Upcoming Webinars

September 27, 2022

Cloud cost optimization is the process of reducing your overall cloud spend by identifying mismanaged resources, eliminating waste, and right-sizing computing services to scale. Gartner recently estimated that 70% of cloud overspending can be attributed to companies that do not have a defined plan for cloud cost management. Fortunately, there are many best practices for cloud cost optimization. Join Pepperdata Engineer Chaitanya Patel to discuss the key best practices for cloud cost management and optimization.

September 28, 2022

Join your host, Minami Rojas, Moogsoft’s VP of Growth and Marketing, and her panelists, Moogsoft CEO, Phil Tee, and lead researcher, Helen Beal to hear their insights into what the data in The State of Availability Report tells them about what teams and leaders must learn to assure their organizations’ futures.
Key takeaways:
- The true cost of availability—and why it hurts
- The things that need to change to break the locks of the incident management cage
- What happens when teams are set free and what does it mean for organizational performance

On-Demand Webinars

Join Jason Bloomberg, President of Industry Analyst Firm Intellyx, and Shailesh Manjrekar, VP of AI & SaaS Marketing at CloudFabrix, as they explain the need for a new AIOps operating model that leverages composable analytics. Attendees of this webinar will:
1. Gain a clear understanding of multicloud, hybrid IT, and hybrid multicloud, and how edge computing impacts all of them.
2. Learn about the new AIOps operating model that is essential for managing the modern IT landscape.
3. Understand how composable analytics is part of the AIOps operating model, catering to these personas and provides out of the box dashboards for the exact view of the operational environment as well as centralized AIOps policy and administration views.

Join Pepperdata Product Manager Heidi Carson for a webinar addressing the discipline and best practices of cost optimization and why cloud data control and optimization are essential to your organization’s digital future. Learn some best practices and techniques to increase cost efficiency and maximize business value.

A modern platform helps you deliver actionable insights to your organization — insights that were previously unavailable or weren’t delivered in a timely manner. These insights help you to overcome cost and resource inefficiencies by reducing data complexity and enabling powerful self-service capabilities. Moving to a modern platform can also provide observability and autonomous optimization, and helps your organization move from reactive to proactive. Join Joel Stewart, VP of Customer Success at Pepperdata for this session as he uses real-world use cases and learn the following:
- Key success factors to ensure a successful migration
- The key players in data stack modernization
- Thinking beyond traditional needs to consider architecture trends like self-service analytics that empower line-of-business professionals to perform queries and generate reports on their own
- Automation, optimization, new techniques, and tools

Access all the presentations from the Robotic Data Automation Fabric & AIOps Conference.

Monitoring cloud platforms and containers while optimizing performance is an almost impossible challenge for the DevOps team without resource optimization and observability. Join Pepperdata engineers Shekhar Gupta and Chai Patel for a discussion on reducing your overall cloud spend. Learn how to achieve automatic cost savings through real-world examples and best practices.

In this webinar, learn about an automated, scalable solution that helps customers optimize big data performance and meet the demands of their analytics and big data stakeholders. Learn how to:
- Identify opportunities to increase efficiency
- Identify opportunities to go from reactive to proactive
- Understand correlation resources being consumed and workloads
- Avoid issues and remediate issues quickly.
- Balance performance goals versus resource availability

Monitoring cloud platforms and containers while optimizing performance is an almost impossible challenge for the DevOps team without resource optimization and observability. Are your existing processes and tools sufficient? Join Pepperdata Product Manager Heidi Carson for a webinar where you will learn how observability can help your team to drive better decisions and results. Learn how to monitor and optimize your entire stack at any scale in one place. Learn:
- Where most companies are at when it comes to observability
- Which types of observability tools are the best for cloud environments
- Observability to validate in support of optimization
- The importance of automation and automatic optimization
- The most important observability capabilities for DevOps teams
- Whether observability drives better business decisions

On May 18, join hundreds of people who will come together for RESOLVE, an event specifically designed around the IT Ops, NOC, DevOps or SRE community. Whether you join the highly-interactive forum online or at one of the in-person watch parties, you don’t want to miss this half-day conference. Now in its third year, RESOLVE ‘22 is where you can hear from, talk with, and ask questions of your peers while learning how they are addressing similar challenges that you are facing. Set aside four hours and get three enlightening keynote discussions, twelve sessions with real-world practices from your peers, real networking opportunities, a job board, and loads of tools to help you understand what is happening with AI for IT Ops, how to automate incident management, how to handle hybrid/multi-cloud, and more.

Join this webinar and learn how to:
- Overcome the visibility and performance challenges of Kubernetes performance management.
- Meet the demands of both complex and new microservices apps while maintaining legacy apps.
- Deploy, manage, monitor, and simplify big data analytics monitoring, platform monitoring, and dynamic optimization.
- Utilize five best practices to improve Kubernetes performance and reduce your overall spend.
- Reduce the complexity of monitoring and managing Kubernetes with automatic optimization

Spark on Kubernetes is growing in popularity due to improved isolation, better resource sharing, and the ability to leverage homogeneous and cloud-native infrastructure for the entire stack. However, running Spark on Kubernetes in a stable, performant, cost-efficient, and secure manner still presents complex challenges. In this webinar, Alex Pierce discusses the key performance metrics to focus on when monitoring and optimizing Spark performance on Kubernetes.Topics include:
- Automation and observability for lowering costs and improving performance
- Deploying, managing, monitoring, and simplifying Spark on Kubernetes: big data application monitoring, platform monitoring, and dynamic optimization
- Configuring for performance and efficiency
- Spark app-level dynamic allocation and cluster level autoscaling
- The fastest way to improve Spark on Kubernetes performance

Monitoring cloud platforms and containers while optimizing performance is an almost impossible challenge for the DevOps team without resource optimization and observability. Are your existing processes and tools sufficient? Join Pepperdata Product Manager Heidi Carson for a webinar where you will learn how observability can help your team to drive better decisions and results. Learn how to monitor and optimize your entire stack at any scale in one place. Learn:
- Where most companies are at when it comes to observability
- Which types of observability tools are the best for cloud environments
- Observability to validate in support of optimization
- The importance of automation and automatic optimization
- The most important observability capabilities for DevOps teams
- Whether observability drives better business decisions

Join Pepperdata Engineers Alex Pierce and Shekhar Gupta for a discussion on how to reduce your overall cloud spend with Kubernetes capacity optimization. Learn how to achieve automatic cost savings through real-world examples and the following best practices:
- Automatic optimization
- Efficiently managing capacity by identifying mismanaged resources
- Eliminating waste and recapturing unused capacity
- Observability, alerts, and job-specific recommendations for Spark

Without visibility and a good IT chargeback model, your cloud costs can quickly spiral out of control. Implementing IT chargeback ensures that everyone knows where their IT budget is going and how they are using it. It allows you to see which departments and workloads are using the most resources and gives you control over your cloud spending. Join this webinar and learn how to:
- Get visibility and control your cloud costs.
- Track cloud resource usage, track costs, and assess trends.
- Understand the cost of shared cluster resources over any period of time.
- View and charge business units for consumption.

Join this discussion of best practices for monitoring and improving Kubernetes visibility and performance. You’ll learn how to:
- Overcome the challenges of Kubernetes performance management.
- Meet the demands of both complex and new microservices apps while maintaining legacy apps.
- Deploy, manage, monitor, and simplify big data analytics monitoring, platform monitoring, and dynamic optimization.
- Utilize five best practices to improve Kubernetes performance and reduce your overall spend.

Join Lead Gartner Analyst, Pankaj Prasad, who will cover the state of the AIOps market, and where he sees the industry going over the coming years. Moderated by John Haley, VP of Marketing at Moogsoft, together they will deliver an informative session and discuss the criticality of AIOps as companies continue to adopt new technologies. Hear how modern companies strive for operational efficiencies while maintaining high availability and customer satisfaction. To wrap up, Phil Tee, CEO of Moogsoft, who will briefly discuss Moogsoft’s perspective and what’s in store for 2022. Here are key takeaways you will learn from tuning in to our strategic advisory session with Gartner:
1. How digital businesses are becoming observable
2. How AIOps allows for continuous insights across ITOM
3. How monitoring is converging with AIOps

This webinar discusses best practices to maintain optimal performance for Kafka data streaming and includes the following topics:
– Apache Kafka cluster components: producers, consumers, and brokers
– Key Kafka performance metrics: throughput and latency
– Kafka performance tuning: tuning brokers, producers, and consumers
– Offline partitioning
– Balancing Apache Kafka clusters
– Optimizing Kafka performance

In this self-guided demo, you’ll learn how to:
- Improve application performance and reduce waste.
- Significantly improve your current AWS autoscaling.
- Get job-specific recommendations to optimize Spark performance.
- Customize alerts to quickly troubleshoot application and infrastructure issues.

Although Docker and Kubernetes are now becoming standard components for building and orchestrating applications, you are still responsible for managing application performance across the stack, and an increasing area of focus in IT is finding a way to monitor, manage, and find opportunities for optimization across these sprawling big data environments. Join this webinar to learn how to:
– Identify Kubernetes challenges: virtualization, distributed applications, and multi-cloud
– Meet the demands of new microservices apps while maintaining legacy apps
– Deploy, manage, monitor, and simplify: big data analytics monitoring, automation, platform monitoring, and dynamic optimization
– Reduce the complexity of monitoring and managing Kubernetes with full-stack observability
– Find and capitalize on optimization opportunities

Join Best-Selling Author Nigel Poulton to learn what Kubernetes is, why it's central to the future of cloud-native infrastructure and applications, and what it means to your career. Participate in the Q and A that follows the webinar for a chance to win a free copy of Quick Start Kubernetes.

This year BigPanda is hosting its customer festival over two days, and it’s all online, so you and your team can participate wherever you are. Each day, Pandapalooza will take place two and a half hours to talk about where customers are in their AIOps journey, get product updates and share best practices in event correlation, triage, root cause analysis, automation and reporting/analytics. Each session will be fast and engaging – and you will walk away with lots of ideas on how to increase the value BigPanda delivers to your organization.

Join Pepperdata Field Engineer Kirk Lewis for this discussion about operational challenges associated with maintaining optimal big data performance in the cloud with a focus on Google Dataproc, what milestones to set, and best practices for managing a successful cloud framework.

In this webinar, we’ll discuss how to prepare and ensure that your organization has a solid plan to manage big data analytics in the cloud. Topics include:
– Primary characteristics of big data and putting your data in the cloud
– The challenges of managing big data performance in the cloud
– FinOps (chargeback, analyzing wasted spend)
– Planning for day 2
– Achieving cloud performance
– Observability, continuous tuning, and managed autoscaling

Join Pepperdata Field Engineer Alex Pierce as he discusses how to reduce the complexity of monitoring and managing Spark on Kubernetes with autonomous optimization and full-stack observability. Topics include:
• Automation and observability for lowering costs and improving performance
• Deploying, managing, monitoring, and simplifying Spark on Kubernetes: big data application monitoring, platform monitoring, and dynamic optimization
• Configuring for performance and efficiency
• Spark app-level dynamic allocation and cluster level autoscaling
• What Spark on Kubernetes performance success looks like

Join Pepperdata Field Engineer Alex Pierce for a webinar on gaining visibility into cloud GPU resource utilization at the application level and improving the performance of your GPU-accelerated big data applications. Topics include:
- Why GPU-accelerated big data applications are going mainstream
- Getting visibility into GPU memory usage and waste
- Fine-tuning GPU usage through end-user recommendations
- Manage costs at a granular level: attributing usage and cost to specific end-users
- Monitoring and eliminating waste with GPU monitoring solutions

Join Pepperdata VP of Customer Success Joel Stewart as he discusses how to navigate through the noise of big data cloud performance recommendations and more efficiently manage big data performance.

On August 26, 2021, attend this free 30-minute BigPanda webinar and find out why event enrichment is either a landmine or linchpin for successful AIOPs efforts. First, you will hear from Sid Roy, VP of Operations and Client Support at Scicom, who will explain why many AIOps projects fail to live up to their promise because alerts don’t get enriched with operational, topological or other contextual data, making it difficult to separate noisy alerts from meaningful alerts, and then eliminate the noise. Next, meet Samy Senthivel, Sr. Digital Enterprise Monitoring Services Manager at AutoDesk. Learn how his team uses technology to structure their event data and add more context to alerts so their Operations team can triage issues quickly and achieve better alert compression rates. Moderated by Anirban Chatterjee, Director of Product Marketing at BigPanda, this conversation will leave attendees with important things to consider as they evaluate AIOps solutions.

Are you getting the best price/performance from your big data cloud solution? Which cloud performance benchmarks do you use? Using cloud performance benchmarks and measuring your performance are key to understanding price/performance. This webinar will discuss the importance of understanding key benchmark metrics and how you can use benchmarking to improve performance. Learn the following:
- Current big data benchmarking methods and trends
- Preferred benchmarking datasets
- Best practices for evaluating benchmarking reports

In this webinar, Alex Pierce will talk about how to optimize Spark performance on Kubernetes. Topics include:
– Making Spark-on-k8s reliable at scale
– Core concepts and setup of Spark on Kubernetes
– Configuration tips for performance and efficient resource sharing
– Spark-app level dynamic allocation and cluster level autoscaling
– Monitoring and security best practices

Face and eliminate your worst big data nightmare with Pepperdata Field Engineer Kirk Lewis as he presents best practices for automatic optimization, cloud efficiency, and cost optimization. Topics include:
- Optimizing your modern big data architecture
- Delivering deep insight from across more data sources and types
- Managing the increased velocity of analytics requests, across the cloud and on premises
- Controlling costs and resources while supporting more users who want self-service capabilities
- Meeting the needs of data scientists and data analysts

Join Pepperdata Field Engineer Alex Pierce for this webinar on Presto performance management best practices to learn:
—When to use Presto versus other engines
—Key criteria to look for in a query engine for interactive analytics
—Visibility into all of your queries in one place with continuous, automated application and infrastructure tuning
—How to enable self-service access to your data lake
—How to Immediately improve and scale application performance through automated tuning
—How to Improve query performance through job-specific recommendations, query run comparisons, and IT chargeback reports

Join Pepperdata Field Engineer Alex Pierce for this discussion about operational challenges associated with maintaining optimal big data performance in the cloud, what milestones to set, and recommendations on how to create a successful cloud migration framework. Learn the following:
– Autoscaling types
– Autoscaling strengths and weaknesses
– When to use autoscaling and what autoscaling does well
– Is traditional autoscaling limiting your success?
– What is optimized cloud autoscaling?

Big data self-service analytics is the solution to two critical issues: the proliferation of data and the subsequent shortage of data scientists to capture, manage, and analyze it all. To bridge the gaps and to take business analytics beyond what legacy reporting tools can do, many organizations are implementing self-service solutions that enable users to extract more value from ever-growing data volumes. When today’s cloud platforms are combined with modern big data performance solutions, data analysis power users can leverage self-service to gain business insights, optimize scaling, and create a unified interface to simplify analysis. Join us as we discuss the best practices for simplifying big data analytics while providing data analysts and scientists with self-service access on AWS cloud. Watch this webinar to:
• Understand why more organizations are moving to the self-service analytics model.
• Learn how to more easily create elastic Hadoop, Spark, and other big data clusters for dynamic, large-scale workloads.
• Learn the best practices for cost optimization of big data workloads.
• Understand how to evaluate big data SaaS criteria and determine whether “as-a-service” is right for your organization.

This webinar discusses best practices to overcome critical performance challenges for Kafka data streaming that can negatively impact the usability, operation, and maintenance of the platform, as well as the data and devices connected to it. Topics include: Kafka data streaming architecture, key monitoring metrics, offline partitioning, broker, topics, consumer groups, and topic lag.

This webinar explores the results of analyzing thousands of Spark jobs on many multi-tenant production clusters. The webinar will focus on common issues, the symptoms of those issues, and how you can address and overcome them without thinking too hard. Topics include best and worst practices, gotchas, machine learning, and tuning recommendations.

In this webinar, we’ll discuss how to prepare and ensure that your organization has a solid plan to manage big data analytics in the cloud. Topics include:
– Primary characteristics of big data and putting your data in the cloud
– The challenges of managing big data performance in the cloud
– FinOps (chargeback, analyzing wasted spend)
– Planning for day 2
– Achieving cloud performance
– Observability, continuous tuning, and managed autoscaling

During this webinar, hear from industry leaders, Ahmed Kamran Imadi, Big Data Solutions Engineering at Fortune 100 Financial Institution, Mark Kidwell, Chief Data Architect at Autodesk, Satish Nekkalapudi, Sr. Manager at Magnite, and VP of Customer Success Joel Stewart at Pepperdata about what role big data is playing in their business today and how they are adapting their IT ops and development teams to keep pace with change. Topics include:
- What will be big data’s role in the future for business and how will IT adapt and grow?
- How will the growth in big data affect IT ops and developer processes today?
- Will this change skill sets for these roles?
- What skills will be needed in IT as the need for big data increases?

Join Pepperdata Field Engineer Kirk Lewis for this discussion about operational challenges associated with maintaining optimal big data performance in the cloud, what milestones to set, and recommendations on how to create a successful cloud migration framework. Learn the following:
– What are the types of autoscaling?
– What does autoscaling do well?
– When should you use autoscaling?
– Does traditional autoscaling limit your success?
– What is optimized cloud autoscaling?

Running Spark on Kubernetes is growing in popularity. Reasons for the growth are improved isolation, better resource sharing, and the ability to leverage homogeneous and cloud-native infrastructure for the entire stack. But running Spark on Kubernetes in a stable, performant, cost-efficient, and secure manner also presents specific challenges. In this webinar, Alex Pierce will talk about how to optimize Spark performance on Kubernetes. Topics include:
– Making Spark-on-k8s reliable at scale
– Core concepts and setup of Spark on Kubernetes
– Configuration tips for performance and efficient resource sharing
– Spark-app level dynamic allocation and cluster level autoscaling
– Monitoring and security best practices

This webinar draws on experiences across dozens of production deployments and explores the best practices for managing Apache Spark performance. Learn how to avoid common mistakes, improve the usability, supportability and performance of Spark. Topics include:
– Serialization
– Partition sizes
– Executor resource sizing
– DAG management

This webinar considers key aspects of cloud system observability and management, including cost management, ensuring compliance with agreed service-level agreements (SLAs), and balancing cloud resource usage to optimize performance. Attendees will learn about:
- The concept of observability for overseeing cloud-based big data applications
- Efficiently and autonomously optimizing big data environments at scale
- Automating performance analysis to help identify performance issues
- Determining where system complexity introduces congestion and bottlenecks that impact observing SLAs
- Understanding cloud service use and optimizing cloud service costs

With many companies prioritizing containers for more applications and more uses, an increasing area of concern for everyone in IT is finding a way to monitor, manage, and optimize performance across these sprawling environments. Join this webinar to learn:
– A brief history of current trends in computing, cloud, containerization, and Kubernetes
– Challenges: virtualization, distributed applications, and multi-cloud
– How to meet the demands of new microservices apps while maintaining legacy apps
– How to deploy, manage, monitor, and simplify: big data analytics monitoring, platform monitoring, and dynamic optimization
– Ways to reduce the complexity of monitoring and managing Kubernetes with automated full-stack observability
– What Kubernetes performance management success looks like

RESOLVE '21 is the only virtual conference designed exclusively for IT Ops, NOC, DevOps and SRE professionals who are creating the next-gen operations environment with AIOps, machine learning, automation and world-class incident management. BigPanda is excited to announce keynote speaker, Steve Wozniak, along with an agenda packed with networking opportunities, eight breakout sessions, games and more.

In this panel discussion, IT Ops pros from NTT Data, WEC Energy Group, Machinify and Blackrock 3 Partners provide insights on what IT Operations will look like in 2021 and how it will continue to evolve.Topics covered in this 45-minute session include:
- Remote workforce
- AI and Automation
- ITIL model
- Adopting SRE models
- New skills
- Big ideas for 2021

Join Anirban Chatterjee, Director of Product Marketing for BigPanda and Waldo Grunenwald, Technical Evangelist, Datadog as they discuss:
- transformation projects IT Ops customers they are working with are undertaking
- steps they are taking to accelerate those projects
- how they use modern observability, event correlation and automation solutions with AIOps to stay ahead of whatever 2021 brings them.

IDG conducted a survey of IT professionals examining how IT Ops teams have been impacted as the demand for digital services has skyrocketed since the start of the pandemic. During this webinar will present the survey findings as well as look at how IT Ops teams are planning for 2021 with a remote workforce model that is here to stay for the foreseeable future.

In this session, you will hear from Expedia, the World’s Travel Platform, on how they modernized Operations on one of the world's fastest-moving IT stacks, and why they chose the BigPanda AIOps platform to help them with their mission.