Thank you for your interest in the Unravel Data for Cloudera Datasheet.

You can download it here.

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Also see our blog post with stats from our Untold conference polls, “More than 60% of our Pipelines have SLAs…”

Unravel Data recently held our first-ever customer conference, Untold. Untold was a four-hour virtual event exclusively for and by Unravel customers, with five talks and an audience of 200 enthusiastic customers. The event featured powerful presentations, lively Q&A sessions, and interactive discussions on a special Slack channel. 

Unravel customers can view the recorded presentations and communicate with the speakers, as well as their peers who attended the event. If you’re among the hundreds of existing Unravel customers, including three of the top five North American banks, reach out to your customer success representative for access. If you are not yet a customer, you can create a free account or contact us. 

The talks included: 

• Using Unravel for DataOps and SDLC enhancement
• Keeping complex data pipelines healthy
• Solving the small files problem (with great decreases in resource usage and large increases in throughput)
• Managing thousands of nodes in scores of ever-busier modern data  clusters

One speaker even described a successful cloud migration and the key pain points that they had to overcome.

In a “triple threat” presentation, with three speakers addressing different use cases for Unravel in the same organization, the middle speaker captured much of the flavor of the day in a single comment: “Especially with cloud costs, I think Unravel could be a game changer for every one of us.” 

Another speaker summed up “the Unravel effect” in their organization: “We can invest those dollars that we’re saving elsewhere, which makes everybody in our organization super happy.”

Brief descriptions of each talk, with highlights from each of our speakers, follow. Look for case studies on these uses of Unravel in the weeks ahead. 

Using Unravel to Improve the Software Development Life Cycle and DataOps

A major bank uses DataOps and Unravel to support the software development life cycle (SDLC) – to create, validate, and promote apps to production. And Unravel helps operators to orchestrate the apps in production. Unravel significantly shortens development time and improves software quality and performance. 

Highlights from the presentation include:

• • “We have Unravel integrated with our entire software development life cycle. Developers get all the insights into how well their code will perform before they go to production.”
  • “The Unravel toolset is something like a starting point to log into our system, and do all the work, from starting building software to deployment level to production.”
  • “When less experienced users look at Spark code, they don’t understand what they’re seeing. When they look at Unravel recommendations, they understand quickly, and then they go fix it.”
  • “As we move to the cloud, Unravel’s APIs will be useful. Today you run your code and spend $10. Tomorrow, you’ll check your code in Unravel, you’ll implement all these recommendations, you’ll spend $5 instead of $10.”

Managing Mission-Critical Pipelines at Scale

A leading software publisher manages thousands of complex, mission-critical pipelines, with tight SLAs – and costs that can range up into the millions of dollars associated with any failures. Unravel gives this organization fine-grained visibility into their pipelines in production, allowing issues to be detected and fixed before they become problems. 

Key points from the talk:

• “At my company, this is a simple pipeline. (Speaker shows slide with Rube Goldberg pipeline image – Ed.) One of our complicated pipelines has a 50-page user manual. We partnered with the Unravel team to stitch these pipelines together.” 
• “Unravel is helping us to actually predict the problems in advance and early in the process, ensuring we can bring these pipelines’ health back to normal, and making sure our SLAs are met.”
• “Last year, to be frank, we were around 80% SLA accomplishments. But, through the two quarters, we are 98% and above.”

Easing Operations and Cutting Costs 

A fast-growing marketing services company uses Unravel to manage operations, reduce costs, and support leadership use cases, all while orchestrating and managing cloud migration – and saves hugely on resources by solving the small files problem. 

This talk actually involved three separate perspectives. A few highlights follow:

• “On-prem Hadoop, that’s where the Unraveled story started for us.”
• “We had around 1,800 cores allocated. After the config changes recommended by Unravel, the cores allocated went down to 120.”
• “Unravel helped us build an executive dashboard… the response time from Unravel on it was great. The whole entire experience was wonderful for me.”
• “Proactive alerting – AutoActions – catches runaway queries, rogue jobs, and resource contention issues. It makes our Hadoop clusters more efficient, and our users good citizens.” 
• “We were over-allocating for jobs in Spark, and I’m not an expert Spark user. Unravel recommendations and AutoActions helped solve the problem of over-allocation, without my having to learn more about Spark.”
• “Having the data from Unravel makes our conversations with our tenants much more productive, and has helped to build trust among our teams.” 
• “We can invest those dollars that we’re saving elsewhere, which makes everybody in our organization super happy.”

A Successful Move to Cloud 

A leading provider of consumer financial software moved to the cloud successfully –  but they had to use inadequate tools, including tracking the move in Excel spreadsheets and saving data in CSV files. They were able to complete the move in less than a year, “leaving no app behind.” 

As the speaker described, it was a huge job: 

• “Think of our move from on-premises to the cloud as changing the engines of the plane while the plane is flying.”
• “We actually started the exercise with more than 20,000 tables, but careful analysis showed that half of them were unused.”
• “We have many, many critical pipelines, and there were millions of dollars at stake for these things not to be correct, complete, or within SLA.” 
• “The cloud is not forgiving when it comes to cost. Linear increases in usage lead to linear increases in costs.” 
• “The cloud offers pay as you go, which sounds great. But when you go, you pay.” 

The move made clear the need for Unravel Data as a supportive platform for assessing the on-premises data estate, matching on-premises software tools to their closest equivalents on each of the major public cloud platforms, and tracking the success of the move. 

Unravel Right-Sizes Resource Consumption – as the Pandemic Sends Traffic Soaring

One of the world’s largest financial services companies sees usage passing critical thresholds – and then the pandemic sends their data processing needs through the roof. They used Unravel to steadily reduce memory and CPU usage, even as data processing volumes grew rapidly. 

• “Before Unravel, our memory and CPU allocations were way greater than our actual usage. And we spent many hours troubleshooting problems because we couldn’t see what was going on inside our apps.” 
• “With Unravel, we saw that a lot of vCores were unused. And we were able to drop almost 40,000 tables… that helped us a lot.”
• “Before Unravel, we were uncomfortably past the 80% line in capacity, and memory was always pegged. With Unravel, we were able to cut usage roughly in half for the same throughput.”
• “Before Unravel, we couldn’t give users – including the CEO – a real good reason on why they weren’t getting what they wanted.”
• “Comprehensive job visibility, such as the configuration page in Unravel, has improved resolution times.”
• “(Unravel) provides us a reasonable rate of growth in our use of resources compared to workloads processed – a rate which I can sell to my management team.”
• “I’m sleeping a lot better than I was a year ago. My Fitbit sleep score is now 88. It’s been a good journey so far.” (A Fitbit sleep score of 88 is well above most Fitbit users – good, bordering on excellent – Ed.)

Finding Out More

Unravel customers can view the talks, communicate with industry peers who gave and attended the talks, and more. (There may still be some swag available!) If you’re interested, you can create a free account or contact us. 

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Last year, Cloudera released the Cloudera Data Platform, an integrated data platform that can be deployed in any environment, including multiple public clouds, bare metal, private cloud, and hybrid cloud. Customers are increasingly demanding maximum flexibility to adhere to multi-cloud, hybrid data management demands. Unravel has from the beginning has made it a core strategy to support the full modern data stack, on any cloud, hybrid as well as on-premises.

Today we are pleased to announce that Unravel is now certified on Cloudera Data Platform (both CDP public cloud as well as CDP Data Center). This marks an important milestone in our continued partnership with Cloudera, bolstered by a growing demand among Cloudera users for our AI-driven performance optimization solution for modern data clouds.

The certification ensures that Unravel is integrated seamlessly with Cloudera Data Platform, providing customers with an intelligent solution to improve the reliability and performance of their modern data stack applications and operations, and optimize costs through data driven insights. We look forward to continually supporting Cloudera customers, on CDP as well as CDH and HDP.

The full press release can be viewed below.

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Unravel Data Earns Certification for Cloudera Data Platform

Unravel Supports Cloudera Data Platform in the public cloud, on-premises and in hybrid environments, continuing Unravel’s mission to simplify and optimize modern data applications wherever they exist

PALO ALTO, CALIFORNIA – March 25, 2020– Unravel Data, the only data operations platform providing full-stack visibility and AI-powered recommendations to drive more reliable performance in modern data applications, today announced that it has been certified on the Cloudera Data Platform. Cloudera Data Platform manages data in any environment, including multiple public clouds, bare metal deployments, private clouds and hybrid clouds. The certification further advances Unravel’s mission to simplify and optimize modern data apps wherever they exist, with this move particularly bolstering Unravel’s support for hybrid cloud and multi-cloud environments.

“Data apps, especially AI and ML apps, are increasingly being spread across a mix of on-premise and public cloud environments. These highly distributed hybrid cloud deployments provide unique advantages and greater flexibility compared to all-in approaches that put everything either in the cloud or in a private datacenter,” said Kunal Agarwal, CEO, Unravel Data. “Organizations are also deploying more data apps in multiple clouds, which allows them to leverage the specific strengths of each cloud and provides unique app functionality. However, the growing distribution of data apps in hybrid and multi-cloud settings introduces operational complexity and naturally makes it harder to optimize and monitor these apps. Unravel ensures that enterprises have both a clear line of sight into these apps and automated recommendations to troubleshoot and maximize their performance, no matter where the apps are located.”

In order to earn this certification, Unravel maintained their silver partnership status through the Cloudera Connect partner program, built new integrations for Cloudera Data Platform (for both the public cloud and on-premise version), then documented and tested those integrations. Cloudera worked closely with Unravel during the entire process.

The certification is the latest milestone in a long relationship between Unravel and Cloudera. Unravel was previously certified on Cloudera Enterprise and the two share many joint customers. This integration will ensure legacy CDH and HDP customers who migrate to Cloudera CDP will continue to enjoy Unravel’s solutions to simplify data operations on AWS, Azure and GCP in addition to on-premises.

About Unravel Data
Unravel radically simplifies the way businesses understand and optimize the performance of their modern data applications – and the complex pipelines that power those applications. Providing a unified view across the entire stack, Unravel’s data operations platform leverages AI, machine learning, and advanced analytics to offer actionable recommendations and automation for tuning, troubleshooting, and improving performance – both today and tomorrow. By operationalizing how you do data, Unravel’s solutions support modern big data leaders, including Kaiser Permanente, Adobe and Deutsche Bank. The company is headquartered in Palo Alto, California, and is backed by Menlo Ventures, GGV Capital, M12, Point72 Ventures, Harmony Partners, Data Elite Ventures, and Jyoti Bansal. To learn more, visit unraveldata.com.

Copyright Statement
The name Unravel Data is a trademark of Unravel Data. Other trade names used in this document are the properties of their respective owners.

PR Contact
Jordan Tewell, 10Fold
unravel@10fold.com
1-415-666-6066

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As discussed in our recent Series C announcement, we are seeing unprecedented and accelerating demand for solutions to complex, business-critical challenges in dealing with data. Modern data systems are becoming impossibly complex. The burgeoning amount of data being processed in organizations today is staggering. Just a year ago, Forbes reported that 90% of the world’s data was created in the previous two years.

“New Stack” of Software Emerging

Organizations of all sizes and in all industries are transforming to deal with this change and a ‘New Stack’ of software is emerging to enable the building, operation and monitoring of these modern applications and the systems that support them. According to Morgan Stanley, ‘New Stack’ revenue is set to hit $50 Billion by 2022. In addition, according to their January 2019 CIO Survey, 50% of application workloads are expected to reside in public cloud environments by 2022, up from ~22% today.

With that backdrop, are the recent headlines about Cloudera and MapR surprising or anticipated? Is interest in data waning? Not even close. So why did Hortonworks get swallowed, Cloudera stumble and is MapR disappearing? Consensus is clear – execution gaps and an expected, but much faster than anticipated adoption of public cloud services. The other side of the equation is evidenced by Microsoft’s impressive latest earnings announcement driven in large part by its $40 Billion Azure business which grew at 73% last quarter – hard to post those kind of growth figures on a number that big <disclaimer: Microsoft is an investor in Unravel>

Rise of Big Data in the Cloud

I’ve written before about the rise of big data in the cloud, but Unravel has been doing a lot more than just talking about this shift. We’ve taken significant steps to support the transition of data workloads to the cloud. Unravel has forged partnerships with Azure and AWS, and our solution for migration and management of data workloads is available on both platforms. We have a particularly deep relationship with Azure and M12 (Microsoft’s investment arm) who participated in both Unravel’s Series B and Series C funding rounds. Unravel caught Azure’s eye precisely because of the need to solve these large scale operational data issues wherever the workloads are being executed.

With Unravel you get complete visibility into every aspect of your data pipelines:

• Is application code executing optimally (or failing)?
• Are resources being used, abused or constrained?
• How do I lower my cloud instance costs?
• Which workloads should I migrate to cloud first and what’s the performance/cost tradeoff?
• What are specific application and workload costs for Chargeback?
• Where are all my workloads being executed?
• How are all my services being utilized?
• How are users behaving and who are the bad actors?

These issues apply as much to systems located in the cloud as they do to systems on-premises. This is true for the breadth of public cloud deployment types:

• IaaS (Infrastructure as a Service): Cloudera, Hortonworks or MapR data platforms deployed on cloud VMs where your modern data applications are running
• PaaS (Platform as a Service): Managed Hadoop/Spark Platforms like AWS Elastic MapReduce (EMR), Azure HDInsight, Google Cloud Dataproc, etc.
• Cloud-Native: Products like Amazon Redshift, Azure Databricks, AWS Databricks, etc.
• Serverless: Ready-to-use services that require no setup like Amazon Athena, Google BigQuery, Google Cloud DataFlow, etc.

For those interested in learning more about specific services offered by the cloud platform providers we recently posted a blog on “Understanding Cloud Data Services.”

We introduced a portfolio of capabilities that help customers plan, migrate, and manage modern data applications running on AWS, Microsoft Azure and the Google Cloud Platform and we have talk frequently about what it takes to “Migrate and scale data pipelines on the AWS Platform” and about “Getting the most from data applications in the cloud.”

Building Expertise in Data Operations

No matter if you are running an on-premises system such as Cloudera or a fully managed PaaS environment such as Azure HDInsight or AWS EMR, or some hybrid combination, companies need to build expertise in data operations. DataOps is the discipline that ensures you are future proofing your architectural, operational and commercial decisions as you transform your business and migrate data workloads to the cloud, go straight to the cloud for new workloads, maintain an application on-premises or any hybrid combination.

Planning for Cloud-based Data Services

So, wherever you are on your cloud adoption and workload migration journey, now is the time to start or accelerate your strategic thinking and execution planning for cloud-based data services. Very recent history shows us that we need to be proactive, not reactive, and to expect this pace of change to continue to accelerate.

However, as migration goes from planning to reality, ensure that you invest in the critical skills, technology and process changes to establish a data operations center of excellence and future proof your critical data applications and systems.

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