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Unravel Data Announces 2022 Fall Release

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.

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Unravel Data Announces 2022 Fall Release

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.

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Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...