Geckoboard vs. Logstash

Great value for the money. Excellent for smaller agencies with multiple projects and teams in a smaller space. We can quickly roll out mobile displays to help with a particular deployment push or monitoring a clients website engagement. It's also useful for showing live data without requiring analytics to run reports from a CRM, etc.

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Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).

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• User self-help - the video tutorials and a robust publicly accessible knowledgebase.
• Geckoboard can aggregate data from a number of other apps into a singular dashboard.
• Sleek, dark UI.

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• Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
• Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
• Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
• You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.

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• A bit more flexibility in the number of columns would be nice.
• Ability to scale to mobile device (web).
• App capabilities are missing on Android.

• It is heavy i.e., intensive as of now. Need to reduce overhead to save CPU/RAM consumption
• Need to be more Kubernetes-friendly. Should support auto-scaling and K8s observability
• Initial configuration is still complex. A seamless config procedure is still required

My company did not renew due to changes in the organization.

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With a simple interface and available templates, creating basic dashboards is easy. Obviously depending on the data you want to visualize, there may be higher learning curves. That being said, they have a huge amount of integrations and extensible frameworks. If you are using anything made in the past ten years there is an API function or integration that can get it talking to the platform. As such, it's pretty easy to hit the main data points you want and get it on a cheap display in front of your team.

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As I said earlier, for a production-grade OpenStack Telco cloud, Logstash brings high value in flexibility, compliance, and troubleshooting efficiency. However, this brings a higher infra & ops cost on resources, but that is not a problem in big datacenters because there is no resource crunch in terms of servers or CPU/RAM

The support levels vary based on the level of plan that you have but that's to be expected. Virtually everything except the Enterprise plan has basic chat/email support. While they are responsive they are not going to be much assistance in helping you figure out API calls or implementing 3rd party integrations. That is to be expected and the support community can pretty much get you in the right direction if you look.

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Domo is more robust. We do use both because Geckoboard is really easy to show the rest of our team without the need for additional licenses.

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Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various searching systems such as Solr or Graylog, or even monitoring solutions built on top of Graphite or OpenTSDB.

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• While we originally used this as an internal IS tool, we eventually have expanded it to be used by nearly every department.
• Because pricing is monthly, we can grow or decrease our usage based on our current client needs.
• Because it is low cost and easy to deploy, we can utilize it in place of considerable resources in analytics and reporting by delivering snapshots of data without pulling reports.

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• Positive: LogStash is OpenSource. While this should not be directly construed as Free, it's a great start towards Free. OpenSource means that while it's free to download, there are no regular patch schedules, no support from a company, no engineer you can get on the phone / email to solve a problem. You are your own Engineer. You are your own Phone Call. You are your own ticketing system.
• Negative: Since Logstash's features are so extensive, you will often find yourself saying "I can just solve this problem better going further down / up the Stack!". This is not a BAD quality, necessarily and it really only depends on what Your Project's Aim is.
• Positive: LogStash is a dream to configure and run. A few hours of work, and you are on your way to collecting and shipping logs to their required addresses!

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info