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Unravel for Cloud Dataproc Released

Unravel Data introduced a performance management solution for the Google Cloud Dataproc platform that makes data workloads running on the top of the platform simpler to use and cheaper to run.

Unravel for Cloud Dataproc, which is available immediately, can improve the productivity of data teams with a simple and intelligent self-service performance management capability, helping DataOps teams:

- Optimize data pipeline performance and ensure application SLAs are adhered to

- Monitor and automatically fix slow, inefficient and failing Spark, Hive, HBase and Kafka workloads

- Maximize cost savings by containing resource-hogging users or applications

- Get a detailed chargeback view to understand which users or departments are utilizing the system resources

For enterprises powered by modern data applications that rely on distributed data systems, the Unravel platform accelerates new cloud workload adoption by operationalizing a reliable data infrastructure, and it ensures enforceable SLAs and lower compute and I/O costs, while drastically lowering storage costs. Furthermore, it reduces operational overhead through rapid mean time to identification (MTTI) and mean time to resolution (MTTR), enabled by unified observability and AIOps capabilities.

“Unravel simplifies the management of data apps wherever they reside - on-premises, in a public cloud, or in a hybrid mix of the two. Extending our platform to Google Cloud Dataproc marks another milestone on our roadmap to radically simplify data operations and accelerate cloud adoption,” said Kunal Agarwal, CEO, Unravel Data. “As enterprises plan and execute their migrations to the cloud, Unravel enables operations and app development teams to improve the performance and reduce the risks commonly associated with these migrations.”

In addition to DataOps optimization, Unravel provides a cloud migration assessment offering to help organizations move data workloads to Google Cloud faster and with lower cost. Unravel has built a goal-driven and adaptive solution that uniquely provides comprehensive details of the source environment and applications running on it, identifies workloads suitable for the cloud and determines the optimal cloud topology based on business strategy, and then computes the anticipated hourly costs. The assessment also provides actionable recommendations to improve application performance and enables cloud capacity planning and chargeback reporting, as well as other critical insights.

“We’re seeing an increased adoption of GCP services for cloud-native workloads as well as on-premises workloads that are targets for cloud migration. Unravel’s full-stack DataOps platform can simplify and speed up the migration of data-centric workloads to GCP giving customers peace of mind by minimizing downtime and lowering risk,” said Mike Leone, Senior Analyst, Enterprise Strategy Group. “Unravel adds operational and business value by delivering actionable recommendations for Dataproc customers. Additionally, the platform can troubleshoot and mitigate migration and operational issues to boost savings and performance for Cloud Dataproc workloads.”

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Unravel for Cloud Dataproc Released

Unravel Data introduced a performance management solution for the Google Cloud Dataproc platform that makes data workloads running on the top of the platform simpler to use and cheaper to run.

Unravel for Cloud Dataproc, which is available immediately, can improve the productivity of data teams with a simple and intelligent self-service performance management capability, helping DataOps teams:

- Optimize data pipeline performance and ensure application SLAs are adhered to

- Monitor and automatically fix slow, inefficient and failing Spark, Hive, HBase and Kafka workloads

- Maximize cost savings by containing resource-hogging users or applications

- Get a detailed chargeback view to understand which users or departments are utilizing the system resources

For enterprises powered by modern data applications that rely on distributed data systems, the Unravel platform accelerates new cloud workload adoption by operationalizing a reliable data infrastructure, and it ensures enforceable SLAs and lower compute and I/O costs, while drastically lowering storage costs. Furthermore, it reduces operational overhead through rapid mean time to identification (MTTI) and mean time to resolution (MTTR), enabled by unified observability and AIOps capabilities.

“Unravel simplifies the management of data apps wherever they reside - on-premises, in a public cloud, or in a hybrid mix of the two. Extending our platform to Google Cloud Dataproc marks another milestone on our roadmap to radically simplify data operations and accelerate cloud adoption,” said Kunal Agarwal, CEO, Unravel Data. “As enterprises plan and execute their migrations to the cloud, Unravel enables operations and app development teams to improve the performance and reduce the risks commonly associated with these migrations.”

In addition to DataOps optimization, Unravel provides a cloud migration assessment offering to help organizations move data workloads to Google Cloud faster and with lower cost. Unravel has built a goal-driven and adaptive solution that uniquely provides comprehensive details of the source environment and applications running on it, identifies workloads suitable for the cloud and determines the optimal cloud topology based on business strategy, and then computes the anticipated hourly costs. The assessment also provides actionable recommendations to improve application performance and enables cloud capacity planning and chargeback reporting, as well as other critical insights.

“We’re seeing an increased adoption of GCP services for cloud-native workloads as well as on-premises workloads that are targets for cloud migration. Unravel’s full-stack DataOps platform can simplify and speed up the migration of data-centric workloads to GCP giving customers peace of mind by minimizing downtime and lowering risk,” said Mike Leone, Senior Analyst, Enterprise Strategy Group. “Unravel adds operational and business value by delivering actionable recommendations for Dataproc customers. Additionally, the platform can troubleshoot and mitigate migration and operational issues to boost savings and performance for Cloud Dataproc workloads.”

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An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

Image
Azul

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ...