Unravel Data announced the general availability of its 2022 Fall Release of the Unravel Platform.
With this new release, users of the Unravel Platform are now able to leverage several new capabilities including support for Google Cloud BigQuery and Cost 360 for Amazon EMR. These new capabilities are designed to help users boost the efficiency of their public cloud spend, simplify troubleshooting across their big data ecosystem, and improve the overall performance of their business critical data applications.
“Data teams have a clear mandate to ensure that the data pipelines that support their data analytics programs are fully optimized, running efficiently and staying within budget. However, given the complexity of their data ecosystem, getting answers about the health and performance of their data pipelines is harder than ever,” said Kunal Agarwal, founder and CEO of Unravel Data. “Whether they're migrating more workloads to platforms like BigQuery or Amazon EMR or already running it as part of their data ecosystem, enterprise data teams are struggling to control costs and accurately forecast their resource requirements that are ultimately impacting their ability to execute on their strategic data analytics initiatives. With this latest edition, Unravel customers will be better able to gain the full-stack observability they need to optimize performance and manage their costs according to budget.”
Some of the new capabilities in the Fall Edition of the Unravel Platform include:
- Full Cost Governance for Amazon EMR: With Unravel’s new ‘Cost 360 for Amazon EMR’ capability, customers can enjoy full visibility and gain critical insights into their spending on Amazon EMR. A new cost page has been added that enables customers to observe their EMR cost and usage trends and identify anomalies, slice and dice chargeback views with a variety of filters, and actively monitor costs against user-defined budgets that can automatically trigger warnings if costs are projected to exceed predefined thresholds.
- Advanced EMR Cluster Management: To streamline the management of EMR clusters, a new Clusters page is available inside the Unravel UI for Amazon EMR, allowing users to actively monitor all their EMR clusters and cost data from a single location. The Clusters page also helps users quickly visualize, debug, and troubleshoot issues at both the cluster and application levels.
- Unified View into BigQuery Deployments: Unravel enables customers to now view all information about any number of Google Cloud Platform projects and all BigQuery queries in these respective projects from a single interface. Key performance indicators and metadata are collected for every query. The new edition now supports advanced relevance-based ranked search, faceted search based on metadata and performance indicators, time-based search, as well as drill downs into the individual query level.
- Enhancements for Databricks: When scheduling a job to extract metadata from Databricks, Unravel users can now specify multiple database names and can extract up to 25,000 Delta tables in a single job. Other Databricks enhancements include custom pricing for workload and tier combinations, APIs to detect anomalies and metrics, as well as the ability to encrypt passwords and tokens to harden application security.
The Latest
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...