Spot by NetApp, now including CloudCheckr, helps companies to run their cloud investments. The Spot product suite uses machine learning and analytics to automate and optimize cloud infrastructure, to ensure that workloads and applications always have the best possible infrastructure that is available, scalable and available at the lowest possible cost. Spot’s technology provides insights into cloud costs, recommendations for how to optimize utilization and costs, and automation to implement…
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Snowflake
Score 9.0 out of 10
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The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
CloudCheckr is fantastic for those that are purely in the Cloud as it provides everything you need under one roof for a comprehensive configuration and usage monitoring tool. It has SysLog capabilities though so you can farm out the alerts into a SIEM or other log management system, so hybrid environments could also benefit from its use.
I am over our HR data, and we use Workday for our HR management system. I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket. Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.
Detailed Best Practices. It's important to align your cloud to industry best practices for security and cost—it just performs better if it's used the way it's meant to be used. AWS is very flexible, and that's great when you have special requirements, but you've got to at least know when you're using something in a non-standard way so you can think through the implications.
Cost Reduction. Some recommendations are almost impossible to make at least for our setup, but many, many others are easy. We only have to log into CloudCheckr every few months and make a few changes for it to more than pay for itself.
Right-Sizing. This is related to the other points, but for some reason is separate from their cost module. The metrics it's able to pull only tell half the story, so it's good to verify it's sizing recommendations before making changes. But it does show you what instances to focus on first, and even if you choose a slightly different size to move it to, it does clearly indicate it's current size isn't appropriate. And this works both ways, if the size is too big, you can save some cash by making it smaller, but if it's too small, you want to be sure to scale up before you run into performance problems.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
CloudCheckr features have a tendency to break without warning. Functionality in place for months could suddenly stop working.
CloudCheckr support often delays work on support tickets for fixing broken application functionality.
The CloudCheckr platform and documentation website often crash or experience performance degradation.
CloudCheckr cost reporting is often impacted by faulty code or broken report functionality. This can contribute to a low level of confidence in CloudCheckr's ability to deliver accurate cost reporting.
This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team.
I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
Overall, CloudCheckr covers all our AWS monitoring needs and great integration through SysLog into our SIEM to capture alerts for investigation. The reports are great and allow for an easy daily review. Small improvements could be made to the interface and better filtering in places would be good. Great product and the price is fair.
The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
There are a few products out there that'll do an aspect or two of what CloudCheckr does, but I honestly couldn't find anything nearly as comprehensive as CloudCheckr.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
Positive impact: we use Snowflake to track our subscription and payment charges, which we use for internal and investor reporting
Positive impact: 3 times faster query speed compared to Treasure Data means that answers to stakeholders can be delivered quicker by analysts
Positive impact: recommender systems now source their data from Snowflake rather than Spark clusters, improving development speed, and no longer require maintainence of Spark clusters.
