Die Schwachstelle in der Firmware eines weit verbreiteten Broadcom-Chipsatzes ermöglicht einem Angreifer, die Kontrolle über den WLAN-Chip des iPhone 7 zu übernehmen. In iOS-Versionen bis hin zu 10.3.3 bleibt die Lücke bislang ungeschlossen.
Quelle: Heise Tech News
Laut dem jüngsten IOCTA-Bericht ist Cybercrime weiter am Wachsen, doch Cyberattacken durch Terroristen gegen Staaten sind eher unwahrscheinlich.
Quelle: Heise Tech News
Anders als bei Privatwohnungen, für die der Rundfunkbeitrag als Haushaltsabgabe unabhängig vom Vorhandensein eines Empfangsgerätes erhoben wird, beurteilen die obersten Verwaltungsrichter die Lage bei Gästezimmern.
Quelle: Heise Tech News
1&1 nutzt für Festnetzangebote auch das Netz der Telekom. Der Konzern hat jetzt durchgesetzt, dass der Konkurrent nicht mit der Aussage “Das beste Netz gibt’s bei 1&1″ werben darf. (1&1, DSL)
Quelle: Golem
By Indranil Chakraborty, Product Manager, Google Cloud
At Google I/O, we introduced Google Cloud IoT Core, a fully managed service on Google Cloud Platform (GCP) to help securely connect and manage IoT devices at scale. Since then, many customers across industries such as transportation, oil and gas, utilities, healthcare and ride-sharing have used the service and provided us with insightful feedback.
Cloud IoT Core is now publicly available to all users in beta, and we have introduced new set of features in this release. With Cloud IoT Core, you can easily connect and centrally manage millions of globally dispersed IoT devices. When used as part of the broader Google Cloud IoT solution, you can ingest all your IoT data and connect to our state-of-the-art analytics services including Google Cloud Pub/Sub, Google Cloud Dataflow, Google Cloud Bigtable, Google BigQuery, and Google Cloud Machine Learning Engine to gain actionable insights.
Key new features
Bring your own certificate
Cloud IoT Core private beta users have asked for the ability to verify the ownership of device keys. In addition to asymmetric key-based authentication per individual device, users can now bring their own device key signed by their Certificate Authority (CA), and IoT Core verifies the signature of the key provided by the device with the CA certificate during the authentication process. This, for example, enables device manufacturers to provision their devices offline in bulk with their CA-issued certificate, and then register the CA certificates and the device public keys with Cloud IoT Core.
Connect existing devices with HTTP
In addition to the standard MQTT protocol, you can now more securely connect existing IoT devices and gateways to Cloud IoT Core over HTTP to easily ingest data into GCP at scale.
Logical device representation
Certain use cases require an IoT application to retrieve the last state and properties of an IoT device even when the device is not connected. Cloud IoT Core now maintains a logical representation of the physical IoT device, including device properties, and its last reported state. It provides APIs for your applications to retrieve and update the device properties and state even when the device is not connected.
Private beta users of Cloud IoT Core have built innovative IoT solutions in a short period of time. For example, transportation and logistics firms have used it to proactively stage the right vehicles in the right places at the right times. Utilities have enabled monitoring, analysis and prediction of consumer energy usage in real-time.
Our customers share feedback
Smart Parking designs, develops and produces leading-edge technology that enables clients to manage parking efficiently and cost effectively. The company recently introduced the latest version of its platform that expands its scope from smart parking to smart cities. This new platform, built on GCP, leverages Cloud IoT Core to allow input from any number of distributed devices within a city. Smart Parking is now able to drive city-wide analytics and interconnected logic using powerful streams of real-time data.
“Our devices are heavily used and constantly send us a huge volume of data. By connecting these devices to Cloud IoT Core, we have a secure and reliable way to not only ingest that data but then also use it to gain valuable insights. We know exactly how our systems are performing and can push updates to devices to ensure we deliver the best products and services as cost effectively as possible.” John Heard, Group CTO, Smart Parking Limited
Tellmeplus’ award-winning AI platform, Predictive Objects, leverages machine learning and big data for predictive models in domains like customer or asset intelligence. As such, it helps experts make faster and more accurate predictions in IoT-based applications. By integrating Predictive Objects with Cloud IoT Core, joint customers can deploy and run predictive models on GCP as well as inside devices managed by Predictive Objects.
“Our disruptive approach to automated embedded artificial intelligence is ideally suited for deployment using Google Cloud IoT Core. This integration enables our predictive models to not only run inside Google Cloud Platform but also inside the objects themselves, whether they are connected or not, with a single point of control and a unified management console. We are proud to have been selected by Google to help extend the value of AI in their IoT ecosystem.” Benoit Gourdon, CEO, Tellmeplus
Partner ecosystem
We continue to work with our partners to offer devices and kits that work seamlessly with Cloud IoT Core. You can now procure kits from our partners and start building IoT solution relevant to your business case.
Cloud IoT Core device partners:
Allwinner Technology
Arm
Intel
Marvell
Microchip
Mongoose OS
NXP
Realtek
Sierra Wireless
SOTEC
Pricing
We are also introducing a simple pricing plan based on the volume of data exchanged with Cloud IoT Core. You can register as many IoT devices as you want, and you pay only when the devices connect to and exchange data with Cloud IoT Core. To make it simple to build quick prototypes with just a few devices, we have added a free tier that lets you try the service at no cost.
Ready to take it for a spin? To get started check out this quick-start tutorial on Cloud IoT Core. We look forward to your feedback and are excited to see what you build!
Quelle: Google Cloud Platform
Trotz der Sicherheitslücken in der Software "PC-Wahl" konnten die IT-Dienstleister der Kommunen "keine besonderen Vorkommnisse" zur Bundestagswahl feststellen. Störungen habe es fast keine gegeben.
Quelle: Heise Tech News
Fritzboxen gehören zu den besten Routern auf dem Markt. c‘t Netzwerke 2017 hilft bei der Wahl des passenden Modells und zeigt Tuning-Projekte, die mehr aus der Berliner Box rausholen. Außerdem: Router-Alternativen, Heimnetz-Sicherheit und WLAN-Praxis.
Quelle: Heise Tech News
This blog post was co-authored by Vitaly Gorbenko, Senior Program Manager, Azure Monitor and Anirudh Cavale, Program Manager, Azure Monitor.
Earlier this year we announced the general availability of Azure Monitor, Microsoft’s built-in platform monitoring service for Azure. The service enables users to access native resource metrics to gain visibility into the performance and health of their workloads in Azure. Since its launch, we have seen enormous growth in the usage of Azure Monitor metrics and heard some great feedback. Today, we are excited to announce some new additions to the metrics ecosystem. They enable you to seamlessly visualize your metrics, monitor more Azure resources, and unlock deeper insights with the addition of dimensions to metrics.
More metrics, for more Azure resources!
Many of you have provided us with feedback around making metrics available for more Azure resources. We are happy to announce additional Azure resources that now have metrics available via Azure Monitor, enabling more visibility into the state and performance of your Azure workloads. All of these metrics can be accessed via the Azure Portal and via the Azure Monitor REST APIs.
Please welcome the following resources to the Azure Monitor family:
Automation: Get visibility into the number of jobs your Azure Automation account is running.
Autoscale: Metrics are now available to help you understand how your Autoscale settings are being evaluated, what metric values are being read, and what scale actions are being taken.
Classic Compute: You can now access host metrics like Network In/Out, Disk Reads/Writes, CPU Percentage etc. for your Classic Compute VMs.
CosmosDB: Determine what the request count for your CosmosDB is by region, database, collection, and status code.
DataLake Analytics: Get visibility into the number of successful, failed, and cancelled jobs in your DataLake Analytics accounts, even measure the total AU time for those jobs.
DataLake Store: Gain insight into the amount of data being stored, written, and read in your DataLake Store accounts.
Express Route: You can now measure the total bytes ingressing and egressing your Express Route circuits.
Public IP Addresses: Metrics are now available to help you understand the inbound packets and bytes being forwarded or dropped for your Public IP Address resources.
Software Load Balancer: You can now query for the availability of your VIP and DIP endpoints for your load balancers.
Storage: You can now access capacity and transaction metrics for a storage account and its underlying services (blobs, files, tables, queues). Learn more about the new Azure storage metrics.
Traffic Manager: View the availability and query metrics for your traffic manager profile and endpoints.
Virtual Network Gateways: Get visibility into the throughput, bytes in, bytes out, packets in, packets out for your VPN Gateways.
A complete list of all the resources and metrics available via Azure Monitor can be found here.
Multi-Dimensional Metrics (public preview)
You also provided feedback that while more metrics are good, you need deeper visibility into the performance of your resources that can help you troubleshoot faster.
In addition to a host of new resource types offering metrics, the Azure Monitor now supports a public preview of multi-dimensional metrics. Native metrics can now have dimensions associated with them. Dimensions are name-value pairs, or attributes, that can be used to further segment a metric; these additional attributes can help make exploring a metric more meaningful.
Let’s look at the metrics of a Blob where your application is writing data to and other apps are reading data from. You expect the Blob writes and reads operations to happen very fast (in just a few milliseconds) to support your mission critical business apps. Prior to the dimension support, you could just use the overall ‘Success E2E Latency’ metric to monitor the average latency. Today, using the new dimensions support, you can break this metric down by the dimension – ‘API Name’. Here is the comparison of the same metric across all API names vs. a break-down by API name.
Metrics Name
Metrics Value: Average (ms)
Success E2E Latency
20
Metric Name
API Name
Metric Value: Average (ms)
Success E2E Latency
Get Block List
50
Success E2E Latency
Put Block List
46
Success E2E Latency
Put Block
18
Success E2E Latency
Get Container Properties
7.0
Success E2E Latency
Acquire Blob Lease
6.4
Success E2E Latency
Release Blob Lease
5.9
Success E2E Latency
Get Blob Properties
3.6
With this you can now learn that the Transactions with ‘Get Block List’ API name take more time than others.
Services like Azure Storage, API Management, and Traffic Manager are already emitting multi-dimensional metrics. A full list of resource emitting metrics, and their respective dimensions, can be found here.
New Metric Charting Experience (public preview)
As part of the multi-dimensional metrics ecosystem, we are introducing our brand-new metrics charting experience that you can use to render charts for both multi-dimensional, and basic metrics with no dimensions. The charts in the new experience can overlay metrics across different resource types, resource groups and subscriptions, and can be customized by applying filters and segmentation. After customizing the charts, you can pin them to dashboards and share with other team members.
Going back to the ‘Success E2E Latency’ metric example from above, we use the new experience to explore the average latency of transactions for a Storage resource, and corelate it to the application metric. The top chart below is segmented on the “API name” dimension to plot the average end-to-end (E2E) transaction latency broken down by API name. The bottom chart illustrates an Application Insights metric ‘Server Requests’, customized to show the volume of successful web requests that returned response code 200, and split them by the country from which the requests were made.
We are excited for you to start exploring multi-dimensional metrics and this powerful new charting experience!
Programmatic access
Users can also query for multi-dimensional metrics using our new REST API (preview) version. Discover the metrics and dimensions for resources, and query for their metric values. Follow these links to get more documentation on the Azure Monitor metric definitions REST API and the metrics REST API. We will soon be publishing .NET and Java SDKs, and adding support for PowerShell and CLI 2.0.
Wrapping up
In summary, Azure Monitor continues to grow and make more metrics available for more Azure resources. You now have a new experience that allows you to drill down further into metrics and filter them as needed. In the coming months, you can expect to see more services emitting metric and log data through Azure Monitor. Moreover, you will be able to create alert rules on these metrics filtered by their dimensions. Drop us a comment, email us, or head over to user voice and let us know what you think!
Quelle: Azure
Mit der kommenden Version 13 will Nextcloud Ende-zu-Ende-Verschlüsselung in seinen Cloud-Speicherdienst einbauen. Die soll verzeichnisbasiert funktionieren, einfach sein und für den Unternehmenseinsatz taugen. (Nextloud, Verschlüsselung)
Quelle: Golem
Auch Vodafone hat einen Tarif eingeführt, bei dem bestimmte Dienste nicht mehr das Datenvolumen belasten. Die Bundesnetzagentur nimmt das unter die Lupe.
Quelle: Heise Tech News
