Better monitoring and logging for Compute Engine VMs

Over the past several months we’ve been focused on improving observability and operations workflows for Compute Engine. Today, we are excited to share the first wave of these enhancements are now available. These include:Significantly improved operating system support for the Cloud Monitoring and Cloud Logging agents.The ability to rapidly deploy, update, and remove agents to groups of VMs, or all of your VMs, by policy, with as little as a single gcloud command.New VM-specific features within the Cloud Monitoring console, which we’ll discuss in an upcoming blog post.Understanding agentsAgents remain a key way to get fine-grained visibility into a virtual machine’s host operating system, and applications running on Compute Engine are no different. Out of the box, every Compute Engine instance (or managed instance group) provides some level of telemetry, including metrics for CPU utilization, uptime, disk throughput and operations, and networking operations. To capture more advanced operating system metrics like memory consumption and disk utilization, metrics from commonly used applications (databases, web proxies, etc.), and logs from your applications, you need to install the Cloud Monitoring and Cloud Logging agents onto each VM.Automatic agent installation and managementBecause agents are so essential in VM environments, we’veautomated the process of installing, updating, and removing the Cloud Monitoring Logging agents onto groups of Compute Engine VMs, or your entire fleet, via a new set of gcloud commands. With as little as one command, you can create a policy that governs existing and new VMs, ensuring proper installation and optional auto-upgrade of both agents. This is a great way to start using Cloud Monitoring or Cloud Logging right away, and to scale metrics and logs collection from a single VM to all VMs in a project.These policies can be applied to Linux virtual machines now as a part of the public alpha and will apply to Windows VMs soon.Improved operating system supportOver the past year, we’ve added Cloud Monitoring and Logging agent support to a host of new operating systems.LinuxThe Monitoring and Logging agents are now compatible with 30 of Compute Engine’s available Linux images, including:CentOS 7+Red Hat Enterprise Linux 7+Debian 9+SUSE Linux Enterprise Server 12+Ubuntu 16+With these additions, the Cloud Monitoring Linux agents can be used on every Compute Engine host operating system other than the Container Optimized OS, which has monitoring and logging capabilities built in to the OS itself.WindowsCloud Monitoring has been able to capture system and SQL Server metrics for Windows virtual machines since before 2015, thanks to its Windows agent. We’re currently improving the compatibility, quality, and functionality of our Windows support with a new agent that provides the following enhancements:Capturing the same advanced OS metrics as the Cloud Monitoring Linux agent, rather than a smaller incompatible setCompatibility with more Windows versionsCapturing application metrics from IIS, SQL Server, and Windows performance countersThe new agent is in preview. Please contact your account manager if you would like to participate in early tests.Wrapping upWe hope you enjoy these improvements to Cloud Monitoring and Cloud Logging, and we look forward to bringing even more capabilities to the platform. To check out these new features, go to our documentation for these new features or to the Cloud Monitoring and Logging in the Google Cloud Console.Related ArticleAll together now: Fleet-wide monitoring for your Compute Engine VMsCloud Monitoring now lets you manage an entire fleet of Compute Engine VMs.Read Article
Quelle: Google Cloud Platform

Introducing Student Success Services from Google Cloud

The shift to remote learning at all levels of education has thrown the challenges of ensuring student success and the student experience into sharp focus. Educational institutions want to guide students throughout their academic careers and improve graduation rates. Students want better remote learning options and ways to collaborate with peers and seek advice from instructors. There is a wealth of data that could drive decisions about these needs, but it’s often locked away in legacy technologies. We have launched Google Cloud’s Student Success Services to help meet these challenges. Student Success Services is a set of tools that aims to unlock student successes with personalized assistants, real-time insights, collaboration tools and more for higher ed and K-12 learners. Using built-in artificial intelligence (AI) models and analytics to gather data and use it for decision-making, this bundle of services benefits both institutions and students by engaging students, improving remote and in-person learning, and creating a modern, fulfilling student experience.How to improve the student experienceGoogle Cloud’s Student Success Services includes the following services that help institutions understand student needs and quickly respond with solutions:Virtual assistants for round-the-clock support: Use virtual assistants, created with Google’s machine learning and natural language tools, to support students 24/7 with instant answers. The virtual assistants can be trained to respond instantly to questions on topics like enrollment status and registration deadlines, freeing up staff for more personal student guidance.Tutors for personalized learning: Give students access to skills practice and guidance from intelligent technology tools. Our APIs and AI-powered learning tools can guide students in their writing practice or coaching for reading comprehension.Smart analytics to improve student engagement, achievement, and retention: The Unizin Data Platform, built on Google Cloud, is an institution-level data platform that aggregates, cleans, models, and stores all teaching and learning data to create a holistic view of the student. Too often, advisors and educators don’t have the information on the students they support until it’s too late to intervene. Google’s Student Success Services allow organizations to easily and securely share aggregate data and enables them to see a unified portrait of learners, uncover insights across diverse student groups at every level, and intervene in real time.Scalable student learning: Distance shouldn’t be a barrier to student success. Google Meet allows groups of up to 250 people to talk face-to-face for classroom learning as well as employee meetings, in compliance with regulations such as HIPAA and FERPA. With Meet’s premium features, meeting leaders can add closed-captioning and recording, while sharing meetings via learning management systems. For schools that rely on live streams, Meet can accommodate up to 100,000 viewers. And with virtual desktop infrastructure (VDI) remote learning solutions for distance learners, educators can create virtual labs and access compute power remotely.Incidence and intelligence management: Get real-time insights to detect issues and rapidly respond to risks on and off campus, as well as track student and campus health.“We believe that a data-informed academic mission must play an essential role in helping every student reach their potential. Every week, we see our institutions leveraging the Unizin Data Platform to engage, enrich, and empower their students with data, analytics, and insights” says Etienne Pelaprat, Chief Technology Officer of Unizin.Creating an equitable playing field for student success is also a goal of the University of Lynchburg in Virginia. “We have students learning with us from all over the world, especially in our online graduate programs,” says Charley Butcher, the university’s director of instructional technology. Those students can join classes using Meet and a web browser from anywhere they happen to be—a benefit at any time, but especially now when remote classes are often the only option for students. And it’s not just graduate students: During the pandemic-related campus shutdown, Meet is helping all students work closely with their instructors.The need to lift student success is certainly critical right now—but when the pandemic recedes, educators will likely still be adjusting to very different learning environments for their students. “In this year of disruption, we’ve seen just how much technology can impact the student experience. As teaching and learning become more digital, institutions must prioritize innovation and technology. This should go beyond learning platforms and include capabilities like artificial intelligence and predictive analytics – supports that students increasingly expect as part of their experience and are proven to be successful says Joe Schaefer, Chief Transformation Officer at Strategic Education. That’s why attention to student success is critical. If you’re looking for more guidance, join us for Student Success Week [register for free at: g.co/cloud/student-success-week], or reach out to our team to get started.Related ArticleCampuses use data analytics and virtual agents for student successStudent success is about much more than getting good grades. It also includes giving instructors more time to coach their students, helpi…Read Article
Quelle: Google Cloud Platform

Accelerating genomics workflows and data analysis on Azure

Genomics is foundational to the development of targeted therapeutics and precision medicine. Advances in DNA sequencing technologies has driven a revolution in genomics-based research and is helping facilitate better understanding of human biology and disease conditions. This expanded knowledge is leading to the proliferation of personalized medicine strategies to prevent, diagnose, and treat diseases. The trend will continue to accelerate in the coming decade as use of genomics information becomes central to clinical decision support and healthcare delivery.

Sequencing genomes at the population level will be required to decipher the genomic fingerprint of a disease, predict interpersonal variability in progression and treatment response, and develop models for clinical decision support. The resulting explosion in genomics data and the computational power required for analysis (tens of exabytes and trillions of core hours in the next five years1) will require agility, easier management, data security, and access to scalable storage and compute capacity.

The demand for cloud-based solutions is evident. It is increasingly being recognized that community driven standards and open-source tools will be necessary in enabling data accessibility, tool interoperability, and reliability of results and models. Microsoft not only supports open-standards and open-source projects but has been actively contributing to these community driven efforts by making it easier to use these tools and software on Azure.

To that end, Microsoft Genomics has released several open source projects on GitHub, including Cromwell on Azure, Genomics Notebooks and Bioconductor support for Azure. We have also made available a growing list of genomics public datasets on the Azure Open Dataset platform.

Scale and automate genomic workflows on Azure with Cromwell

Cromwell is an open-source workflow management system geared toward scientific workflows, originally developed by the Broad Institute. With Cromwell on Azure, users can accelerate their genomic research with the hyperscale compute capabilities of Azure. Cromwell orchestrates the dynamic provisioning of computing resources via Azure Batch and integrates with customers’ Azure Blob storage account for easy data access.

Propelling novel next generation sequencing (NGS) based detection and characterization assay for COVID-19 with Biotia

Biotia is an emerging startup focused on building a platform leveraging next-generation DNA sequencing (NGS) and artificial intelligence (AI) for precision disease detection and diagnosis. They were looking for a cloud-based workflow solution to manage their NGS pipelines and Cromwell on Azure was able to meet their key requirements.

"At Biotia, we have achieved substantial parallelization, thorough version control, and novel COVID-19 detection results by using Cromwell on Azure to back our compute-intensive genomics workflows. We are pleased to include Cromwell on Azure in our bioinformatics software stack." —Joe Barrows, Director of Software Engineering at Biotia

Enable collaborative and repeatable data analysis using Genomics Notebooks powered by Jupyter Notebooks on Azure

Jupyter Notebooks provides users an environment for analyzing data using R or Python and enabling reusability of methods and reproducibility of results. Biomedical researchers and data scientists are increasingly using notebooks for their genomics data analysis needs and for building machine learning models based on multi-modal datasets (genomic, phenotypic, clinical, EMR, demographic, etc.).

Microsoft’s Genomics Notebooks open-source project provides a growing collection of pre-configured notebooks that users can easily launch and use in their Azure workspace. These pre-configured notebooks cover scenarios from genomics variant detection, filtration, annotation, to transformation of the genomic, phenotypic and clinical data into multi-modal data frames needed for data querying and building machine learning models.

Leveraging genomic data to assess the impact of environmental change with the Canadian Department of Fisheries and Oceans

The Canadian Department of Fisheries and Oceans (DFO) is responsible for preserving Canada’s aquatic natural resources. DFO researchers at the Bedford Institute of Oceanography in Dartmouth, Nova Scotia have been using genomics to understand the impact of climate change and human activity on the migration patterns, genetic diversity and population demography of fish such as Atlantic Salmon and Atlantic Cod, which can have major socio-economic implications for the communities that rely on these resources.

The research teams are starting to sequence fish genomes in the hundreds and were looking for Azure based solutions for scaling and streamlining their growing genomics and data analysis needs. The team successfully deployed, and scale tested Cromwell on Azure and is now looking to adopt it as a common genomics workflow platform across their various institutions.

“Leveraging Cromwell on Azure for running our genomics pipelines give us the ability to scale our analysis to thousands of genomes for any species of fish with automation. We can essentially eliminate three months’ time of manual work to generate all the variant calls we need and move directly into connecting that data with other data sources we have. The data science tools will help us easily build and train complex multi-modal data models to gain deeper insights into the impact resulting from interactions between genetic factors, climate information, and human impacts on these species, and predict how they might respond to environmental challenges in the future.” —Dr. Tony Kess, Researcher at the Bradbury Population Genomics Lab, a part of the Bedford Institute of Oceanography in Dartmouth, Nova Scotia

Easily access the vast collection of community-built bioinformatics tools with Bioconductor on Azure

Bioconductor is an open source, open development project that focuses on providing a repository of extensible statistical and graphical software packages, developed in R, for the analysis of high-throughput genomic and biomedical data. Microsoft is collaborating with the Bioconductor core team in bringing Azure support for this wide-ranging OSS software repository.

Bioinformaticians and data scientists can now easily use their preferred Bioconductor software packages on Azure by deploying the preconfigured Bioconductor Docker image hosted in the Microsoft Container Registry on Docker Hub. Additionally, users can also use Azure Virtual Machine (VM) templates to deploy Genomics Data Science VM preconfigured with popular tools for data exploration, analysis, machine learning, and deep learning model development.

Power data analysis and machine learning models with genomics datasets available through the Azure Open Data platform

The Genomics Data Lake on the Azure Open Dataset platform provides a growing compendium of curated and publicly available genomics datasets. These datasets have been generated by key international collaborative efforts with a focus on providing resources for the biomedical research community. Users across healthcare, pharma and life sciences can now use the Genomics Data Lake on Azure to access these datasets for free and easily integrate the data into their genomics analysis workflows.

Accelerate whole exome and genome processing using Microsoft Genomics turnkey service on Azure

Microsoft Genomics is a highly scalable Azure service to perform secondary analysis of the human genome using the Burrows-Wheeler Aligner (BWA) and the Genome Analysis Toolkit (GATK) open-source software. The service is ISO-certified, enables customers’ compliance with HIPAA, and is covered under the Microsoft Business Associate Agreement (BAA). Microsoft continues to optimize the performance of the service by leveraging the innovations in Azure’s high-performance compute infrastructure enabling customers to generate durable genetic variant data from whole genome sequence data (WGS) within hours. Compliance, performance, data durability and provenance make the service ideal for integration into genomics-based clinical decision support workflows.

Accelerating scientific discoveries to advance cures for childhood cancers through access to real-time clinical genome sequencing at St. Jude Children’s Research Hospital

Whole-genome sequencing offers the most comprehensive assessment of differences between patients’ normal and cancer genomes. Realtime access to the genomic information is not only important for clinical decision support, but it can also accelerate research and novel discoveries and cures. St. Jude Children’s Research Hospital has partnered with Microsoft and DNAnexus to build St. Jude Cloud—the world’s largest public repository of pediatric genomics data.

This first-of-its-kind initiative provides researchers from around the world access to high-quality whole-genome, whole-exome and transcriptome data from appropriately consented St. Jude patients who have undergone clinical genomic profiling. St. Jude Cloud uses Azure and the Microsoft Genomics service to quickly upload, analyze, and harmonize the genomics data, which is subsequently made available through the St. Jude Cloud data browser to researchers worldwide.

“Access to high-quality clinical genomic data, generated leveraging the Microsoft Genomics service and streamed to St. Jude Cloud, will help further research in precision medicine for childhood cancer and other diseases.”—Dr. Jinghui Zhang, Chair of Department of Computational Biology at the St. Jude Children’s Research Hospital

Learn more and get started

Microsoft Genomics and the open-source projects are fully supported by a team of Microsoft developers and scientists committed to driving the innovation needed to advance genomics and precision medicine. Learn more about Microsoft Genomics solutions and help contribute to the open-source projects by visiting our GitHub repositories.

Microsoft Genomics service on Azure.
Cromwell on Azure.
Genomics Notebooks.
Bioconductor Docker Image for Azure.
Genomics Data Science VM.

1 Big Data: Astronomical or Genomical?

Azure. Invent with purpose.
Quelle: Azure