Tag Archives: Oracle

Wielaard: dtrace for linux; Oracle does the right thing

Post Syndicated from corbet original https://lwn.net/Articles/747260/rss

Mark Wielaard writes
about
the recently discovered relicensing of the dtrace dynamic tracing
subsystem under the GPL. “Thank you Oracle for making everyone’s
life easier by waving your magic relicensing wand!

Now there is lots of hard work to do to actually properly integrate this. And I am sure there are a lot of technical hurdles when trying to get this upstreamed into the mainline kernel. But that is just hard work. Which we can now start collaborating on in earnest.”

Amazon Relational Database Service – Looking Back at 2017

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/amazon-relational-database-service-looking-back-at-2017/

The Amazon RDS team launched nearly 80 features in 2017. Some of them were covered in this blog, others on the AWS Database Blog, and the rest in What’s New or Forum posts. To wrap up my week, I thought it would be worthwhile to give you an organized recap. So here we go!

Certification & Security

Features

Engine Versions & Features

Regional Support

Instance Support

Price Reductions

And That’s a Wrap
I’m pretty sure that’s everything. As you can see, 2017 was quite the year! I can’t wait to see what the team delivers in 2018.

Jeff;

 

Security updates for Thursday

Post Syndicated from jake original https://lwn.net/Articles/746915/rss

Security updates have been issued by Debian (django-anymail, libtasn1-6, and postgresql-9.1), Fedora (w3m), Mageia (389-ds-base, gcc, libtasn1, and p7zip), openSUSE (flatpak, ImageMagick, libjpeg-turbo, libsndfile, mariadb, plasma5-workspace, pound, and spice-vdagent), Oracle (kernel), Red Hat (flash-plugin), SUSE (docker, docker-runc, containerd, golang-github-docker-libnetwork and kernel), and Ubuntu (libvirt, miniupnpc, and QEMU).

Security updates for Friday

Post Syndicated from jake original https://lwn.net/Articles/746326/rss

Security updates have been issued by CentOS (systemd and thunderbird), Debian (squid and squid3), Fedora (firefox), Mageia (java-1.8.0-openjdk and sox), openSUSE (ecryptfs-utils and libXfont), Oracle (systemd and thunderbird), Scientific Linux (thunderbird), and Ubuntu (dovecot and w3m).

Security updates for Tuesday

Post Syndicated from corbet original https://lwn.net/Articles/745775/rss

Security updates have been issued by Arch Linux (curl, lib32-curl, lib32-libcurl-compat, lib32-libcurl-gnutls, libcurl-compat, libcurl-gnutls, and rsync), Debian (curl), Fedora (clamav and java-1.8.0-openjdk), openSUSE (apache2), Oracle (kernel), and Ubuntu (linux-kvm and thunderbird).

2017 Weather Station round-up

Post Syndicated from Richard Hayler original https://www.raspberrypi.org/blog/2017-weather-station/

As we head into 2018 and start looking forward to longer days in the Northern hemisphere, I thought I’d take a look back at last year’s weather using data from Raspberry Pi Oracle Weather Stations. One of the great things about the kit is that as well as uploading all its readings to the shared online Oracle database, it stores them locally on the Pi in a MySQL or MariaDB database. This means you can use the power of SQL queries coupled with Python code to do automatic data analysis.

Soggy Surrey

My Weather Station has only been installed since May, so I didn’t have a full 52 weeks of my own data to investigate. Still, my station recorded more than 70000 measurements. Living in England, the first thing I wanted to know was: which was the wettest month? Unsurprisingly, both in terms of average daily rainfall and total rainfall, the start of the summer period — exactly when I went on a staycation — was the soggiest:

What about the global Weather Station community?

Even soggier Bavaria

Here things get slightly trickier. Although we have a shiny Oracle database full of all participating schools’ sensor readings, some of the data needs careful interpretation. Many kits are used as part of the school curriculum and do not always record genuine outdoor conditions. Nevertheless, it appears that Adalbert Stifter Gymnasium in Bavaria, Germany, had an even wetter 2017 than my home did:


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Where the wind blows

The records Robert-Dannemann Schule in Westerstede, Germany, is a good example of data which was most likely collected while testing and investigating the weather station sensors, rather than in genuine external conditions. Unless this school’s Weather Station was transported to a planet which suffers from extreme hurricanes, it wasn’t actually subjected to wind speeds above 1000km/h in November. Dismissing these and all similarly suspect records, I decided to award the ‘Windiest location of the year’ prize to CEIP Noalla-Telleiro, Spain.


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This school is right on the coast, and is subject to some strong and squally weather systems.

Weather Station at CEIP Noalla - Telleiro

Weather Station at CEIP Noalla-Telleiro

They’ve mounted their wind vane and anemometer nice and high, so I can see how they were able to record such high wind velocities.

A couple of Weather Stations have recently been commissioned in equally exposed places — it will be interesting to see whether they will record even higher speeds during 2018.

Highs and lows

After careful analysis and a few disqualifications (a couple of Weather Stations in contention for this category were housed indoors), the ‘Hottest location’ award went to High School of Chalastra in Thessaloniki, Greece. There were a couple of Weather Stations (the one at The Marwadi Education Foundation in India, for example) that reported higher average temperatures than Chalastra’s 24.54 ºC. However, they had uploaded far fewer readings and their data coverage of 2017 was only partial.


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At the other end of the thermometer, the location with the coldest average temperature is École de la Rose Sauvage in Calgary, Canada, with a very chilly 9.9 ºC.

Ecole de la Rose sauvage Weather Station

Weather Station at École de la Rose Sauvage

I suspect this school has a good chance of retaining the title: their lowest 2017 temperature of -24 ºC is likely to be beaten in 2018 due to extreme weather currently bringing a freezing start to the year in that part of the world.


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Analyse your own Weather Station data

If you have an Oracle Raspberry Pi Weather Station and would like to perform an annual review of your local data, you can use this Python script as a starting point. It will display a monthly summary of the temperature and rainfall for 2017, and you should be able to customise the code to focus on other sensor data or on a particular time of year. We’d love to see your results, so please share your findings with [email protected], and we’ll send you some limited-edition Weather Station stickers.

The post 2017 Weather Station round-up appeared first on Raspberry Pi.

Security updates for Friday

Post Syndicated from jake original https://lwn.net/Articles/745493/rss

Security updates have been issued by CentOS (389-ds-base, dhcp, kernel, and nautilus), Debian (curl, openssh, and wireshark), Fedora (clamav, firefox, java-9-openjdk, and poco), Gentoo (clamav), openSUSE (curl, libevent, mupdf, mysql-community-server, newsbeuter, php5, redis, and tre), Oracle (389-ds-base, dhcp, kernel, and nautilus), Slackware (mozilla), and Ubuntu (kernel and linux-hwe, linux-azure, linux-gcp, linux-oem).

Security updates for Monday

Post Syndicated from ris original https://lwn.net/Articles/745042/rss

Security updates have been issued by CentOS (bind), Debian (openocd), Mageia (unbound), Oracle (bind and microcode_ctl), Red Hat (bind, java-1.6.0-sun, libvirt, and qemu-kvm), Scientific Linux (bind), SUSE (kernel and perl-XML-LibXML), and Ubuntu (gimp, intel-microcode, mysql-5.5, mysql-5.7, and openssh).

Security updates for Monday

Post Syndicated from ris original https://lwn.net/Articles/744905/rss

Security updates have been issued by Debian (bind9, couchdb, lucene-solr, mysql-5.5, openocd, and php5), Mageia (gdk-pixbuf2.0, golang, and mariadb), openSUSE (curl, gd, ImageMagick, lxterminal, ncurses, newsbeuter, perl-XML-LibXML, and xmltooling), Oracle (kernel), and SUSE (xmltooling).

Security updates for Friday

Post Syndicated from ris original https://lwn.net/Articles/744791/rss

Security updates have been issued by Arch Linux (bind, irssi, nrpe, perl-xml-libxml, and transmission-cli), CentOS (java-1.8.0-openjdk), Debian (awstats, libgd2, mysql-5.5, rsync, smarty3, and transmission), Fedora (keycloak-httpd-client-install and rootsh), and Red Hat (java-1.7.0-oracle and java-1.8.0-oracle).

Security updates for Thursday

Post Syndicated from ris original https://lwn.net/Articles/744713/rss

Security updates have been issued by CentOS (linux-firmware and microcode_ctl), Fedora (icecat and transmission), Oracle (java-1.8.0-openjdk and microcode_ctl), Red Hat (java-1.8.0-openjdk), Scientific Linux (java-1.8.0-openjdk), Slackware (bind), SUSE (kernel), and Ubuntu (eglibc).

Scale Your Web Application — One Step at a Time

Post Syndicated from Saurabh Shrivastava original https://aws.amazon.com/blogs/architecture/scale-your-web-application-one-step-at-a-time/

I often encounter people experiencing frustration as they attempt to scale their e-commerce or WordPress site—particularly around the cost and complexity related to scaling. When I talk to customers about their scaling plans, they often mention phrases such as horizontal scaling and microservices, but usually people aren’t sure about how to dive in and effectively scale their sites.

Now let’s talk about different scaling options. For instance if your current workload is in a traditional data center, you can leverage the cloud for your on-premises solution. This way you can scale to achieve greater efficiency with less cost. It’s not necessary to set up a whole powerhouse to light a few bulbs. If your workload is already in the cloud, you can use one of the available out-of-the-box options.

Designing your API in microservices and adding horizontal scaling might seem like the best choice, unless your web application is already running in an on-premises environment and you’ll need to quickly scale it because of unexpected large spikes in web traffic.

So how to handle this situation? Take things one step at a time when scaling and you may find horizontal scaling isn’t the right choice, after all.

For example, assume you have a tech news website where you did an early-look review of an upcoming—and highly-anticipated—smartphone launch, which went viral. The review, a blog post on your website, includes both video and pictures. Comments are enabled for the post and readers can also rate it. For example, if your website is hosted on a traditional Linux with a LAMP stack, you may find yourself with immediate scaling problems.

Let’s get more details on the current scenario and dig out more:

  • Where are images and videos stored?
  • How many read/write requests are received per second? Per minute?
  • What is the level of security required?
  • Are these synchronous or asynchronous requests?

We’ll also want to consider the following if your website has a transactional load like e-commerce or banking:

How is the website handling sessions?

  • Do you have any compliance requests—like the Payment Card Industry Data Security Standard (PCI DSS compliance) —if your website is using its own payment gateway?
  • How are you recording customer behavior data and fulfilling your analytics needs?
  • What are your loading balancing considerations (scaling, caching, session maintenance, etc.)?

So, if we take this one step at a time:

Step 1: Ease server load. We need to quickly handle spikes in traffic, generated by activity on the blog post, so let’s reduce server load by moving image and video to some third -party content delivery network (CDN). AWS provides Amazon CloudFront as a CDN solution, which is highly scalable with built-in security to verify origin access identity and handle any DDoS attacks. CloudFront can direct traffic to your on-premises or cloud-hosted server with its 113 Points of Presence (102 Edge Locations and 11 Regional Edge Caches) in 56 cities across 24 countries, which provides efficient caching.
Step 2: Reduce read load by adding more read replicas. MySQL provides a nice mirror replication for databases. Oracle has its own Oracle plug for replication and AWS RDS provide up to five read replicas, which can span across the region and even the Amazon database Amazon Aurora can have 15 read replicas with Amazon Aurora autoscaling support. If a workload is highly variable, you should consider Amazon Aurora Serverless database  to achieve high efficiency and reduced cost. While most mirror technologies do asynchronous replication, AWS RDS can provide synchronous multi-AZ replication, which is good for disaster recovery but not for scalability. Asynchronous replication to mirror instance means replication data can sometimes be stale if network bandwidth is low, so you need to plan and design your application accordingly.

I recommend that you always use a read replica for any reporting needs and try to move non-critical GET services to read replica and reduce the load on the master database. In this case, loading comments associated with a blog can be fetched from a read replica—as it can handle some delay—in case there is any issue with asynchronous reflection.

Step 3: Reduce write requests. This can be achieved by introducing queue to process the asynchronous message. Amazon Simple Queue Service (Amazon SQS) is a highly-scalable queue, which can handle any kind of work-message load. You can process data, like rating and review; or calculate Deal Quality Score (DQS) using batch processing via an SQS queue. If your workload is in AWS, I recommend using a job-observer pattern by setting up Auto Scaling to automatically increase or decrease the number of batch servers, using the number of SQS messages, with Amazon CloudWatch, as the trigger.  For on-premises workloads, you can use SQS SDK to create an Amazon SQS queue that holds messages until they’re processed by your stack. Or you can use Amazon SNS  to fan out your message processing in parallel for different purposes like adding a watermark in an image, generating a thumbnail, etc.

Step 4: Introduce a more robust caching engine. You can use Amazon Elastic Cache for Memcached or Redis to reduce write requests. Memcached and Redis have different use cases so if you can afford to lose and recover your cache from your database, use Memcached. If you are looking for more robust data persistence and complex data structure, use Redis. In AWS, these are managed services, which means AWS takes care of the workload for you and you can also deploy them in your on-premises instances or use a hybrid approach.

Step 5: Scale your server. If there are still issues, it’s time to scale your server.  For the greatest cost-effectiveness and unlimited scalability, I suggest always using horizontal scaling. However, use cases like database vertical scaling may be a better choice until you are good with sharding; or use Amazon Aurora Serverless for variable workloads. It will be wise to use Auto Scaling to manage your workload effectively for horizontal scaling. Also, to achieve that, you need to persist the session. Amazon DynamoDB can handle session persistence across instances.

If your server is on premises, consider creating a multisite architecture, which will help you achieve quick scalability as required and provide a good disaster recovery solution.  You can pick and choose individual services like Amazon Route 53, AWS CloudFormation, Amazon SQS, Amazon SNS, Amazon RDS, etc. depending on your needs.

Your multisite architecture will look like the following diagram:

In this architecture, you can run your regular workload on premises, and use your AWS workload as required for scalability and disaster recovery. Using Route 53, you can direct a precise percentage of users to an AWS workload.

If you decide to move all of your workloads to AWS, the recommended multi-AZ architecture would look like the following:

In this architecture, you are using a multi-AZ distributed workload for high availability. You can have a multi-region setup and use Route53 to distribute your workload between AWS Regions. CloudFront helps you to scale and distribute static content via an S3 bucket and DynamoDB, maintaining your application state so that Auto Scaling can apply horizontal scaling without loss of session data. At the database layer, RDS with multi-AZ standby provides high availability and read replica helps achieve scalability.

This is a high-level strategy to help you think through the scalability of your workload by using AWS even if your workload in on premises and not in the cloud…yet.

I highly recommend creating a hybrid, multisite model by placing your on-premises environment replica in the public cloud like AWS Cloud, and using Amazon Route53 DNS Service and Elastic Load Balancing to route traffic between on-premises and cloud environments. AWS now supports load balancing between AWS and on-premises environments to help you scale your cloud environment quickly, whenever required, and reduce it further by applying Amazon auto-scaling and placing a threshold on your on-premises traffic using Route 53.

Security updates for Monday

Post Syndicated from ris original https://lwn.net/Articles/744398/rss

Security updates have been issued by Arch Linux (qtpass), Debian (libkohana2-php, libxml2, transmission, and xmltooling), Fedora (kernel and qpid-cpp), Gentoo (PolarSSL and xen), Mageia (flash-player-plugin, irssi, kernel, kernel-linus, kernel-tmb, libvorbis, microcode, nvidia-current, php & libgd, poppler, webkit2, and wireshark), openSUSE (gifsicle, glibc, GraphicsMagick, gwenhywfar, ImageMagick, libetpan, mariadb, pngcrush, postgresql94, rsync, tiff, and wireshark), and Oracle (kernel).

Security updates for Friday

Post Syndicated from ris original https://lwn.net/Articles/744175/rss

Security updates have been issued by Arch Linux (intel-ucode), Debian (gifsicle), Fedora (awstats and kernel), Gentoo (icoutils, pysaml2, and tigervnc), Mageia (dokuwiki and poppler), Oracle (kernel), SUSE (glibc, kernel, microcode_ctl, tiff, and ucode-intel), and Ubuntu (intel-microcode).

Security updates for Tuesday

Post Syndicated from ris original https://lwn.net/Articles/743700/rss

Security updates have been issued by Arch Linux (graphicsmagick and linux-lts), CentOS (thunderbird), Debian (kernel, opencv, php5, and php7.0), Fedora (electrum), Gentoo (libXfont), openSUSE (gimp, java-1_7_0-openjdk, and libvorbis), Oracle (thunderbird), Slackware (irssi), SUSE (kernel, kernel-firmware, and kvm), and Ubuntu (awstats, nvidia-graphics-drivers-384, python-pysaml2, and tomcat7, tomcat8).

Security updates for Friday

Post Syndicated from jake original https://lwn.net/Articles/743242/rss

Security updates have been issued by Arch Linux (kernel), CentOS (kernel, libvirt, microcode_ctl, and qemu-kvm), Debian (kernel and xen), Fedora (kernel), Mageia (backintime, erlang, and wildmidi), openSUSE (kernel and ucode-intel), Oracle (kernel, libvirt, microcode_ctl, and qemu-kvm), Red Hat (kernel, kernel-rt, libvirt, microcode_ctl, qemu-kvm, and qemu-kvm-rhev), Scientific Linux (libvirt and qemu-kvm), SUSE (kvm and qemu), and Ubuntu (ruby1.9.1, ruby2.0, ruby2.3).

Security updates for Thursday

Post Syndicated from jake original https://lwn.net/Articles/742959/rss

As might be guessed, a fair number of these updates are for the kernel and microcode changes to mitigate Meltdown and Spectre. More undoubtedly coming over the next weeks.

Security updates have been issued by CentOS (kernel, linux-firmware, and microcode_ctl), Debian (imagemagick), Fedora (kernel, libvirt, and python33), Mageia (curl, gdm, gnome-shell, libexif, libxml2, libxml2, perl-XML-LibXML, perl, swftools, and systemd), openSUSE (kernel-firmware), Oracle (kernel), Red Hat (kernel, kernel-rt, linux-firmware, and microcode_ctl), Scientific Linux (kernel, linux-firmware, and microcode_ctl), SUSE (ImageMagick, java-1_7_0-openjdk, kernel, kernel-firmware, microcode_ctl, qemu, and ucode-intel), and Ubuntu (apport, dnsmasq, and webkit2gtk).

Security updates for Monday

Post Syndicated from ris original https://lwn.net/Articles/741158/rss

Security updates have been issued by CentOS (postgresql), Debian (firefox-esr, kernel, libxcursor, optipng, thunderbird, wireshark, and xrdp), Fedora (borgbackup, ca-certificates, collectd, couchdb, curl, docker, erlang-jiffy, fedora-arm-installer, firefox, git, linux-firmware, mupdf, openssh, thunderbird, transfig, wildmidi, wireshark, xen, and xrdp), Mageia (firefox and optipng), openSUSE (erlang, libXfont, and OBS toolchain), Oracle (kernel), Slackware (openssl), and SUSE (kernel and OBS toolchain).