Datadog, a leading firm that provides cloud monitoring as a service has announced its support for Hadoop framework for processing large datasets across a cluster of computers. Hadoop users can use Datadog’s dashboard for target alerts and full stack visibility. Hadoop users will not be able to host’s system level metric and hundreds of Hadoop metrics so that they can easily relate to what’s happening throughout their stack. Users will also be able to set alerts if critical hadoop jobs don’t finish on time.
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Speaking at the Strata and Hadoop World conference, Hadoop creator Doug Cutting mentioned about the increasing I/O bottleneck arising as processing speed and efficiency are increasing faster than the storage read-write rates. Cutting predicts that the new Intel 3D XPoint storage chips will retrieve data 1000 times faster will open up the platform to new uses so that users can process large datasets in-memory by bypassing the latency inherent in fetching the data from disk.
Pepperdata conducted a survey of about 134 software engineers, data scientists from various industries such as finance, education, etc. The biggest challenge the respondents found in using Hadoop in operations is – the he skills gap – on implementing Hadoop and the knowledge of Hadoop.
BlueData, whose software allows enterprises to run Apache Hadoop and Spark in a virtualized environment is now branching out and offering its new EPIC platform version. This will let users run computing on AWS, while keeping their data on-premise.
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ODPi is a non-profit organization that is dedicated to standardizing big data and Hadoop ecosystem with a common reference solution specification, known as the ODPi core. Hadoop distributions - Altiscale, ArenaData, Hortonworks, IBM, and Infosys are now ODPi Runtime Compliant. These Hadoop distributions now adhere to a specific set of expectations to run big data solutions.
With many companies still struggling with Hadoop complexities to yield data-driven results, MapR announced its new initiative Spyglass. MapR’s new Spyglass intuitive will help customers leverage will ease hadoop administration with greater administrator productivity and efficient cluster management. Spyglass will provide in-depth visibility with various customizable dashboards that will ease big data deployments.
To bring in Spark’s fast data processing speed advantages within the reach of its R users, Microsoft has integrated the support for Spark into its R server for Hadoop. This integration will help R users run R functions on 1000’s of apache spark nodes and train models on data that is thousand times larger. The new integrated support combines the speed of R Server’s parallelized algorithms and Spark’s in-memory architecture, it can run algorithms several times faster than the open source.
BMC is evolving with its new hadoop initiatives. As Hadoop turns 10 this years, BMC has opened up bunch of new API’s. Automation is a key ingredient to its services and its working on automating jobs across different platforms including hadoop to provide simple and sexy interface. There already exist many technologies that warn customers of potential threat but BMC is working on changing that by actually preventing threat and securing operations instead of just warning them.
At the Hadoop Summit 2016 in San Jose, CA, Mark Holder Baugh, senior director of Hadoop Engineering at Yahoo highlights 3 ways in which Yahoo uses Hadoop to optimize utilization. To meet the growing demands from its customers and provide better user experience –
The leading provider of big data management software solutions Attunity released its latest software solution Attunity Visibility for Hadoop. The latest release with enhanced technology provides organization comprehensive data usage analytics that help enterprise measure their hadoop data storage usage for optimized cost performance, accurate capacity planning, and ensure that all data governance and compliance requirements are met.