Security updates have been issued by Arch Linux (tomcat7), Debian (kernel and perl), Fedora (libwmf and mpg123), Mageia (bluez, ffmpeg, gstreamer0.10-plugins-good, gstreamer1.0-plugins-good, libwmf, tomcat, and tor), openSUSE (emacs, fossil, freexl, php5, and xen), Red Hat (augeas, rh-mysql56-mysql, samba, and samba4), Scientific Linux (augeas, samba, and samba4), Slackware (samba), SUSE (emacs and kernel), and Ubuntu (qemu).
To make managing your AWS account easier, some AWS services perform actions on your behalf, including the creation and management of AWS resources. For example, AWS Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring. To make these AWS actions more transparent, AWS adds an AWS Identity and Access Management (IAM) service-linked roles to your account for each linked service you use. Service-linked roles let you view all actions an AWS service performs on your behalf by using AWS CloudTrail logs. This helps you monitor and audit the actions AWS services perform on your behalf. No additional actions are required from you and you can continue using AWS services the way you do today.
To learn more about which AWS services use service-linked roles and log actions on your behalf to CloudTrail, see AWS Services That Work with IAM. Over time, more AWS services will support service-linked roles. For more information about service-linked roles, see Role Terms and Concepts.
In this blog post, I demonstrate how to view CloudTrail logs so that you can more easily monitor and audit AWS services performing actions on your behalf. First, I show how AWS creates a service-linked role in your account automatically when you configure an AWS service that supports service-linked roles. Next, I show how you can view the policies of a service-linked role that grants an AWS service permission to perform actions on your behalf. Finally, I use the configured AWS service to perform an action and show you how the action appears in your CloudTrail logs.
How AWS creates a service-linked role in your account automatically
I will use Amazon Lex as the AWS service that performs actions on your behalf for this post. You can use Amazon Lex to create chatbots that allow for highly engaging conversational experiences through voice and text. You also can use chatbots on mobile devices, web browsers, and popular chat platform channels such as Slack. Amazon Lex uses Amazon Polly on your behalf to synthesize speech that sounds like a human voice.
Amazon Lex uses two IAM service-linked roles:
- AWSServiceRoleForLexBots — Amazon Lex uses this service-linked role to invoke Amazon Polly to synthesize speech responses for your chatbot.
- AWSServiceRoleForLexChannels — Amazon Lex uses this service-linked role to post text to your chatbot when managing channels such as Slack.
You don’t need to create either of these roles manually. When you create your first chatbot using the Amazon Lex console, Amazon Lex creates the AWSServiceRoleForLexBots role for you. When you first associate a chatbot with a messaging channel, Amazon Lex creates the AWSServiceRoleForLexChannels role in your account.
1. Start configuring the AWS service that supports service-linked roles
Navigate to the Amazon Lex console, and choose Get Started to navigate to the Create your Lex bot page. For this example, I choose a sample chatbot called OrderFlowers. To learn how to create a custom chatbot, see Create a Custom Amazon Lex Bot.
2. Complete the configuration for the AWS service
When you scroll down, you will see the settings for the OrderFlowers chatbot. Notice the field for the IAM role with the value, AWSServiceRoleForLexBots. This service-linked role is “Automatically created on your behalf.” After you have entered all details, choose Create to build your sample chatbot.
AWS has created the AWSServiceRoleForLexBots service-linked role in your account. I will return to using the chatbot later in this post when I discuss how Amazon Lex performs actions on your behalf and how CloudTrail logs these actions. First, I will show how you can view the permissions for the AWSServiceRoleForLexBots service-linked role by using the IAM console.
How to view actions in the IAM console that AWS services perform on your behalf
When you configure an AWS service that supports service-linked roles, AWS creates a service-linked role in your account automatically. You can view the service-linked role by using the IAM console.
1. View the AWSServiceRoleForLexBots service-linked role on the IAM console
Go to the IAM console, and choose AWSServiceRoleForLexBots on the Roles page. You can confirm that this role is a service-linked role by viewing the Trusted entities column.
2.View the trusted entities that can assume the AWSServiceRoleForLexBots service-linked role
Choose the Trust relationships tab on the AWSServiceRoleForLexBots role page. You can view the trusted entities that can assume the AWSServiceRoleForLexBots service-linked role to perform actions on your behalf. In this example, the trusted entity is lex.amazonaws.com.
3. View the policy attached to the AWSServiceRoleForLexBots service-linked role
Choose AmazonLexBotPolicy on the Permissions tab to view the policy attached to the AWSServiceRoleForLexBots service-linked role. You can view the policy summary to see that AmazonLexBotPolicy grants permission to Amazon Lex to use Amazon Polly.
4. View the actions that the service-linked role grants permissions to use
Choose Polly to view the action, SynthesizeSpeech, that the AmazonLexBotPolicy grants permission to Amazon Lex to perform on your behalf. Amazon Lex uses this permission to synthesize speech responses for your chatbot. I show later in this post how you can monitor this SynthesizeSpeech action in your CloudTrail logs.
Now that I know the trusted entity and the policy attached to the service-linked role, let’s go back to the chatbot I created earlier and see how CloudTrail logs the actions that Amazon Lex performs on my behalf.
How to use CloudTrail to view actions that AWS services perform on your behalf
As discussed already, I created an OrderFlowers chatbot on the Amazon Lex console. I will use the chatbot and display how the AWSServiceRoleForLexBots service-linked role helps me track actions in CloudTrail. First, though, I must have an active CloudTrail trail created that stores the logs in an Amazon S3 bucket. I will use a trail called TestTrail and an S3 bucket called account-ids-slr.
1. Use the Amazon Lex chatbot via the Amazon Lex console
In Step 2 in the first section of this post, when I chose Create, Amazon Lex built the OrderFlowers chatbot. After the chatbot was built, the right pane showed that a Test Bot was created. Now, I choose the microphone symbol in the right pane and provide voice input to test the OrderFlowers chatbot. In this example, I tell the chatbot, “I would like to order some flowers.” The bot replies to me by asking, “What type of flowers would you like to order?”
When the chatbot replies using voice, Amazon Lex uses Amazon Polly to synthesize speech from text to voice. Amazon Lex assumes the AWSServiceRoleForLexBots service-linked role to perform the SynthesizeSpeech action.
2. Check CloudTrail to view actions performed on your behalf
Now that I have created the chatbot, let’s see which actions were logged in CloudTrail. Choose CloudTrail from the Services drop-down menu to reach the CloudTrail console. Choose Trails and choose the S3 bucket in which you are storing your CloudTrail logs.
In the S3 bucket, you will find log entries for the SynthesizeSpeech event. This means that CloudTrail logged the action when Amazon Lex assumed the AWSServiceRoleForLexBots service-linked role to invoke Amazon Polly to synthesize speech responses for your chatbot. You can monitor and audit this invocation, and it provides you with transparency into Amazon Polly’s SynthesizeSpeech action that Amazon Lex invoked on your behalf. The applicable CloudTrail log section follows and I have emphasized the key lines.
Service-linked roles make it easier for you to track and view actions that linked AWS services perform on your behalf by using CloudTrail. When an AWS service supports service-linked roles to enable this additional logging, you will see a service-linked role added to your account.
If you have comments about this post, submit a comment in the “Comments” section below. If you have questions about working with service-linked roles, start a new thread on the IAM forum or contact AWS Support.
Security updates have been issued by Arch Linux (apache and ettercap), Debian (gdk-pixbuf and newsbeuter), Red Hat (kernel), Slackware (httpd, libgcrypt, and ruby), SUSE (kernel), and Ubuntu (bind9, kernel, libidn2-0, libxml2, linux, linux-aws, linux-gke, linux-kvm, linux-raspi2, linux-snapdragon, linux, linux-raspi2, linux-hwe, linux-lts-trusty, and linux-lts-xenial).
Security updates have been issued by Arch Linux (ffmpeg, lib32-libgcrypt, libgcrypt, linux-zen, and newsbeuter), Debian (emacs25, freexl, and tomcat8), Fedora (cyrus-imapd, FlightGear, freexl, gdm, kernel, LibRaw, ruby, and xen), Gentoo (binutils, chkrootkit, curl, gdk-pixbuf, gimps, git, kpathsea, mod_gnutls, perl, squirrelmail, subversion, supervisor, and webkit-gtk), Mageia (389-ds-base, kernel, kernel-linus, kernel-tmb, and mpg123), openSUSE (ffmpeg, ffmpeg2, qemu, and xen), Slackware (kernel), SUSE (xen), and Ubuntu (gdk-pixbuf).
Security updates have been issued by Arch Linux (bluez and linux-hardened), CentOS (bluez and kernel), Debian (bluez, emacs24, tcpdump, and xen), Fedora (kernel and mimedefang), Oracle (bluez and kernel), Red Hat (bluez, flash-plugin, instack-undercloud, kernel, kernel-rt, and openvswitch), Scientific Linux (bluez and kernel), Slackware (emacs and libzip), SUSE (xen), and Ubuntu (bluez and qemu).
Security updates have been issued by Debian (freerdp, mbedtls, tiff, and tiff3), Fedora (chromium, krb5, libstaroffice, mbedtls, mingw-libidn2, mingw-openjpeg2, openjpeg2, and rubygems), Mageia (bzr, libarchive, libgcrypt, and tcpdump), openSUSE (gdk-pixbuf, libidn2, mpg123, postgresql94, postgresql96, and xen), Slackware (bash, mariadb, and tcpdump), and SUSE (evince and kernel).
A couple of months ago on the blog, I announced the AWS Chatbot Challenge in conjunction with Slack. The AWS Chatbot Challenge was an opportunity to build a unique chatbot that helped to solve a problem or that would add value for its prospective users. The mission was to build a conversational, natural language chatbot using Amazon Lex and leverage Lex’s integration with AWS Lambda to execute logic or data processing on the backend.
I know that you all have been anxiously waiting to hear announcements of who were the winners of the AWS Chatbot Challenge as much as I was. Well wait no longer, the winners of the AWS Chatbot Challenge have been decided.
May I have the Envelope Please? (The Trumpets sound)
The winners of the AWS Chatbot Challenge are:
- First Place: BuildFax Counts by Joe Emison
- Second Place: Hubsy by Andrew Riess, Andrew Puch, and John Wetzel
- Third Place: PFMBot by Benny Leong and his team from MoneyLion.
- Large Organization Winner: ADP Payroll Innovation Bot by Eric Liu, Jiaxing Yan, and Fan Yang
Diving into the Winning Chatbot Projects
Let’s take a walkthrough of the details for each of the winning projects to get a view of what made these chatbots distinctive, as well as, learn more about the technologies used to implement the chatbot solution.
BuildFax Counts by Joe Emison
The BuildFax Counts bot was created as a real solution for the BuildFax company to decrease the amount the time that sales and marketing teams can get answers on permits or properties with permits meet certain criteria.
BuildFax, a company co-founded by bot developer Joe Emison, has the only national database of building permits, which updates data from approximately half of the United States on a monthly basis. In order to accommodate the many requests that come in from the sales and marketing team regarding permit information, BuildFax has a technical sales support team that fulfills these requests sent to a ticketing system by manually writing SQL queries that run across the shards of the BuildFax databases. Since there are a large number of requests received by the internal sales support team and due to the manual nature of setting up the queries, it may take several days for getting the sales and marketing teams to receive an answer.
The BuildFax Counts chatbot solves this problem by taking the permit inquiry that would normally be sent into a ticket from the sales and marketing team, as input from Slack to the chatbot. Once the inquiry is submitted into Slack, a query executes and the inquiry results are returned immediately.
The BuildFax Counts bot is used today for the BuildFax sales and marketing team to get back data on inquiries immediately that previously took up to a week to receive results.
Not only is BuildFax Counts bot our 1st place winner and wonderful solution, but its creator, Joe Emison, is a great guy. Joe has opted to donate his prize; the $5,000 cash, the $2,500 in AWS Credits, and one re:Invent ticket to the Black Girls Code organization. I must say, you rock Joe for helping these kids get access and exposure to technology.
Hubsy by Andrew Riess, Andrew Puch, and John Wetzel
Hubsy bot was created to redefine and personalize the way users traditionally manage their HubSpot account. HubSpot is a SaaS system providing marketing, sales, and CRM software. Hubsy allows users of HubSpot to create engagements and log engagements with customers, provide sales teams with deals status, and retrieves client contact information quickly. Hubsy uses Amazon Lex’s conversational interface to execute commands from the HubSpot API so that users can gain insights, store and retrieve data, and manage tasks directly from Facebook, Slack, or Alexa.
In order to implement the Hubsy chatbot, Andrew and the team members used AWS Lambda to create a Lambda function with Node.js to parse the users request and call the HubSpot API, which will fulfill the initial request or return back to the user asking for more information. Terraform was used to automatically setup and update Lambda, CloudWatch logs, as well as, IAM profiles. Amazon Lex was used to build the conversational piece of the bot, which creates the utterances that a person on a sales team would likely say when seeking information from HubSpot. To integrate with Alexa, the Amazon Alexa skill builder was used to create an Alexa skill which was tested on an Echo Dot. Cloudwatch Logs are used to log the Lambda function information to CloudWatch in order to debug different parts of the Lex intents. In order to validate the code before the Terraform deployment, ESLint was additionally used to ensure the code was linted and proper development standards were followed.
PFMBot by Benny Leong and his team from MoneyLion
PFMBot, Personal Finance Management Bot, is a bot to be used with the MoneyLion finance group which offers customers online financial products; loans, credit monitoring, and free credit score service to improve the financial health of their customers. Once a user signs up an account on the MoneyLion app or website, the user has the option to link their bank accounts with the MoneyLion APIs. Once the bank account is linked to the APIs, the user will be able to login to their MoneyLion account and start having a conversation with the PFMBot based on their bank account information.
ADP Payroll Innovation Bot by Eric Liu, Jiaxing Yan, and Fan Yang
ADP PI (Payroll Innovation) bot is designed to help employees of ADP customers easily review their own payroll details and compare different payroll data by just asking the bot for results. The ADP PI Bot additionally offers issue reporting functionality for employees to report payroll issues and aids HR managers in quickly receiving and organizing any reported payroll issues.
The ADP Payroll Innovation bot is an ecosystem for the ADP payroll consisting of two chatbots, which includes ADP PI Bot for external clients (employees and HR managers), and ADP PI DevOps Bot for internal ADP DevOps team.
The architecture for the ADP PI DevOps bot is different architecture from the ADP PI bot shown above as it is deployed internally to ADP. The ADP PI DevOps bot allows input from both Slack and Alexa. When input comes into Slack, Slack sends the request to Lex for it to process the utterance. Lex then calls the Lambda backend, which obtains ADP data sitting in the ADP VPC running within an Amazon VPC. When input comes in from Alexa, a Lambda function is called that also obtains data from the ADP VPC running on AWS.
The architecture for the ADP PI bot consists of users entering in requests and/or entering issues via Slack. When requests/issues are entered via Slack, the Slack APIs communicate via Amazon API Gateway to AWS Lambda. The Lambda function either writes data into one of the Amazon DynamoDB databases for recording issues and/or sending issues or it sends the request to Lex. When sending issues, DynamoDB integrates with Trello to keep HR Managers abreast of the escalated issues. Once the request data is sent from Lambda to Lex, Lex processes the utterance and calls another Lambda function that integrates with the ADP API and it calls ADP data from within the ADP VPC, which runs on Amazon Virtual Private Cloud (VPC).
The ADP PI bot ecosystem has the following functional groupings:
- Summarize Payrolls
- Compare Payrolls
- Escalate Issues
- Evolve PI Bot
HR Manager Functionality
- Bot Management
- Audit and Feedback
- Reduce call volume in service centers (ADP PI Bot).
- Track issues and generate reports (ADP PI Bot).
- Monitor jobs for various environment (ADP PI DevOps Bot)
- View job dashboards (ADP PI DevOps Bot)
- Query job details (ADP PI DevOps Bot)
Let’s all wish all the winners of the AWS Chatbot Challenge hearty congratulations on their excellent projects.
You can review more details on the winning projects, as well as, all of the submissions to the AWS Chatbot Challenge at: https://awschatbot2017.devpost.com/submissions. If you are curious on the details of Chatbot challenge contest including resources, rules, prizes, and judges, you can review the original challenge website here: https://awschatbot2017.devpost.com/.
Hopefully, you are just as inspired as I am to build your own chatbot using Lex and Lambda. For more information, take a look at the Amazon Lex developer guide or the AWS AI blog on Building Better Bots Using Amazon Lex (Part 1)
Chat with you soon!
Security updates have been issued by CentOS (firefox, httpd, and java-1.7.0-openjdk), Fedora (cups-filters, potrace, and qpdf), Mageia (libsoup and mingw32-nsis), openSUSE (kernel), Oracle (httpd, kernel, spice, and subversion), Red Hat (httpd, java-1.7.1-ibm, and subversion), Scientific Linux (httpd), Slackware (xorg), SUSE (java-1_8_0-openjdk), and Ubuntu (firefox, linux, linux-aws, linux-gke, linux-raspi2, linux-snapdragon, linux-lts-xenial, postgresql-9.3, postgresql-9.5, postgresql-9.6, and ubufox).
Security updates have been issued by Debian (botan1.10, cvs, firefox-esr, iortcw, libgd2, libgxps, supervisor, and zabbix), Fedora (curl, firefox, git, jackson-databind, libgxps, libsoup, openjpeg2, potrace, python-dbusmock, spatialite-tools, and sqlite), Mageia (cacti, ffmpeg, git, heimdal, jackson-databind, kernel-linus, kernel-tmb, krb5, php-phpmailer, ruby-rubyzip, and supervisor), openSUSE (firefox, librsvg, libsoup, ncurses, and tcmu-runner), Oracle (firefox), Red Hat (java-1.8.0-ibm), Slackware (git, libsoup, mercurial, and subversion), and SUSE (kernel).
Security updates have been issued by Debian (firefox-esr), Fedora (cacti, community-mysql, and pspp), Mageia (varnish), openSUSE (mariadb, nasm, pspp, and rubygem-rubyzip), Oracle (evince, freeradius, golang, java-1.7.0-openjdk, log4j, NetworkManager and libnl3, pki-core, qemu-kvm, and X.org), Red Hat (flash-plugin), and Slackware (curl and mozilla).
Post Syndicated from Eevee original https://eev.ee/dev/2017/08/09/weekly-roundup-taking-a-breather/
Nothing too special about this week; it went a little slow, but that’s been nice after the mad panic I was in at the end of July.
cc: I’m getting the hang of Unity and forming an uneasy truce with C#. Mostly did refactoring of some existing actor code, trying to move all the reading of controls to a single place so the rest of it can be reused for non-players.
fox flux: I put some work into a new forest background, which is already just… hilariously better than the one from the original game. Complex textures like leaves are one of my serious weak points, but this is forcing me to do it anyway and I’m slowly learning.
blog: I finished that post on Pokémon datamining, which ended up extraordinarily long and slightly late.
veekun: Dug into some missing stuff regarding items.
art: Spent a day or two doodling.
Still behind by one blog post (oops), and slacked on veekun a bit, but I’ve still got momentum.
Post Syndicated from Blogs on Grafana Labs Blog original https://grafana.com/blog/2017/08/04/timeshiftgrafanabuzz-1w-issue-7/
Hard to believe it’s already August! This week there were a ton of articles to highlight. It’s really exciting to see how many data aficionados there are out there coming up with new ways to connect Grafana to their data, wherever it may live. In this issue we cover crypto currency visualization, home automation setups and breakdown the installation in a number of environments. Enjoy!
Grafana 4.4.2 Released
From the Blogosphere
Monitoring CouchDB with Prometheus, Grafana and Docker: Geoff walks us through all of the steps to get Prometheus, Alertmanager and Grafana installed in Docker to monitor and alert on a CouchDB cluster. These six steps will have you up and running in no time.
Try InfluxDB and Grafana by Docker: Continuing with our Docker theme, Xiao breaks down all of the pieces, explores the configuration options, and explains the Docker commands to setup a simple monitoring stack by using collectd, InfluxDB and Grafana.
Installation of Collectd, Graphite and Grafana – Part 2: Last week we covered the first article in a series focused on setting up a complete Graphite stack. This week we tackle installing Graphite, its components, and Grafana on the server.
Grafana and Home Automation: More and more pieces of our homes are becoming “smart”, so why not monitor them? This article walks you through collecting data from home automation software Jeedom, sending metrics to InfluxDB, and visualizing and alerting in Grafana – so you can know how your smart-toaster is performing.
Making an Awesome Dashboard for your Crypto Currencies in 3 Steps: Christian lays out three steps that will help you keep an eye on your Bitcoin and Ethereum investments. His PHP script fetches things like current price, current balances, earnings, and sends the data to InfluxDB via UDP. He’s also created a dashboard that’s ready to import so you can get back to mining.
FHEM #6 – Grafana and InfluxDB: We’re seeing more and more articles about using Grafana to monitor home automation. This is the sixth article in a series getting data from FHEM into Grafana using InfdluxDB. It also touches on connecting Grafana to MariaDB, taking advantage of Grafana’s alpha native MySQL support.
Installation Overview of Node Exporter, Prometheus and Grafana: Looking to get started with Prometheus? Frits walks us through installing Node Exporter, Prometheus, and Grafana and importing our first dashboard.
Collect Metrics from Liberty Apps and Display in Grafana: This in-depth article covers adding custom metrics to your Liberty application and how to monitor these metrics using collectd, Graphite and Grafana.
Gatling, Graphite, Grafana: Your Application Under High Surveillance!: David explores Gatling, for load testing which can write the data to Graphite and over to Grafana for visualization and alerting.
Plugins and Dashboards
Last week’s timeShift was packed full of plugin updates, as well as a couple of new ones. This week was a little quieter on the plugin front, but we still have a new data source plugin to announce. It’s easy to install this new plugin via the grafana-cli for an on-prem Grafana instance, or a 1-click install on Hosted Grafana.
PRTG Data Source – This data source visualizes data from the Paessler PRTG monitoring system. The easy to use query editor included with this plugin gives access to an array of PRTG metadata properties including Status, Message, Active, Tags, Priority, and more. Annotation support to show sensor status messages on graphs.
This week’s MVC (Most Valuable Contributor)
This week we highlight a contributor who is going to make everyone waiting for Elasticsearch alerting in Grafana jump for joy!
Tweet of the Week
We scour Twitter each week to find an interesting/beautiful dashboard and show it off! #monitoringLove
Having fun with pflogsumm and mailq, I'm addicted! I turn boring numbers into beautiful dashboards. How to monitor Zimbra with Grafana, soon pic.twitter.com/WFNtg7vHNk
— Jorge de la Cruz (@jorgedlcruz) August 2, 2017
We love when people talk about Grafana at meetups and conferences.
Wednesday, August 16, 2017 – 7:30pm | Apprenda HQ
433 River Street, 4th Floor, Troy, NY
Kubernetes focused event! demo from Apprenda and how Kubernetes is used @ GitHub:
Steve Wade, is a Principal Kubernetes Consultant from London and will be providing some fundamental information about the Kubernetes ecosystem as well as overview of its core components. He’ll also talk about some monitoring and alerting best practices learned from working with Kubernetes customers and demo how Prometheus, Grafana and Slack can be used to monitor, visualize and alert on both the Kubernetes platform as well as application workloads.
Aaron Brown, a Site Reliability Engineer at Github, will dive into the ways in which Kubernetes is used within Github to make software development and deployment more efficient.
What do you think?
Please tell us how we’re doing. We want to make sure this continues to be a valuable resource for the Grafana community. Submit a comment on this article below, or post something at our community forum. Help us make this better!
Security updates have been issued by Debian (varnish), Fedora (gcc, gcc-python-plugin, libtool, mingw-c-ares, and php-PHPMailer), Red Hat (bash, curl, evince, freeradius, gdm and gnome-session, ghostscript, git, glibc, golang, GStreamer, gtk-vnc, kernel, kernel-rt, libtasn1, mariadb, openldap, openssh, pidgin, postgresql, python, qemu-kvm, qemu-kvm-rhev, samba, tigervnc and fltk, tomcat, and X.org X11 libraries), Slackware (gnupg), and Ubuntu (apache2, lxc, and webkit2gtk).
Security updates have been issued by Debian (apache2, enigmail, graphicsmagick, ipsec-tools, libquicktime, lucene-solr, mysql-5.5, nasm, and supervisor), Fedora (mingw-librsvg2, php-PHPMailer, and webkitgtk4), Mageia (freeradius, gdk-pixbuf2.0, graphicsmagick, java-1.8.0-openjdk, kernel, libmtp, libgphoto, libraw, nginx, openvpn, postgresql9.4, valgrind, webkit2, and wireshark), openSUSE (apache2, chromium, libical, mysql-community-server, and nginx), Oracle (kernel), Red Hat (chromium-browser and eap7-jboss-ec2-eap), Slackware (squashfs), and Ubuntu (linux-hwe and nss).
Post Syndicated from Ben Nuttall original https://www.raspberrypi.org/blog/raspberry-jam-big-birthday-weekend-2018/
For the last few years, we have held a big Raspberry Pi community event in Cambridge around Raspberry Pi’s birthday, where people have come together for a huge party with talks, workshops, and more. We want more people to have the chance to join in with our birthday celebrations next year, so we’re going to be coordinating Raspberry Jams all over the world to take place over the Raspberry Jam Big Birthday Weekend, 3–4 March 2018.
Big Birthday fun!
Whether you’ve run a Raspberry Jam before, or you’d like to start a new Jam in your area, we invite you to join us for our Big Birthday Weekend, wherever you are in the world. This event will be a community-led, synchronised, global mega-Jam in celebration of our sixth birthday and the digital making community! Members of the Raspberry Pi Foundation team will be attending Jams far and wide to celebrate with you during the weekend.
Jams across the world will receive a special digital pack – be sure to register your interest so we can get your pack to you! We’ll also be sending out party kits to registered Jams – more info on this below.
Need help getting started?
If there’s no Jam near you yet, the Raspberry Jam Big Birthday Weekend is the perfect opportunity to start one yourself! If you’d like some help getting your Jam off the ground, there are a few places you can get support:
- The Raspberry Jam Guidebook is full of advice gathered from the amazing people who run Jams in the UK.
- The Raspberry Jam Slack team is available for Jam organisers to chat, share ideas, and get help from each other. Just email jam [at] raspberrypi.org and ask to be invited.
- Attend a Jam! Find an upcoming Jam near you, and go along to get an idea of what it’s like.
- Email us – if you have more queries, you can email jam [at] raspberrypi.org and we’ll do what we can to help.
If you’re keen to start a new Jam, there’s no need to wait until March – why not get up and running over the summer? Then you’ll be an expert by the time the Raspberry Jam Big Birthday Weekend comes around. Check out the guidebook, join the Jam Slack, and submit your event to the map when you’re ready.
Like the idea of running a Jam, but don’t want to do it by yourself? Then feel free to email us, and we’ll try and help you find someone to co-organise it.
If you don’t fancy organising a Jam for our Big Birthday Weekend, but would like to celebrate with us, keep an eye on our website for an update early next year. We’ll publish a full list of Jams participating in the festivities so you can find one near you. And if you’ve never attended a Jam before, there’s no need to wait: find one to join on the map here.
Register your interest
If you think you’d like to run a Jam as part of the Big Birthday Weekend, register your interest now, and you’ll be the first to receive updates. Don’t worry if you don’t have the venue or logistics in place yet – this is just to let us know you’re keen, and to give us an idea about how big our party is going to be.
We will contact you in autumn to give you more information, as well as some useful resources. On top of our regular Raspberry Jam branding pack, we’ll provide a special digital Big Birthday Weekend pack to help you celebrate and tell everyone about your Jam!
Then, once you have confirmed you’re taking part, you’ll be able to register your Jam on our website. This will make sure that other people interested in joining the party can find your event. If your Jam is among the first 150 to be registered for a Big Birthday Weekend event, we will send you a free pack of goodies to use on the big day!
Go fill in the form, and we’ll be in touch!
PS: We’ll be running a big Cambridge event in the summer on the weekend of 30 June–1 July 2018. Put it in your diary – we’ll say more about it as we get closer to the date.
The post Announcing the Raspberry Jam Big Birthday Weekend 2018 appeared first on Raspberry Pi.
Security updates have been issued by Debian (catdoc, gsoap, and libtasn1-3), Fedora (GraphicsMagick, java-1.8.0-openjdk, krb5, librsvg2, nodejs, phpldapadmin, rubygem-rack-cors, and yara), Mageia (irssi), openSUSE (rubygem-puppet), Red Hat (kernel), Slackware (tcpdump), and Ubuntu (imagemagick, linux, linux-raspi2, linux-snapdragon, linux-lts-xenial, mysql-5.5, samba, and xorg-server, xorg-server-hwe-16.04, xorg-server-lts-xenial).
Security updates have been issued by CentOS (graphite2 and java-1.8.0-openjdk), Debian (atril, bind9, catdoc, and qemu), Fedora (glpi, GraphicsMagick, heimdal, kernel, nodejs, perl-XML-LibXML, and qt5-qtwebengine), Gentoo (adobe-flash), Mageia (c-ares, expat, flash-player-plugin, gnutls, libgcrypt, libtiff, sane, and tnef), openSUSE (evince and xorg-x11-server), Scientific Linux (graphite2), Slackware (seamonkey), and Ubuntu (heimdal and linux-lts-trusty).
Post Syndicated from Yev original https://www.backblaze.com/blog/why-consumer-design-is-good-for-business/
We know that business users sometimes ask, “Why can’t business software be as easy to use as consumer software?”
At Backblaze, we believe it can be.
We started our business to make backup easier for everyone, knowing that the primary reason why people don’t backup is that it is too complicated and too intimidating.
Backblaze has spent the last decade building an unlimited, inexpensive, and best of all easy-to-use backup service. We designed it from the ground up, with the goal of making it a simple service – one that “just works.” We wanted it to be the easiest backup solution for grandmothers and IT administrators alike.
Having a product that’s intuitive and easy makes it ideal for people that don’t want to fret about backing up or worrying about whether or not the they selected the right files when their backup system was set up. Backblaze backs up all user data by default so there’s no worrying about missing something. What that means is when you use Backblaze for Business – you’re getting a solution that works out of the box not just for the end-user, but also for the account administrator.
Design for Enterprise Scalability but With Consumer Simplicity
Often times when a product is designed “for enterprise” the result can be an unintuitive piece of software that only the systems administrators can navigate. While that may be acceptable for antivirus or anti-spam software, there are many products and services that should not require hours to learn to use. Some of the most common services that businesses use today are known for their ease-of-use. Dropbox Sync, Trello, and Slack come to mind.
Backblaze Online Backup is much the same. Regardless of whether you have one computer or are deploying to an organization of 1,000, Backblaze scales so that you and all your users get the same, simple service that backs up and makes data accessible.
Overcomplexity reduces efficiency
The last thing an IT professional wants is users asking them how a program on their computer works, or complaining about a process that’s supposed to be running in the background. The more bloated and over-designed products and services get, the more stumbling blocks appear before the end-user. When you’re developing a product there’s a fine line between adding features and creating an overwhelmingly complicated user interface. The cost of getting that balance wrong is that it will raise more questions than it provides answers, leaving customers and end-users confused with too many choices. Many of the players in the online backup space have made confusing design choices that leave customers perplexed. We believe easy is better for everyone.
Backblaze for Business is built on top of our award winning Computer Backup product that has been in market for over 10 years. We have over 350 PB under storage and have helped users save over 23 BILLION files. We know a lot about backup.
But businesses have unique needs, such as centralized user management and billing, reporting, monitoring usage, and the ability to act on behalf of any user. When an end-user (or the IT admin) installs Backblaze, the backup starts automatically, backing up all the user-data on the machine. There’s no need to select files or folders. The backup process just starts, because all of the data is important. We’ve heard time and time again that a user’s files were saved because we backed up an obscure directory where one or two important files would have been forgotten about had the user been forced to choose what to back up.
Backblaze just works—for everyone
The best products are the ones that don’t impede your workflow and work seamlessly with the processes you have in place. Which is another reason having something designed with the end-user in mind is helpful. You build software that is aware of its environment (not everyone has top-of-the-line computing systems) and stays out of the way.
Making sure that people are diligent about their backup strategy is hard enough. At Backblaze we believe that simplicity is key, and that’s why we designed a backup service that scales from 1 to 10,000 — without having to change a setting.
Security updates have been issued by Arch Linux (apache, evince, and mosquitto), Debian (apache2, evince, heimdal, and knot), Fedora (c-ares, cacti, evince, GraphicsMagick, httpd, jabberd, libgcrypt, openvas-cli, openvas-gsa, openvas-libraries, openvas-manager, openvas-scanner, poppler, qt5-qtwebengine, qt5-qtwebkit, spatialite-tools, and sqlite), openSUSE (gnutls, ncurses, qemu, and xorg-x11-server), Slackware (mariadb and samba), SUSE (cryptctl), and Ubuntu (heimdal and samba).
Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2017/07/book_review_twi.html
There are two opposing models of how the Internet has changed protest movements. The first is that the Internet has made protesters mightier than ever. This comes from the successful revolutions in Tunisia (2010-11), Egypt (2011), and Ukraine (2013). The second is that it has made them more ineffectual. Derided as “slacktivism” or “clicktivism,” the ease of action without commitment can result in movements like Occupy petering out in the US without any obvious effects. Of course, the reality is more nuanced, and Zeynep Tufekci teases that out in her new book Twitter and Tear Gas.
Tufekci is a rare interdisciplinary figure. As a sociologist, programmer, and ethnographer, she studies how technology shapes society and drives social change. She has a dual appointment in both the School of Information Science and the Department of Sociology at University of North Carolina at Chapel Hill, and is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University. Her regular New York Times column on the social impacts of technology is a must-read.
Modern Internet-fueled protest movements are the subjects of Twitter and Tear Gas. As an observer, writer, and participant, Tufekci examines how modern protest movements have been changed by the Internet — and what that means for protests going forward. Her book combines her own ethnographic research and her usual deft analysis, with the research of others and some big data analysis from social media outlets. The result is a book that is both insightful and entertaining, and whose lessons are much broader than the book’s central topic.
“The Power and Fragility of Networked Protest” is the book’s subtitle. The power of the Internet as a tool for protest is obvious: it gives people newfound abilities to quickly organize and scale. But, according to Tufekci, it’s a mistake to judge modern protests using the same criteria we used to judge pre-Internet protests. The 1963 March on Washington might have culminated in hundreds of thousands of people listening to Martin Luther King Jr. deliver his “I Have a Dream” speech, but it was the culmination of a multi-year protest effort and the result of six months of careful planning made possible by that sustained effort. The 2011 protests in Cairo came together in mere days because they could be loosely coordinated on Facebook and Twitter.
That’s the power. Tufekci describes the fragility by analogy. Nepalese Sherpas assist Mt. Everest climbers by carrying supplies, laying out ropes and ladders, and so on. This means that people with limited training and experience can make the ascent, which is no less dangerous — to sometimes disastrous results. Says Tufekci: “The Internet similarly allows networked movements to grow dramatically and rapidly, but without prior building of formal or informal organizational and other collective capacities that could prepare them for the inevitable challenges they will face and give them the ability to respond to what comes next.” That makes them less able to respond to government counters, change their tactics — a phenomenon Tufekci calls “tactical freeze” — make movement-wide decisions, and survive over the long haul.
Tufekci isn’t arguing that modern protests are necessarily less effective, but that they’re different. Effective movements need to understand these differences, and leverage these new advantages while minimizing the disadvantages.
To that end, she develops a taxonomy for talking about social movements. Protests are an example of a “signal” that corresponds to one of several underlying “capacities.” There’s narrative capacity: the ability to change the conversation, as Black Lives Matter did with police violence and Occupy did with wealth inequality. There’s disruptive capacity: the ability to stop business as usual. An early Internet example is the 1999 WTO protests in Seattle. And finally, there’s electoral or institutional capacity: the ability to vote, lobby, fund raise, and so on. Because of various “affordances” of modern Internet technologies, particularly social media, the same signal — a protest of a given size — reflects different underlying capacities.
This taxonomy also informs government reactions to protest movements. Smart responses target attention as a resource. The Chinese government responded to 2015 protesters in Hong Kong by not engaging with them at all, denying them camera-phone videos that would go viral and attract the world’s attention. Instead, they pulled their police back and waited for the movement to die from lack of attention.
If this all sounds dry and academic, it’s not. Twitter and Tear Gasis infused with a richness of detail stemming from her personal participation in the 2013 Gezi Park protests in Turkey, as well as personal on-the-ground interviews with protesters throughout the Middle East — particularly Egypt and her native Turkey — Zapatistas in Mexico, WTO protesters in Seattle, Occupy participants worldwide, and others. Tufekci writes with a warmth and respect for the humans that are part of these powerful social movements, gently intertwining her own story with the stories of others, big data, and theory. She is adept at writing for a general audience, anddespite being published by the intimidating Yale University Press — her book is more mass-market than academic. What rigor is there is presented in a way that carries readers along rather than distracting.
The synthesist in me wishes Tufekci would take some additional steps, taking the trends she describes outside of the narrow world of political protest and applying them more broadly to social change. Her taxonomy is an important contribution to the more-general discussion of how the Internet affects society. Furthermore, her insights on the networked public sphere has applications for understanding technology-driven social change in general. These are hard conversations for society to have. We largely prefer to allow technology to blindly steer society or — in some ways worse — leave it to unfettered for-profit corporations. When you’re reading Twitter and Tear Gas, keep current and near-term future technological issues such as ubiquitous surveillance, algorithmic discrimination, and automation and employment in mind. You’ll come away with new insights.
Tufekci twice quotes historian Melvin Kranzberg from 1985: “Technology is neither good nor bad; nor is it neutral.” This foreshadows her central message. For better or worse, the technologies that power the networked public sphere have changed the nature of political protest as well as government reactions to and suppressions of such protest.
I have long characterized our technological future as a battle between the quick and the strong. The quick — dissidents, hackers, criminals, marginalized groups — are the first to make use of a new technology to magnify their power. The strong are slower, but have more raw power to magnify. So while protesters are the first to use Facebook to organize, the governments eventually figure out how to use Facebook to track protesters. It’s still an open question who will gain the upper hand in the long term, but Tufekci’s book helps us understand the dynamics at work.
This essay originally appeared on Vice Motherboard.
The book on Amazon.com.