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Review the top sessions from recent cloud conferences
Build your own cloud conference from home. Watch sessions from the past year to learn about modern application architecture, cloud security, machine learning and cost management.
If there's a silver lining to social distancing, it's the fact that it gives us a chance to catch up on content we otherwise might have missed. There are always too many sessions to attend at cloud conferences -- from service introductions and updates to best practices and use cases -- that could change the way you use cloud technologies.
The global health crisis has made it unlikely any of us will gather for a conference in 2020. Given the dangers of COVID-19, it seems unwise for thousands of professionals from around the world to gather in a crowded convention center.
While the in-person conference experience is off the table for the near future, there are plenty of resources still available to review from cloud conferences over the past year. There are also upcoming digital conferences like Google Cloud Next '20, set to start July 14 and continue into September.
Here, you'll find a collection of sessions from AWS re:Invent 2019, Google Cloud Next '19, Microsoft Ignite 2019 and Microsoft Build 2020, which was held virtually this past May.
To better replicate the conference experience, these sessions are organized into a schedule that follows four tracks -- modern application infrastructure, cloud security, machine learning and cost management. The schedule starts with service introductions followed by best practices and use cases. You can follow the schedule based on the track or cloud provider that interests you.
So, fix yourself a continental breakfast and get started.
Cloud service deep dives
9-10 a.m.
Modern application infrastructure
AWS re:Invent
This talk walks you through the infrastructure behind Fargate, AWS' compute engine for containers. With Fargate, users can run containers on AWS without having to provision virtual machines. In this session, you will learn how AWS built the service. Use that knowledge to better inform your use of Fargate.
Security
Microsoft Ignite
"Security in overdrive! Best practices for configuring Microsoft Defender ATP"
Explore the security capabilities of Microsoft Defender, the best practices for getting the most out of this centralized security tool, and how security and IT admins can use it to collaborate.
Machine learning
AWS re:Invent
"Introducing Amazon SageMaker Studio"
Amazon SageMaker Studio is an integrated development environment used to build, train, tune, debug, deploy and monitor machine learning models. Watch this introduction to see how this service works.
Cost management
Google Cloud Next
"Creating interactive cost and KPI dashboards using BigQuery"
BigQuery is a serverless data warehouse that works with Google Cloud Storage. Learn how to export billing data to BigQuery and visualize cost trends in this 2019 cloud conference session.
10-10:30 a.m.
Modern application infrastructure
Microsoft Build
"Azure Arc and Kubernetes: A developer story"
Azure Arc is a hybrid cloud management platform that supports Kubernetes clusters across different clouds, data centers and edge locations. Learn how Kubernetes is central to Microsoft Azure Arc's hybrid cloud capability.
Cloud security
Google Cloud Next
"Detecting threats in logs at cloud scale"
This talk explains how you can use Event Threat Detection to analyze Stackdriver logs for malware, phishing, cryptomining and more. It includes a live demo on how to catch a cryptominer.
Machine learning
Google Cloud Next
"What's new with TensorFlow, and how GCP developers benefit"
TensorFlow is an open source platform developed by Google for machine learning. This session goes over how Google has used the framework to build its AI offerings and how you can use it to deploy a machine learning model.
Cost management
Microsoft Ignite
"Manage and optimize your cloud cost with Azure Cost Management"
Cost management visibility is an often overlooked aspect of cloud management. This session explains how to use Azure Cost Management to dig into your Azure expenses and make it more accessible across your organization.
10:30-11 a.m.: Break
Best practices
11 a.m. - 12 p.m.
Modern application infrastructure
AWS re:Invent
"Building microservices with AWS Lambda"
This cloud conference session unites two concepts that are core to modern application infrastructure -- microservices and serverless. Explore how to map a microservices-based architecture to AWS Lambda's event-driven, serverless model.
Cloud security
AWS re:Invent
"Getting started with AWS identity"
This talk goes over the fundamentals of identity and access management (IAM) on AWS. The speaker, Becky Weiss, a senior principal engineer at AWS, breaks down how to set up IAM policies and permissions across AWS accounts. This session is essential for beginners and useful for experienced IT pros to review.
Machine learning
Google Cloud Next
"ML Ops best practices in Google Cloud"
Operations teams often struggle with the complexities of maintaining machine learning models. This talk explores the concept of ML Ops -- aka DevOps for ML -- and how you can use tools like Kubeflow Pipelines to manage complicated machine processes, such as continuous training and automated model validation.
Cost management
Microsoft Build
"Evaluate and optimize your costs using the Microsoft Azure Well-Architected Framework"
"Working with Azure cost management APIs"
These two Microsoft Build sessions pair well together and should cover the allotted hour. The first session outlines the first pillar of the Microsoft Azure Well-Architected Framework -- cost optimization. It goes through a number of Azure tools and practices to make sure you only pay for what you use and need. The second session is a detailed demo on the Azure Cost Management APIs and shows viewers how to set up budget reports, alerts and more.
12-1 p.m.: Lunch
1-1:45 p.m.
Modern application infrastructure
Google Cloud Next
"Migrating a monolithic application to microservices"
Many enterprises will identify with the subject of this cloud conference session. It explains how Google Cloud's Release Engineering team migrated a monolithic application to microservices, as well as the tools and practices it found most useful during that process.
Cloud security
Microsoft Ignite
"Top 10 best security best practices for Azure today"
This talk goes over attack monitoring, choosing the right firewall strategy, retiring legacy technology and other best practices. It also explains how Azure security services, such as Azure Sentinel, fit into these strategies.
Machine learning
AWS re:Invent
"Future-proof your career: Java dev to machine-learning practitioner"
In this session, Kesha Williams, an AWS Machine Learning Hero, explains her career pivot from Java developer to machine learning practitioner. It's a good intro to AWS' machine learning services DeepLens, Rekognition and SageMaker. She also shows how you can apply your skills in Java to work with machine learning tools like TensorFlow and Jupyter.
Cost Management
Microsoft Ignite
"Make the most of Azure to reduce your cloud spend"
A typical enterprise runs a few different kinds of workloads on Azure, such as web servers, services with fluctuating usage and applications with constant usage. This talk explores how you can tailor Azure compute to your needs and budget, with features like low priority and Spot VMs and tools like Azure Advisor.
1:45-2:45 p.m.
Modern application infrastructure
AWS re:Invent
"Serverless architectural patterns and best practices"
Serverless isn't going to be the right fit for every application. This talk identifies some of most common serverless architectural patterns, with some interesting monikers like "the cherry-pick," "call me Maybe," and "the big Fan," among others. Gain a better grasp on how enterprises can stitch these patterns together.
Cloud security
Google Cloud Next
"Keeping hackers out and your data secure: A proactive approach to G Suite security"
This talk examines the lessons and best practices that the G Suite higher education team learned working with universities and how these lessons can be applied to any enterprise running Google in the cloud.
Machine learning
Microsoft Build
"Responsible ML: Getting started and analyzing your models"
"Researching, building and consuming responsible ML"
These two Microsoft Build sessions explore a recent Microsoft Azure initiative -- responsible machine learning. The focus is on building models in Azure Machine Learning that limit data exposure and promote responsibility.
Cost management
AWS re:Invent
"Guidelines and design patterns for optimizing cost in Amazon S3"
This talk goes over a few ways to lower storage costs in S3. It's not rocket science; it often comes down to simply picking the right S3 storage classes and monitoring your costs with AWS Budgets and Amazon CloudWatch.
2:45-3 p.m.: Break
Use cases
3-4 p.m.
Modern application architecture
AWS re:Invent
"A day in the life of a Netflix engineer"
Netflix is a high-profile AWS customer and a frequent presence at re:Invent. Netflix employees have given talks on how they design systems and tackle operational challenges. Netflix's scale and chaos engineering won't be applicable to most enterprises, but its approach and use of AWS technologies could give you some ideas.
Cloud security
Google Cloud Next
"How Airbnb secured access to their cloud with context-aware access"
Context-aware access, or the zero-trust security model, works well for enterprises that have complicated network and cloud requirements. In this use case, Samuel Keeley, a security engineer from Airbnb, explains how the company uses context-aware access tools to protect applications running on hybrid or multi-cloud environments.
Machine learning
AWS re:Invent
"How Rovio teaches Angry Birds to fly in the cloud using ML"
In this session, Rovio engineers explain how they use AWS to run their gaming operations. The use case explores how Rovio uses reinforcement learning to predict game difficulty.
Cost management
Google Cloud Next
"Better insight: Measuring the cost of an application on GCP"
An enterprise like Target generates a significant cloud bill. This use case examines how Target uses Stackdriver logging, Cloud Functions and other Google services to get a handle on its costs.
