GoodData.AI vs. Zabbix

I think it works nicely for shops that want the analytical power and are ok to host their own infrastructure for the data and etl. For smaller operations with limited budgets but still high demand for analytical features the math may not work out.

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Zabbix is great for monitoring your servers and seeing alerts when the system uses too much CPU or memory. This allowed the system Engineer to be proactive and add resources to these systems to avoid interrupting the services. Especially servers running operations applications and services. This is one of the best usages for Zabbix.

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• The source datasets are often complex, semi-structured and un-linked to key entities. With GoodData, all of these datasets are unified to serve as a central semantic data model layer, building into a galaxy schema with dimensions, bridge, and facts, which then forms the backbone that powers the [...] data intelligence cloud. Building insights and dashboards become a much easier task once the underlying data model is designed. GoodData enforces certain best practices as a BI tool, which must be adhered to get the true value of the raw data. For e.g. the source FDA dashboard may just show inspection data but the Site Profile dashboard built on GoodData goes beyond the standard information and shows more insight into site risk scores and can be drilled into details. There is blog written on this topic: [...].
• GoodData provides a rich collection of visualization options that help us create compelling story-telling via dashboards. Being well-prepared for FDA inspections is essential for maintaining product quality, regulatory compliance, and avoiding serious business setbacks. FDA inspections are critical events that can shape a company’s market access and reputation. The FDA itself offers the FDA Data Dashboard, but it doesn’t make every document available. There is a blog written on this topic: [...].
• Medical devices and technologies do not stop evolving after they receive regulatory approval. Once a product hits the market, it faces real-world usage, compliance challenges, and an array of regulatory scrutiny. Managing these postmarket dynamics is critical to a product’s long-term success and patient safety. However, many companies struggle to keep track of relevant events across a product’s markets, from adverse event reports to changing regulations. Postmarket Intelligence developed on GoodData platform enables us to solve that problem. It empowers MedTech companies to efficiently monitor, assess, and act on postmarket data—saving time, improving decision-making, and ensuring compliance with industry standards. Anyone who is used to trying to get the data they need from the various FDA, and other regulatory agency websites, knows that collecting, cleaning, and structuring that data takes hours. And that’s before any analysis can get done. We enable customers to free up time to focus only on the high-value analysis and subsequent recommendations to leadership, rather than wrangling the data.
• The data pipeline refresh that is provided by GoodData Platform is also quite useful from data engineering perspective. The Automated Data Distribution v2 or commonly called as ADD refresh follows a set pattern of identifying the analytical data model through output stage which helps abstract the complex table definition to simpler views that can help with quick rebuild at the data warehouse level while loading the data into GoodData's ADS storage layer. The import first way of loading data into GoodData's cloud storage, followed by querying for any aggregations or metrics on the GoodData analyzer, makes this simple and fast.
• GoodData's latest product i.e. Cloud also offers several good features like Analytics as Code which helps software engineering teams follow a code-first approach to analytics, where building insights, dashboards or even datasets can be done in YAML templates or serviced by REST APIs. This is particularly forward thinking in the modern technology stack and evolving industry requirements. These provide seamless integration options to front-end and backend code, embedded analytics with multiple choices from HTML to React based workloads. At [...], we are currently exploring most of these features while planning for a future migration from Platform to Cloud.

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• Collecting hardware data - CPU, Memory, Network, and Disk Metrics are collected and reported on.
• Flexible design - It is very easy to build out even very large environments via the templating system. You can also start where you are - network monitoring, server monitoring, etc. and then build it out from there as time and resources permit.
• Provides a "plugin architecture" (via XML templates) to allow end users to extend it to monitor all kinds of equipment, software, or other metrics that are not already added into the software already.
• Very complete documentation. Almost every aspect of Zabbix has been documented and reported on.
• Cost - Zabbix is FOSS software and always free. Support is reasonably priced and readily available.

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• Good Data is already have certain customizable options. However, having more flexibility in customizing reports and dashboards & control over the visual aspects would enhance the overall user experience.
• To make Good Data even more powerful tool, improving the speed and responsiveness of the tool, especially during data-intensive tasks, would be a significantly helpful.
• For new users, the interface can be made more user friendly which would promote easy navigation through features of tool.

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• Creating an alert & its trigger can be made easier.
• More VM-based data collection counters should be introduced to have better VM monitoring.
• The raw counters collection agent in every node is relatively weak. It goes down often, which needs more stability.

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Because gooddata really helps us in processing data to make reports or dashboards. So we are very satisfied when we use it. What we like is the flexible use of charts. We change at will the use of charts to display in reports or dashboards. Thank you Gooddata for helping companies like us who need flexibility in usage

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It is free. It didn't cost anything to implement (other than my time and the cost incurred for it) and it is filling a badly needed gap in our IT infrastructure. Support is available if we have issues and can be done annually or paid for on a per incident basis as needed. Expansion, updates, and all other future lifecycle activities are likewise free of cost, so as long as someone is able to implement/maintain the software (and the OSS project is maintained) then I imagine the company will never leave it.

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From a customer perspective it is incredibly usable. We have more users building their own reports that would normally need custom work from our support team. The back end can be daunting when trying to configure things like new data elements or push changes to a report to all existing customers.

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I think every organization, especially the IT department, needs a tool like this. I know of another product like Zabbix that gives a similar or the same solution, but its range makes it very useful. You can see almost all the device info in one place: disk usage, disk space, network usage, etc.

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We are approximately one month since go-live. There has been one short outage.

I'm generally impressed with how fast it reflects so much data.

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Support team has been highly responsive and helpful from our first initial deployment to present day. They engage and work with us. know when to escalate for more challenging problems. They also follow up. Overall have had a very good experience with support

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The setup is the most time-consuming portion of using zabbix. It takes a lot of effort to shape it into a usable format and even then it can get very messy. It's not exactly intuitive and as mentioned the UI seems a bit antiquated. If I was to roll out a monitoring solution from scratch, I'd probably look for alternatives which are easier to use and maintain.

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Petr was a rock star - patient, knowledgeable, clear and easy to work with.

GoodData implementation team was professional and courteous

Implementations are hard and we had limited technical resources. We relied too heavily on GD care team. When we found technical gaps, they weren't simple to overcome

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We are a mainly Windows environment, so it would be useful if we could have used Active Directory to deploy agents. As of version 4.2, Zabbix has announced a new agent MSI file to allow exactly that. Unfortunately, we didn't have that option. Also, for Linux and MAC deployments, there is no simple way to deploy that. Using remote scripts you may be able to create something, but most places will opt for either SNMP (agentless) or manual installation of agents to add to Zabbix. A way of deploying agents via discovery would go a long way to helping in the adoption of the tool.

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GoodData comparing to other platform is very easy to use, customer support and on-boarding support. Set of features, speed of integration in our platform. Also great benefit for us was very competetive pricing.

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We're using the Solarwinds suite as our global monitoring standard, but it is very complex and its licensing model makes it difficult to monitor a wide range of technologies. So, we're using Zabbix as a complement on our monitoring process. Zabbix is a way more flexible and has free integrations to a wide range of technologies. It is also more 'user friendly' and easy to manage.

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We never had any issues with scalability, other than being limited by workspaces

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• I personally pushed our management to get GoodData implemented, and there on we have been making much more profits than we ever did!
• Last month we made a decision using the platform and withing a short span of time our ROI gets 7X.
• We also made a marketing spend of $100,000 every quater using the insights and metrics, and we are really happy with the returs.

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• Good ROI when trying to get ahead of network related problems instead of waiting for users to complain
• Good ROI when doing upgrades or exploratory work on a neglected network
• Good ROI when showing usage trends to management showing higher actual usage versus what was thought to be happening