DataOps Done Right: How to Optimize DataOps for the Cloud
Modern applications are powered by data that must first run through a gamut of software, systems, and technologies before being consumed by business users. DataOps represents an emerging discipline for designing, managing, and monitoring the flow of data from source to target. DataOps provides a level of rigor required to manage dozens or hundreds of data pipelines that potentially serve mission-critical applications with stringent service level agreements.
Today, companies want to run some or all of their data pipelines in the cloud or spanning cloud and non-cloud platforms. But how does that work in theory and in practice? How does a DataOps team manage the processes, technologies, and data when pipelines cross multiple environments? What does a DataOps for the cloud look like? This webcast will define DataOps, explore best practices, and discuss how DataOps can build and manage data pipelines in the cloud.
RecordedAug 6 201964 mins
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Chris Santiago, Solution Engineering Director, Unravel Data
Make your on-premise Hadoop platform faster, better & cheaper with Unravel by joining Chris Santiago, Solution Engineering Manager to learn how to reduce the time troubleshooting and the costs involved in operating your data platform. During this webinar we will demonstrate how Unravel complements and extends your existing on-premise data platform to:
Instantly understand why technologies such as Spark applications, Kafka jobs, and Impala underperform or even fail!
Define and meet enterprise service levels through proactive reporting and alerting.
Reduce the overall cost of Cloudera/MapR/Apache Hadoop/Spark through better cluster utilisation resulting to an immediate reduction in MTTI and MTTR
Inderjeet Singh, Solution Engineering, Unravel Data
Apache Spark is quickly becoming the default choice for AI operations. This webinar will focus on optimizing Apache Spark data pipelines to ensure organizations who depend on Spark meet their Service Level Agreements (SLAs). We will discuss:
Understanding Spark Memory Management
Data skew identification and best practices
Garbage collection techniques to debug slow or failing Spark jobs
Abha Jain, Senior Director of Products, Unravel Data
Azure Databricks has become very popular as a computing framework for big data. However, customers are finding unexpected costs eating into their cloud budget. Furthermore, lack of visibility to root cause and general inefficiency is costing organizations thousands, if not millions in operating their Azure Databricks environment.
Join Unravel to discuss new features to effectively help manage costs on Azure Databricks:
Cost analytics to provide assurance and forecasting for optimizing Databricks workloads as they scale.
Accurate, detailed chargeback reporting of the cost of running data apps on Azure Databricks.
Right-sizing recommendations to reveal the best virtual machine or workload types that will provide same performance on cheaper clusters.
Muji Qadri, Senior Solution Engineer, Unravel Data
Join Unravel to develop an understanding of the performance dynamics of modern data pipelines and applications. In this session, you will learn about uncovering and understanding the key datasets, metrics, and best practices needed to develop mastery with Spark performance management on-premise and in the Cloud.
Chris Santiago, Solution Engineering Director, Unravel Data
Running real-time data injection workloads on HBase clusters are always challenging. Timely, up-to-date, detailed data is crucial to locating and fixing issues to maintain a cluster's health and performance. Join us to learn how Unravel provides detailed data and metrics to help you identify the root causes of cluster and performance issues in Hbase.
Jason Baick, Senior Director of Product Marketing, Unravel; Javier Ramirez, Senior Developer Associate, AWS
Lack of agility, excessive costs, and administrative overhead are convincing on-premises Spark and Hadoop customers to migrate to cloud native services on AWS. As you’re migrating these applications to the cloud, Unravel helps ensure you won’t be flying blind.
Join AWS and Unravel as we discuss:
Top reasons customers choose AWS for their cloud migration journey,
Advantages of planning out your Hadoop migration to AWS,
Demo: Migration assessment capabilities to ensure risk-free migration.
Mick Nolen, Senior Solution Engineer, Unravel Data
Enterprises across all sectors have invested heavily in big data infrastructure (Hadoop, Impala, Spark, Kafka, etc.) to turn data into insights into business value. It is increasingly challenging for Data Ops teams to operate and maintain these clusters to meet business requirements and performance SLAs. Unravel helps organizations optimize performance, automate troubleshooting and contain costs - on premises or in the cloud. Register for a demo of Unravel for big data application performance management.
Abha Jain, Director of Products, Unravel Data; Shashi Raina, Partner Solution Architect at Amazon Web Services
According to Ovum research, over half of big data workloads will be running in the cloud by the end of this year (2019). Amazon EMR is an industry leading cloud-native big data platform that can easily run Apache Spark, Hadoop, Presto and Hive. Unravel for Amazon EMR provides a solution to deliver comprehensive monitoring, troubleshooting, and application performance management for Amazon EMR environments.
In this webinar, we will discuss:
Overview of Amazon EMR with common use cases;
Application Performance Management for Amazon EMR;
Comprehensive reporting, alerting, and recommendations for optimization
Chris Santiago, Solution Engineering Manager, Unravel Data
Whether you are looking to establish a “cloud first” strategy for big data or are migrating from on-premises Cloudera, Hortonworks, and MapR, this session provides practical insights on how to make that journey simple and cost effective on Azure. Join Chris Santiago as he shares how a data driven approach can guide you in deciding which cloud technologies will best fit the needs unique to your organisation and budget.
Abha Jain, Director of Products, Unravel Data; Ron Abellera, Microsoft Global Blackbelt Microsoft,
According to Ovum research, over half of big data workloads will be running in the cloud by the end of this year (2019). Microsoft Azure provides a number of options for powering your modern data estate with the flexibility and scalability of the cloud. AI driven, intelligent DataOps is critical to gain visibility to modern data operations. In this webinar, we will focus on:
Advantages of running modern data platforms in the cloud
The importance of visibility into your cloud data infrastructure
Demonstration of Unravel for Azure Databricks to manage DataOps on Azure
Try Unravel risk free with a 60 day license and up to $15K Free Azure for starting a Proof of Concept. Contact: email@example.com
As you’re migrating your Spark and Hadoop applications to Microsoft Azure, Unravel helps ensure you won’t be flying blind. With data-driven intelligence and recommendations for optimizing compute, memory, and storage resources, Unravel makes your transition a smooth one. Abha Jain, Director of Products at Unravel demonstrates how.
As you’re migrating your Spark and Hadoop applications to the cloud, Unravel helps ensure you won’t be flying blind. With data-driven intelligence and recommendations for optimizing compute, memory, and storage resources, Unravel makes your transition a smooth one. Abha Jain, Director of Products at Unravel demonstrates how.
Aengus Rooney, Head of Solution Engineering - International, Unravel Data
Join Unravel expert Aengus Rooney to develop an understanding of the performance dynamics of modern data pipelines and applications. In this session, you will learn about uncovering and understanding the key datasets, metrics, and best practices needed to develop mastery with Spark performance management on Azure Databricks.
AI-powered performance management for your modern data applications.
At Unravel, we see an urgent need to help every business understand and optimize the performance of their applications, while managing data operations with greater insight, intelligence, and automation.
For these businesses, Unravel is the AI-powered data operations company. We offer novel solutions that leverage AI, machine learning, and advanced analytics to help you fully operationalize the way you drive predictable performance in your modern data applications and pipelines.
DataOps Done Right: How to Optimize DataOps for the CloudGeorge Demarest, Senior Director of Product Marketing, Unravel; Wayne W. Eckerson; Eckerson Group[[ webcastStartDate * 1000 | amDateFormat: 'MMM D YYYY h:mm a' ]]64 mins