AWS Firewall Manager unterstützt jetzt AWS CloudFormation

AWS Firewall Manager unterstützt jetzt AWS CloudFormation, sodass Kunden alle Firewall Manager-Richtlinientypen und -Ressourcen mit CloudFormation-Stack-Vorlagen verwalten können. AWS Firewall Manager ist ein Sicherheitsmanagementservice, der die zentrale Konfiguration und Verwaltung von Firewallregeln für Ihre Konten und Anwendungen in AWS Organization ermöglicht. Mit Firewall Manager können Sie AWS WAF, AWS Shield Advanced oder VPC-Sicherheitsgruppen in Ihrer gesamten AWS Organization verwalten. Firewall Manager stellt sicher, dass alle Sicherheitsregeln konsistent durchgesetzt werden, auch wenn neue Konten oder Anwendungen erstellt werden.
Quelle: aws.amazon.com

Amazon Rekognition erkennt jetzt Text in Videos und ermöglicht Ihnen das Filtern von Ergebnissen nach Region, Größe des Begrenzungsrahmens und Zuverlässigkeitswert

Amazon Rekognition ist ein auf Deep Learning basierender Bild- und Videoanalyseservice, der Objekte, Menschen, Text und Szenen erkennt sowie die Inhaltsmoderation durch das Erkennen unsicherer Inhalte erleichtert. Ab sofort können Sie Text in Videos erkennen und die Erkennungszuverlässigkeit, den Positionsbegrenzungsrahmen und den Zeitstempel für jede Texterkennung erhalten. Zudem bietet die Texterkennung sowohl in Bildern als auch in Videos jetzt praktische Optionen zum Herausfiltern von Wörtern nach Bereichen von Interesse (Regions Of Interest, ROIs), Größe des Wortbegrenzungsrahmens und Wortzuverlässigkeitswert.  
Quelle: aws.amazon.com

Your cloud, your infrastructure: Announcing Anthos Ready Storage

We launched Anthos to provide customers with a platform to deliver and manage applications across all types of environments and infrastructure—most commonly, hybrid and multi-cloud environments—leveraging containers and Kubernetes.To date, we have seen an extremely enthusiastic response from customers who want to run key workloads on Anthos. Our partners are enabling customers to deliver solutions that leverage Anthos in new and exciting ways. This includes storage, which is a key consideration as organizations look to manage their data across hybrid or multi-cloud deployments in containerized environments.Today, we’re excited to announce a new qualification for partner storage solutions:Anthos Ready Storage. This qualification recognizes partner solutions that have met a core set of requirements to run optimally with Anthos running on-premises, and helps organizations select storage solutions that are deployed with Anthos.The first set of partners to achieve the Anthos Ready Storage qualification for Anthos on-premise are Dell EMC, HP Enterprise, NetApp, Portworx, Pure Storage, and Robin.io. All Anthos Ready Storage partners have met multiple criteria, including:Demonstrated core Kubernetes functionality including dynamic provisioning of volumes via open and portable Kubernetes-native storage APIs.A proven ability to automatically manage storage across cluster scale-up and scale-down scenarios.A simplified deployment experience following Kubernetes practices.“Speed is the new scale in the world upset by digital transformation, the complex reality is that data and resources live anywhere and everywhere.” said Anthony Lye, senior vice president and general manager, Cloud Data Services at NetApp. “We’re excited to expand our support for customers on Anthos in the hybrid multicloud as a part of the Anthos Ready Storage initiative. Together, Google Cloud’s Anthos and NetApp Trident and Kubernetes-ready storage offer a proven solution that helps customers manage their data on public cloud, on premises and hybrid cloud environments.”“Speed to market is a key differentiator as companies develop next generation, cloud-native applications. The emergence of Kubernetes is driven by that need for agility,” said Jay Snyder, SVP Global Alliances, Dell Technologies. “We’re pleased to participate in this program, as Dell EMC PowerMax and VxFlex are ideal infrastructure options when paired with Google Cloud Anthos to deploy Kubernetes in multi-cloud environments.”“Businesses are moving rapidly to modernize their applications using container based architectures,” said Omer Asad, VP and GM Primary Storage & Data Services at HP Enterprise. “We’re excited to expand our work with Google Cloud to qualify our fully-managed, container-based storage solutions such as HPE Nimble Storage for the Anthos platform.”We’re committed to meeting customers where they are, and providing them with the ability to run key workloads and applications in the environment best suited for their business. To learn more about the Anthos Ready Storage program, please visit here. To get started with Anthos, contact us.
Quelle: Google Cloud Platform

Getting Started with Istio Using Docker Desktop

This is a guest post from Docker Captain Elton Stoneman, a Docker alumni who is now a freelance consultant and trainer, helping organizations at all stages of their container journey. Elton is the author of the book Learn Docker in a Month of Lunches, and numerous Pluralsight video training courses – including Managing Apps on Kubernetes with Istio and Monitoring Containerized Application Health with Docker.

Istio is a service mesh – a software component that runs in containers alongside your application containers and takes control of the network traffic between components. It’s a powerful architecture that lets you manage the communication between components independently of the components themselves. That’s useful because it simplifies the code and configuration in your app, removing all network-level infrastructure concerns like routing, load-balancing, authorization and monitoring – which all become centrally managed in Istio.

There’s a lot of good material for digging into Istio. My fellow Docker Captain Lee Calcote is the co-author of Istio: Up and Running, and I’ve just published my own Pluralsight course Managing Apps on Kubernetes with Istio. But it can be a difficult technology to get started with because you really need a solid background in Kubernetes before you get too far. In this post, I’ll try and keep it simple. I’ll focus on three scenarios that Istio enables, and all you need to follow along is Docker Desktop.

Setup

Docker Desktop gives you a full Kubernetes environment on your laptop. Just install the Mac or Windows version – be sure to switch to Linux containers if you’re using Windows – then open the settings from the Docker whale icon, and select Enable Kubernetes in the Kubernetes section. You’ll also need to increase the amount of memory Docker can use, because Istio and the demo app use a fair bit – in the Resources section increase the memory slider to at least 6GB.

Now grab the sample code for this blog post, which is in my GitHub repo:

git clone https://github.com/sixeyed/istio-samples.git
cd istio-samples


The repo has a set of Kubernetes manifests that will deploy Istio and the demo app, which is a simple bookstore website (this is the Istio team’s demo app, but I use it in different ways so be sure to use my repo to follow along). Deploy everything using the Kubernetes control tool kubectl, which is installed as part of Docker Desktop:

kubectl apply -f ./setup/

You’ll see dozens of lines of output as Kubernetes creates all the Istio components along with the demo app – which will all be running in Docker containers. It will take a few minutes for all the images to download from Docker Hub, and you can check the status using kubectl:

# Istio – will have “1/1” in the “READY” column when fully running:
kubectl get deploy -n istio-system

# demo app – will have “2/2” in the “READY” column when fully running:
kubectl get pods

When all the bits are ready, browse to http://localhost/productpage and you’ll see this very simple demo app:

And you’re good to go. If you’re happy working with Kubernetes YAML files you can look at the deployment spec for the demo app, and you’ll see it’s all standard Kubernetes resources – services, service accounts and deployments. Istio is managing the communication for the app, but we haven’t deployed any Istio configurations, so it isn’t doing much yet.

The demo application is a distributed app. The homepage runs in one container and it consumes data from REST APIs running in other containers. The book details and book reviews you see on the page are fetched from other containers. Istio is managing the network traffic between those components, and it’s also managing the external traffic which comes into Kubernetes and on to the homepage.

We’ll use this demo app to explore the main features of Istio: traffic management, security and observability.

Managing Traffic – Canary Deployments with Istio

The homepage is kinda boring, so let’s liven it up with a new release. We want to do a staged release so we can check out how the update gets received, and Istio supports both blue-green and canary deployments. Canary deployments are generally more useful and that’s what we’ll use. We’ll have two versions of the home page running, and Istio will send a proportion of the traffic to version 1 and the remainder to version 2:

We’re using Istio for service discovery and routing here: all incoming traffic comes into Istio and we’re going to set rules for how it forwards that traffic to the product page component. We do that by deploying a VirtualService, which is a custom Istio resource. That contains this routing rule for HTTP traffic:

gateways:
– bookinfo-gateway
http:
– route:
– destination:
host: productpage
subset: v1
port:
number: 9080
weight: 70
– destination:
host: productpage
subset: v2
port:
number: 9080
weight: 30

There are a few moving pieces here:

The gateway is the Istio component which receives external traffic. The bookinfo-gateway object is configured to listen to all HTTP traffic, but gateways can be restricted to specific ports and host names;The destination is the actual target where traffic will be routed (which can be different from the requested domain name). In this case, there are two subsets, v1 which will receive 70% of traffic and v2 which receives 30%;Those subsets are defined in a DestinationRule object, which uses Kubernetes labels to identify pods within a service. In this case the v1 subset finds pods with the label version=v1, and the v2 subset finds pods with the label version=v2.

Sounds complicated, but all it’s really doing is defining the rules to shift traffic between different pods. Those definitions come in Kubernetes manifest YAML files, which you deploy in the same way as your applications. So we can do our canary deployment of version 2 with a single command – this creates the new v2 pod, together with the Istio routing rules:

# deploy:
kubectl apply -f ./canary-deployment

# check the deployment – it’s good when all pods show “2/2” in “READY”:
kubectl get pods

Now if you refresh the bookstore demo app a few times, you’ll see that most of the responses are the same boring v1 page, but a lucky few times you’ll see the v2 page which is the result of much user experience testing:

As the positive feedback rolls in you can increase the traffic to v2 just by altering the weightings in the VirtualService definition and redeploying. Both versions of your app are running throughout the canary stage, so when you shift traffic you’re sending it to components that are already up and ready to handle traffic, so there won’t be additional latency from new pods starting up.

Canary deployments are just one aspect of traffic management which Istio makes simple. You can do much more, including adding add fault tolerance with retries and circuit breakers, all with Istio components and without any changes to your apps.

Securing Traffic – Authentication and Authorization with mTLS

Istio handles all the network traffic between your components transparently, without the components themselves knowing that it’s interfering. It does this by running all the application container traffic through a network proxy, which applies Istio’s rules. We’ve seen how you can use that for traffic management, and it works for security too.

If you need encryption in transit between app components, and you want to enforce access rules so only certain consumers can call services, Istio can do that for you too. You can keep your application code and config simple, use basic unauthenticated HTTP and then apply security at the network level.

Authentication and authorization are security features of Istio which are much easier to use than they are to explain. Here’s the diagram of how the pieces fit together:

Here the product page component on the left is consuming a REST API from the reviews component on the right. Those components run in Kubernetes pods, and you can see each pod has one Docker container for the application and a second Docker container running the Istio proxy, which handles the network traffic for the app.

This setup uses mutual-TLS for encrypting the HTTP traffic and authenticating and authorizing the caller:

The authentication Policy object applied to the service requires mutual TLS, which means the service proxy listens on port 443 for HTTPS traffic, even though the service itself is only configured to listen on port 80 for HTTP traffic;The AuthorizationPolicy object applied to the service specifies which other components are allowed access. In this case, everything is denied access, except the product page component which is allowed HTTP GET access;The DestinationRule object is configured for mutual-TLS, which means the proxy for the product page component will upgrade HTTP calls to HTTPS, so when the app calls the reviews component it will be a mutual-TLS conversation.

Mutual-TLS means the client presents a certificate to identify itself, as well as the service presenting a certificate for encryption (only the server cert is standard HTTPS behavior). Istio can generate and manage all those certs, which removes a huge burden from normal mTLS deployments. 

There’s a lot to take in there, but the deployment and management of all that is super simple, it’s just the same kubectl process:

kubectl apply -f ./service-authorization/

Istio uses the Kubernetes Service Account for identification, and you’ll see when you try the app that nothing’s changed, it all works as before. The difference is that no other components running in the cluster can access the reviews component now, the API is locked down so only the product page can consume it.

You can verify that by connecting to another container – the details component is running in the same cluster. Try to consume the reviews API from the details container:

docker container exec -it $(docker container ls –filter name=k8s_details –format ‘{{ .ID}}’) sh

curl http://reviews:9080/1

You’ll see an error – RBAC: access denied, which is Istio enforcing the authorization policy. This is powerful stuff, especially having Istio manage the certs for you. It generates certs with a short lifespan, so even if they do get compromised they’re not usable for long. All this without complicating your app code or dealing with self-signed certs.

Observability – Visualising the Service Mesh with Kiali

All network traffic runs through Istio, which means it can monitor and record all the communication. Istio uses a pluggable architecture for storing telemetry, which has support for standard systems like Prometheus and Elasticsearch. 

Collecting and storing telemetry for every network call can be expensive, so this is all configurable. The deployment of Istio we’re using is the demo configuration, which has telemetry configured so we can try it out. Telemetry data is sent from the service proxies to the Istio component called Mixer, which can send it out to different back-end stores, in this case, Prometheus:

(This diagram is a simplification – Prometheus actually pulls the data from Istio, and you can use a single Prometheus instance to collect metrics from Istio and your applications).

The data in Prometheus includes response codes and durations, and Istio comes with a bunch of Grafana dashboards you can use to drill down into the metrics. And it also has support for a great tool called Kiali, which gives you a very useful visualization of all your services and the network traffic between them.

Kiali is already running in the demo deployment, but it’s not published by default. You can gain access by deploying a Gateway and a VirtualService:

kubectl apply -f ./visualization-kiali/

Now refresh the app a few times at http://localhost/productpage and then check out the service mesh visualization in Kiali at http://localhost:15029. Log in with the username admin and password admin, then browse to the Graph view and you’ll see the live traffic for the bookstore app:

I’ve turned on “requests percentage” for the labels here, and I can see the traffic split between my product page versions is 67% to 34%, which is pretty close to my 70-30 weighting (the more traffic you have, the closer you’ll get to the specified weightings).

Kiali is just one of the observability tools Istio supports. The demo deployment also runs Grafana with multiple dashboards and Jaeger for distributed tracing – which is a very powerful tool for diagnosing issues with latency in distributed applications. All the data to power those visualizations is collected automatically by Istio.

Wrap-Up

A service mesh makes the communication layer for your application into a separate entity, which you can control centrally and independently from the app itself. Istio is the most fully-featured service mesh available now, although there is also Linkerd (which tends to have better baseline performance), and the Service Mesh Interface project (which aims to standardise mesh features). 

Using a service mesh comes with a cost – there are runtime costs for hosting additional compute for the proxies and organizational costs for getting teams skilled in Istio. But the scenarios it enables will outweigh the cost for a lot of people, and you can very quickly test if Istio is for you, using it with your own apps in Docker Desktop.
The post Getting Started with Istio Using Docker Desktop appeared first on Docker Blog.
Quelle: https://blog.docker.com/feed/

New Azure Firewall certification and features in Q1 CY2020

This post was co-authored by Suren Jamiyanaa, Program Manager, Azure Networking

We continue to be amazed by the adoption, interest, positive feedback, and the breadth of use cases customers are finding for our service. Today, we are excited to share several new Azure Firewall capabilities based on your top feedback items:

ICSA Labs Corporate Firewall Certification.
Forced tunneling support now in preview.
IP Groups now in preview.
Customer configured SNAT private IP address ranges now generally available.
High ports restriction relaxation now generally available.

Azure Firewall is a cloud native firewall as a service (FWaaS) offering that allows you to centrally govern and log all your traffic flows using a DevOps approach. The service supports both application and network level filtering rules and is integrated with the Microsoft Threat Intelligence feed for filtering known malicious IP addresses and domains. Azure Firewall is highly available with built-in auto scaling.

ICSA Labs Corporate Firewall Certification

ICSA Labs is a leading vendor in third-party testing and certification of security and health IT products, as well as network-connected devices. They measure product compliance, reliability, and performance for most of the world’s top technology vendors.

Azure Firewall is the first cloud firewall service to attain the ICSA Labs Corporate Firewall Certification. For the Azure Firewall certification report, see information here. For more information, see the ICSA Labs Firewall Certification program page.

Figure one – Azure Firewall now ICSA Labs certified.

Forced tunneling support now in preview

Forced tunneling lets you redirect all internet bound traffic from Azure Firewall to your on-premises firewall or a nearby Network Virtual Appliance (NVA) for additional inspection. By default, forced tunneling isn't allowed on Azure Firewall to ensure all its outbound Azure dependencies are met.

To support forced tunneling, service management traffic is separated from customer traffic. An additional dedicated subnet named AzureFirewallManagementSubnet is required with its own associated public IP address. The only route allowed on this subnet is a default route to the internet, and BGP route propagation must be disabled.

Within this configuration, the AzureFirewallSubnet can now include routes to any on-premise firewall or NVA to process traffic before it's passed to the Internet. You can also publish these routes via BGP to AzureFirewallSubnet if BGP route propagation is enabled on this subnet. For more information see Azure Firewall forced tunneling documentation.

Figure two – Creating a firewall with forced tunneling enabled.

IP Groups now in preview

IP Groups is a new top-level Azure resource in that allows you to group and manage IP addresses in Azure Firewall rules. You can give your IP group a name and create one by entering IP addresses or uploading a file. IP Groups eases your management experience and reduce time spent managing IP addresses by using them in a single firewall or across multiple firewalls. For more information, see the IP Groups in Azure Firewall documentation.

Figure three – Azure Firewall application rules utilize an IP group.

Customer configured SNAT private IP address ranges

Azure firewall provides automatic Source Network Address Translation (SNAT) for all outbound traffic to public IP addresses. Azure Firewall doesn’t SNAT when the destination IP address is a private IP address range per IANA RFC 1918. If your organization uses a public IP address range for private networks or opts to force tunnel Azure Firewall internet traffic via an on-premises firewall, you can configure Azure Firewall to not SNAT additional custom IP address ranges. For more information, see Azure Firewall SNAT private IP address ranges.

Figure four – Azure Firewall with custom private IP address ranges.

High ports restriction relaxation now generally available

Since its initial preview release, Azure Firewall had a limitation that prevented network and application rules from including source or destination ports above 64,000. This default behavior blocked RPC based scenarios and specifically Active Directory synchronization. With this new update, customers can use any port in the 1-65535 range in network and application rules.

Next steps

For more information on everything we covered above please see the following blogs, documentation, and videos.

Azure Firewall documentation.
Azure Firewall July 2019 blog: What’s new in Azure Firewall.
Azure Firewall Manager documentation.
Azure Firewall Manager blog: Azure Firewall Manager now supports virtual networks.

Azure Firewall central management partners:

AlgoSec CloudFlow.
Barracuda Cloud Security Guardian, now generally available in Azure Market.
Tufin SecureCloud.

Quelle: Azure

Azure Firewall Manager now supports virtual networks

This post was co-authored by Yair Tor, Principal Program Manager, Azure Networking.

Last November we introduced Microsoft Azure Firewall Manager preview for Azure Firewall policy and route management in secured virtual hubs. This also included integration with key Security as a Service partners, Zscaler, iboss, and soon Check Point. These partners support branch to internet and virtual network to internet scenarios.

Today, we are extending Azure Firewall Manager preview to include automatic deployment and central security policy management for Azure Firewall in hub virtual networks.

Azure Firewall Manager preview is a network security management service that provides central security policy and route management for cloud-based security perimeters. It makes it easy for enterprise IT teams to centrally define network and application-level rules for traffic filtering across multiple Azure Firewall instances that spans different Azure regions and subscriptions in hub-and-spoke architectures for traffic governance and protection. In addition, it empowers DevOps for better agility with derived local firewall security policies that are implemented across organizations.

For more information see Azure Firewall Manager documentation.

Figure one – Azure Firewall Manger Getting Started page

 

Hub virtual networks and secured virtual hubs

Azure Firewall Manager can provide security management for two network architecture types:

 Secured virtual hub—An Azure Virtual WAN Hub is a Microsoft-managed resource that lets you easily create hub-and-spoke architectures. When security and routing policies are associated with such a hub, it is referred to as a secured virtual hub.

 Hub virtual network—This is a standard Azure Virtual Network that you create and manage yourself. When security policies are associated with such a hub, it is referred to as a hub virtual network. At this time, only Azure Firewall Policy is supported. You can peer spoke virtual networks that contain your workload servers and services. It is also possible to manage firewalls in standalone virtual networks that are not peered to any spoke.

Whether to use a hub virtual network or a secured virtual depends on your scenario:

 Hub virtual network—Hub virtual networks are probably the right choice if your network architecture is based on virtual networks only, requires multiple hubs per regions, or doesn’t use hub-and-spoke at all.

 Secured virtual hubs—Secured virtual hubs might address your needs better if you need to manage routing and security policies across many globally distributed secured hubs. Secure virtual hubs have high scale VPN connectivity, SDWAN support, and third-party Security as Service integration. You can use Azure to secure your Internet edge for both on-premises and cloud resources.

The following comparison table in Figure 2 can assist in making an informed decision:

 

 
Hub virtual network
Secured virtual hub

Underlying resource
Virtual network
Virtual WAN hub

Hub-and-Spoke
Using virtual network peering
Automated using hub virtual network connection

On-prem connectivity

VPN Gateway up to 10 Gbps and 30 S2S connections; ExpressRoute

More scalable VPN Gateway up to 20 Gbps and 1000 S2S connections; ExpressRoute

Automated branch connectivity using SDWAN
Not supported
Supported

Hubs per region
Multiple virtual networks per region

Single virtual hub per region. Multiple hubs possible with multiple Virtual WANs

Azure Firewall – multiple public IP addresses
Customer provided
Auto-generated (to be available by general availability)

Azure Firewall Availability Zones
Supported
Not available in preview. To be available availabilityavailablity

Advanced internet security with 3rd party Security as a service partners

Customer established and managed VPN connectivity to partner service of choice

Automated via Trusted Security Partner flow and partner management experience

Centralized route management to attract traffic to the hub

Customer managed UDR; Roadmap: UDR default route automation for spokes

Supported using BGP

Web Application Firewall on Application Gateway
Supported in virtual network
Roadmap: can be used in spoke

Network Virtual Appliance
Supported in virtual network
Roadmap: can be used in spoke

Figure 2 – Hub virtual network vs. secured virtual hub

Firewall policy

Firewall policy is an Azure resource that contains network address translation (NAT), network, and application rule collections as well as threat intelligence settings. It's a global resource that can be used across multiple Azure Firewall instances in secured virtual hubs and hub virtual networks. New policies can be created from scratch or inherited from existing policies. Inheritance allows DevOps to create local firewall policies on top of organization mandated base policy. Policies work across regions and subscriptions.

Azure Firewall Manager orchestrates Firewall policy creation and association. However, a policy can also be created and managed via REST API, templates, Azure PowerShell, and CLI.

Once a policy is created, it can be associated with a firewall in a Virtual WAN Hub (aka secured virtual hub) or a firewall in a virtual network (aka hub virtual network).

Firewall Policies are billed based on firewall associations. A policy with zero or one firewall association is free of charge. A policy with multiple firewall associations is billed at a fixed rate.

For more information, see Azure Firewall Manager pricing.

The following table compares the new firewall policies with the existing firewall rules:

 

Policy

Rules

Contains

NAT, Network, Application rules, and Threat Intelligence settings

NAT, Network, and Application rules

Protects

Virtual hubs and virtual networks

Virtual networks only

Portal experience

Central management using Firewall Manager

Standalone firewall experience

Multiple firewall support

Firewall Policy is a separate resource that can be used across firewalls

Manually export and import rules or using 3rd party management solutions

Pricing

Billed based on firewall association. See Pricing

Free

Supported deployment mechanisms

Portal, REST API, templates, PowerShell, and CLI

Portal, REST API, templates, PowerShell, and CLI

Release Status

Preview

General Availability

Figure 3 – Firewall Policy vs. Firewall Rules

Next steps

For more information on topics covered here, see the following blogs, documentation, and videos:

 Azure Firewall Manager documentation
 Azure Firewall Manager Pricing

Azure Firewall central management partners:

AlgoSec CloudFlow
Barracuda Cloud Security Guardian, now generally available in Azure Market
Tufin SecureCloud

Quelle: Azure

Introducing the Cloud Monitoring dashboards API

Using dashboards in Cloud Monitoring makes it easy to track critical metrics across time. Dashboards can, for example, provide visualizations to help debug high latency in your application or track key metrics for your applications. Creating dashboards by hand in the Monitoring UI can be a time-consuming process, which may require many iterations. Once dashboards are created, you can save time by using them in multiple Workspaces within your organization. Today, we’re pleased to announce that the Cloud Monitoring dashboards API is generally available from Google Cloud. The dashboards API lets you read the configuration for existing dashboards, create new dashboards, update existing dashboards and delete dashboards that you no longer use. These methods follow the REST and gRPC semantics and are consistent with other Google Cloud APIs. A common use case for the dashboards API is to deploy a dashboard developed in one Monitoring Workspace into one or more additional Workspaces. For example, you may have a separate Workspace for your development, QA and production environments (learn more on selecting Workspace structures). In one of the environments, you may have developed a standard operational dashboard that you’d like to use across all your Workspaces. By first reading the dashboard configuration via the projects.dashboards.get method, you can save the dashboard configuration and then use the projects.dashboards.create method to create the same dashboard across the other environments.How the dashboard API works When creating a dashboard, you have to specify the layout and the widgets that go inside that layout. A dashboard must use one of three layout types: GridLayout, RowLayout or ColumnLayout. GridLayout divides the available space into vertical columns of equal width and arranges a set of widgets using a row-first strategy.RowLayout divides the available space into rows and arranges a set of widgets horizontally in each row.ColumnLayout divides the available space into vertical columns and arranges a set of widgets vertically in each column.The widgets available to place inside the layouts include an XyChart, Scorecard and Text object.XyChart: displays data using X and Y axes. Charts created through the Google Cloud Console are instances of this widget.Scorecard: displays the latest value of a metric, and how this value relates to one or more thresholds. Text: displays textual content, either as raw text or a markdown string. Here’s an example of the JSON dashboard configuration, which specifies a GridLayout with a single XyChart widget. You can see other examples in our sample dashboards and layouts documentation.Dashboard configuration as a templateA simple approach to building a dashboard configuration is to first create a dashboard in the Cloud Monitoring console, then use the dashboards API projects.dashboards.get method to export the JSON configuration. Then, you can share that configuration as a template either via source control or however you normally share files with your colleagues.You can try out the dashboard API in the Try this API section of the API documentation, and learn more about managing dashboards by reading the Managing Dashboards documentation. We’re working on features to make the API even more useful, including through the gcloud command line. Also, contributors are discussing and planning the Terraform module for the Monitoring Dashboard API in github.A special thanks to our colleagues David Batelu, Technical Lead and Joy Wang, Product Manager, Cloud Monitoring, for their contributions to this post.
Quelle: Google Cloud Platform

Azure Offline Backup with Azure Data Box now in preview

An ever-increasing number of enterprises, even as they adopt a hybrid IT strategy, continue to retain mission-critical data on-premises and look towards the public cloud as an effective offsite for their backups. Azure Backup—Azure’s built-in data-protection solution, provides a simple, secure, and cost-effective mechanism to backup these data-assets over the network to Azure, while eliminating on-premises backup infrastructure. After the initial full backup of data, Azure Backup transfers only incremental changes in the data, thereby delivering continued savings on both network and storage.

With the exponential growth in critical enterprise data, the initial full backups are reaching terabyte scale. Transferring these large full-backups over the network, especially in high-latency network environments or remote offices, may take weeks or even months. Our customers are looking for more efficient ways beyond fast networks to transfer these large initial backups to Azure. Microsoft Azure Data Box solves the problem of transferring large data sets to Azure by enabling the “offline” transfer of data using secure, portable, and easy-to-get Microsoft appliances.

Announcing the preview of Azure Offline Backup with Azure Data Box

Today, we are thrilled to add the power of Azure Data Box to Azure Backup, and announce the preview program for offline initial backup of large datasets using Azure Data Box! With this preview, customers will be able to use Azure Data Box with Azure Backup to seed large initial backups (up to 80 TB per server) offline to an Azure Recovery Services Vault. Subsequent backups will take place over the network.

This preview is currently available to the customers of Microsoft Azure Recovery Services agent and is a much-awaited addition to the existing support for offline backup using Azure Import/Export Services. 

Key benefits

The Azure Data Box addition to Azure Backup delivers core benefits of the Azure Data Box service while offering key advantages over the Azure Import/Export based offline backup.

Simple—No need to procure your own Azure-compatible disks or connectors as with the Azure Import based offline backup. Simply order and receive one or more Data Box appliances from your Azure subscription, plug-in, fill with backup data, return to Azure, and track all of it on the Azure portal.
Built-in—The Azure Data Box based offline backup experience is built-into the Recovery Services agent, so you can easily discover and detect your received Azure Data Box appliances, transfer backup data, and track the completion of the initial backup directly from the agent.
Secure—Azure Data Box is a tamper-resistant appliance that comes with ruggedized casing to handle bumps and bruises during transport and supports 256-bit AES encryption on your data.
Efficient—Get freedom from provisioning temporary storage (staging locations) or use of additional tools to prepare disks and copy data, as in the Azure Import based offline backup. Azure Backup directly copies backup data to Azure Data Box, delivering savings on storage and time, and eliminating additional copy tools.

Getting started

Seeding your large initial backups using Azure Backup and Azure Data Box involves the following high-level steps. 

Order and receive your Azure Data Box based on the amount of data you want to backup from a server. Order an Azure Data Box Disk if you want to backup less than 7.2 TB of data. Order an Azure Data Box to backup up to 80 TB of data.
Install and register the latest Recovery Services agent to an Azure Recovery Services Vault.
Select the “Transfer using Microsoft Azure Data Box disks” option for offline backup as part of scheduling your backups with the Recovery Services agent.

Trigger Backup to Azure Data Box from the Recovery Services Agent.
Return Azure Data Box to Azure.

Azure Data Box and Azure Backup will automatically upload the data to the Azure Recovery Services Vault. Refer to this article for a detailed overview of pre-requisites and steps to take advantage of Azure Data Box when seeding your initial backup offline with Azure Backup.

Offline backup with Azure Data Box on Data Protection Manager and Azure Backup Server

If you are using System Center Data Protection Manager or Microsoft Azure Backup Server and are interested in seeding large initial backups using Azure Data Box, drop us a line at systemcenterfeedback@microsoft.com for access to early previews.

Related links and additional content

Jump right into using Offline Backup with Azure Data Box.
Learn more about Offline backup options with Azure Backup.
New to Azure Backup? Sign up for a free Azure trial subscription.
Review whether you need to use online or offline mechanisms to send backup data to Azure.
Need help? Reach out to Azure Backup forum for support or browse Azure Backup documentation.
Follow us on Twitter @AzureBackup for the latest news and updates.

Quelle: Azure