend.

I would rate this solution a seven out of ten.

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The advice I would give to others considering this solution is that you have to have someone knowledgeable managing the system. You have to know the needs, know how to manage queries, and understand the visualization. You have to have someone working on it and dedicated to it so that you can manage it. It is not just plug-and-play. If you decide to run with it, the performance and the result can be very satisfactory. We did not have any issues with achieving what we tried to do. When we need certain data, we always find it.

On a scale from one to ten where one is the worst and ten is the best, I would rate ELK Elasticsearch as an eight out of ten. What would make it a ten for us is something I wouldn't know at this point. Until we use it more heavily in production then we'll see how it performs under a full load and we'll have a better idea of what needs to be improved.

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This solution is ok for me and my business.

I would rate this solution an eight out of ten.

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The search product is a product exposing API. Therefore, be comfortable in developing your own front-end to integrate the Search API.

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I also use Kibana, which is integrated with Elasticsearch. Kibana is for visualization and we can also customize Elasticsearch using Kibana.

In summary, Elasticsearch is a very useful product that I can quickly recommend.

I would rate this solution an eight out of ten.

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