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Raspberry Jam Big Birthday Weekend 2018 roundup

Post Syndicated from Ben Nuttall original https://www.raspberrypi.org/blog/big-birthday-weekend-2018-roundup/

A couple of weekends ago, we celebrated our sixth birthday by coordinating more than 100 simultaneous Raspberry Jam events around the world. The Big Birthday Weekend was a huge success: our fantastic community organised Jams in 40 countries, covering six continents!

We sent the Jams special birthday kits to help them celebrate in style, and a video message featuring a thank you from Philip and Eben:

Raspberry Jam Big Birthday Weekend 2018

To celebrate the Raspberry Pi’s sixth birthday, we coordinated Raspberry Jams all over the world to take place over the Raspberry Jam Big Birthday Weekend, 3-4 March 2018. A massive thank you to everyone who ran an event and attended.

The Raspberry Jam photo booth

I put together code for a Pi-powered photo booth which overlaid the Big Birthday Weekend logo onto photos and (optionally) tweeted them. We included an arcade button in the Jam kits so they could build one — and it seemed to be quite popular. Some Jams put great effort into housing their photo booth:



Here are some of my favourite photo booth tweets:

RGVSA on Twitter

PiParty photo booth @RGVSA & @ @Nerdvana_io #Rjam

Denis Stretton on Twitter

The @SouthendRPIJams #PiParty photo booth

rpijamtokyo on Twitter

PiParty photo booth

Preston Raspberry Jam on Twitter

Preston Raspberry Jam Photobooth #RJam #PiParty

If you want to try out the photo booth software yourself, find the code on GitHub.

The great Raspberry Jam bake-off

Traditionally, in the UK, people have a cake on their birthday. And we had a few! We saw (and tasted) a great selection of Pi-themed cakes and other baked goods throughout the weekend:






Raspberry Jams everywhere

We always say that every Jam is different, but there’s a common and recognisable theme amongst them. It was great to see so many different venues around the world filling up with like-minded Pi enthusiasts, Raspberry Jam–branded banners, and Raspberry Pi balloons!

Europe

Sergio Martinez on Twitter

Thank you so much to all the attendees of the Ikana Jam in Krakow past Saturday! We shared fun experiences, some of them… also painful 😉 A big thank you to @Raspberry_Pi for these global celebrations! And a big thank you to @hubraum for their hospitality! #PiParty #rjam

NI Raspberry Jam on Twitter

We also had a super successful set of wearables workshops using @adafruit Circuit Playground Express boards and conductive thread at today’s @Raspberry_Pi Jam! Very popular! #PiParty

Suzystar on Twitter

My SenseHAT workshop, going well! @SouthendRPiJams #PiParty

Worksop College Raspberry Jam on Twitter

Learning how to scare the zombies in case of an apocalypse- it worked on our young learners #PiParty @worksopcollege @Raspberry_Pi https://t.co/pntEm57TJl

Africa

Rita on Twitter

Being one of the two places in Kenya where the #PiParty took place, it was an amazing time spending the day with this team and getting to learn and have fun. @TaitaTavetaUni and @Raspberry_Pi thank you for your support. @TTUTechlady @mictecttu ch

GABRIEL ONIFADE on Twitter

@TheMagP1

GABRIEL ONIFADE on Twitter

@GABONIAVERACITY #PiParty Lagos Raspberry Jam 2018 Special International Celebration – 6th Raspberry-Pi Big Birthday! Lagos Nigeria @Raspberry_Pi @ben_nuttall #RJam #RaspberryJam #raspberrypi #physicalcomputing #robotics #edtech #coding #programming #edTechAfrica #veracityhouse https://t.co/V7yLxaYGNx

North America

Heidi Baynes on Twitter

The Riverside Raspberry Jam @Vocademy is underway! #piparty

Brad Derstine on Twitter

The Philly & Pi #PiParty event with @Bresslergroup and @TechGirlzorg was awesome! The Scratch and Pi workshop was amazing! It was overall a great day of fun and tech!!! Thank you everyone who came out!

Houston Raspi on Twitter

Thanks everyone who came out to the @Raspberry_Pi Big Birthday Jam! Special thanks to @PBFerrell @estefanniegg @pcsforme @pandafulmanda @colnels @bquentin3 couldn’t’ve put on this amazing community event without you guys!

Merge Robotics 2706 on Twitter

We are back at @SciTechMuseum for the second day of @OttawaPiJam! Our robot Mergius loves playing catch with the kids! #pijam #piparty #omgrobots

South America

Javier Garzón on Twitter

Así terminamos el #Raspberry Jam Big Birthday Weekend #Bogota 2018 #PiParty de #RaspberryJamBogota 2018 @Raspberry_Pi Nos vemos el 7 de marzo en #ArduinoDayBogota 2018 y #RaspberryJamBogota 2018

Asia

Fablab UP Cebu on Twitter

Happy 6th birthday, @Raspberry_Pi! Greetings all the way from CEBU,PH! #PiParty #IoTCebu Thanks @CebuXGeeks X Ramos for these awesome pics. #Fablab #UPCebu

福野泰介 on Twitter

ラズパイ、6才のお誕生日会スタート in Tokyo PCNブースで、いろいろ展示とhttps://t.co/L6E7KgyNHFとIchigoJamつないだ、こどもIoTハッカソンmini体験やってます at 東京蒲田駅近 https://t.co/yHEuqXHvqe #piparty #pipartytokyo #rjam #opendataday

Ren Camp on Twitter

Happy birthday @Raspberry_Pi! #piparty #iotcebu @coolnumber9 https://t.co/2ESVjfRJ2d

Oceania

Glenunga Raspberry Pi Club on Twitter

PiParty photo booth

Personally, I managed to get to three Jams over the weekend: two run by the same people who put on the first two Jams to ever take place, and also one brand-new one! The Preston Raspberry Jam team, who usually run their event on a Monday evening, wanted to do something extra special for the birthday, so they came up with the idea of putting on a Raspberry Jam Sandwich — on the Friday and Monday around the weekend! This meant I was able to visit them on Friday, then attend the Manchester Raspberry Jam on Saturday, and finally drop by the new Jam at Worksop College on my way home on Sunday.

Ben Nuttall on Twitter

I’m at my first Raspberry Jam #PiParty event of the big birthday weekend! @PrestonRJam has been running for nearly 6 years and is a great place to start the celebrations!

Ben Nuttall on Twitter

Back at @McrRaspJam at @DigInnMMU for #PiParty

Ben Nuttall on Twitter

Great to see mine & @Frans_facts Balloon Pi-Tay popper project in action at @worksopjam #rjam #PiParty https://t.co/GswFm0UuPg

Various members of the Foundation team attended Jams around the UK and US, and James from the Code Club International team visited AmsterJam.

hackerfemo on Twitter

Thanks to everyone who came to our Jam and everyone who helped out. @phoenixtogether thanks for amazing cake & hosting. Ademir you’re so cool. It was awesome to meet Craig Morley from @Raspberry_Pi too. #PiParty

Stuart Fox on Twitter

Great #PiParty today at the @cotswoldjam with bloody delicious cake and lots of raspberry goodness. Great to see @ClareSutcliffe @martinohanlon playing on my new pi powered arcade build:-)

Clare Sutcliffe on Twitter

Happy 6th Birthday @Raspberry_Pi from everyone at the #PiParty at #cotswoldjam in Cheltenham!

Code Club on Twitter

It’s @Raspberry_Pi 6th birthday and we’re celebrating by taking part in @amsterjam__! Happy Birthday Raspberry Pi, we’re so happy to be a part of the family! #PiParty

For more Jammy birthday goodness, check out the PiParty hashtag on Twitter!

The Jam makers!

A lot of preparation went into each Jam, and we really appreciate all the hard work the Jam makers put in to making these events happen, on the Big Birthday Weekend and all year round. Thanks also to all the teams that sent us a group photo:

Lots of the Jams that took place were brand-new events, so we hope to see them continue throughout 2018 and beyond, growing the Raspberry Pi community around the world and giving more people, particularly youths, the opportunity to learn digital making skills.

Philip Colligan on Twitter

So many wonderful people in the @Raspberry_Pi community. Thanks to everyone at #PottonPiAndPints for a great afternoon and for everything you do to help young people learn digital making. #PiParty

Special thanks to ModMyPi for shipping the special Raspberry Jam kits all over the world!

Don’t forget to check out our Jam page to find an event near you! This is also where you can find free resources to help you get a new Jam started, and download free starter projects made especially for Jam activities. These projects are available in English, Français, Français Canadien, Nederlands, Deutsch, Italiano, and 日本語. If you’d like to help us translate more content into these and other languages, please get in touch!

PS Some of the UK Jams were postponed due to heavy snowfall, so you may find there’s a belated sixth-birthday Jam coming up where you live!

S Organ on Twitter

@TheMagP1 Ours was rescheduled until later in the Spring due to the snow but here is Babbage enjoying the snow!

The post Raspberry Jam Big Birthday Weekend 2018 roundup appeared first on Raspberry Pi.

The Challenges of Opening a Data Center — Part 2

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/factors-for-choosing-data-center/

Rows of storage pods in a data center

This is part two of a series on the factors that an organization needs to consider when opening a data center and the challenges that must be met in the process.

In Part 1 of this series, we looked at the different types of data centers, the importance of location in planning a data center, data center certification, and the single most expensive factor in running a data center, power.

In Part 2, we continue to look at factors that need to considered both by those interested in a dedicated data center and those seeking to colocate in an existing center.

Power (continued from Part 1)

In part 1, we began our discussion of the power requirements of data centers.

As we discussed, redundancy and failover is a chief requirement for data center power. A redundantly designed power supply system is also a necessity for maintenance, as it enables repairs to be performed on one network, for example, without having to turn off servers, databases, or electrical equipment.

Power Path

The common critical components of a data center’s power flow are:

  • Utility Supply
  • Generators
  • Transfer Switches
  • Distribution Panels
  • Uninterruptible Power Supplies (UPS)
  • PDUs

Utility Supply is the power that comes from one or more utility grids. While most of us consider the grid to be our primary power supply (hats off to those of you who manage to live off the grid), politics, economics, and distribution make utility supply power susceptible to outages, which is why data centers must have autonomous power available to maintain availability.

Generators are used to supply power when the utility supply is unavailable. They convert mechanical energy, usually from motors, to electrical energy.

Transfer Switches are used to transfer electric load from one source or electrical device to another, such as from one utility line to another, from a generator to a utility, or between generators. The transfer could be manually activated or automatic to ensure continuous electrical power.

Distribution Panels get the power where it needs to go, taking a power feed and dividing it into separate circuits to supply multiple loads.

A UPS, as we touched on earlier, ensures that continuous power is available even when the main power source isn’t. It often consists of batteries that can come online almost instantaneously when the current power ceases. The power from a UPS does not have to last a long time as it is considered an emergency measure until the main power source can be restored. Another function of the UPS is to filter and stabilize the power from the main power supply.

Data Center UPS

Data center UPSs

PDU stands for the Power Distribution Unit and is the device that distributes power to the individual pieces of equipment.

Network

After power, the networking connections to the data center are of prime importance. Can the data center obtain and maintain high-speed networking connections to the building? With networking, as with all aspects of a data center, availability is a primary consideration. Data center designers think of all possible ways service can be interrupted or lost, even briefly. Details such as the vulnerabilities in the route the network connections make from the core network (the backhaul) to the center, and where network connections enter and exit a building, must be taken into consideration in network and data center design.

Routers and switches are used to transport traffic between the servers in the data center and the core network. Just as with power, network redundancy is a prime factor in maintaining availability of data center services. Two or more upstream service providers are required to ensure that availability.

How fast a customer can transfer data to a data center is affected by: 1) the speed of the connections the data center has with the outside world, 2) the quality of the connections between the customer and the data center, and 3) the distance of the route from customer to the data center. The longer the length of the route and the greater the number of packets that must be transferred, the more significant a factor will be played by latency in the data transfer. Latency is the delay before a transfer of data begins following an instruction for its transfer. Generally latency, not speed, will be the most significant factor in transferring data to and from a data center. Packets transferred using the TCP/IP protocol suite, which is the conceptual model and set of communications protocols used on the internet and similar computer networks, must be acknowledged when received (ACK’d) and requires a communications roundtrip for each packet. If the data is in larger packets, the number of ACKs required is reduced, so latency will be a smaller factor in the overall network communications speed.

Latency generally will be less significant for data storage transfers than for cloud computing. Optimizations such as multi-threading, which is used in Backblaze’s Cloud Backup service, will generally improve overall transfer throughput if sufficient bandwidth is available.

Those interested in testing the overall speed and latency of their connection to Backblaze’s data centers can use the Check Your Bandwidth tool on our website.
Data center telecommunications equipment

Data center telecommunications equipment

Data center under floor cable runs

Data center under floor cable runs

Cooling

Computer, networking, and power generation equipment generates heat, and there are a number of solutions employed to rid a data center of that heat. The location and climate of the data center is of great importance to the data center designer because the climatic conditions dictate to a large degree what cooling technologies should be deployed that in turn affect the power used and the cost of using that power. The power required and cost needed to manage a data center in a warm, humid climate will vary greatly from managing one in a cool, dry climate. Innovation is strong in this area and many new approaches to efficient and cost-effective cooling are used in the latest data centers.

Switch's uninterruptible, multi-system, HVAC Data Center Cooling Units

Switch’s uninterruptible, multi-system, HVAC Data Center Cooling Units

There are three primary ways data center cooling can be achieved:

Room Cooling cools the entire operating area of the data center. This method can be suitable for small data centers, but becomes more difficult and inefficient as IT equipment density and center size increase.

Row Cooling concentrates on cooling a data center on a row by row basis. In its simplest form, hot aisle/cold aisle data center design involves lining up server racks in alternating rows with cold air intakes facing one way and hot air exhausts facing the other. The rows composed of rack fronts are called cold aisles. Typically, cold aisles face air conditioner output ducts. The rows the heated exhausts pour into are called hot aisles. Typically, hot aisles face air conditioner return ducts.

Rack Cooling tackles cooling on a rack by rack basis. Air-conditioning units are dedicated to specific racks. This approach allows for maximum densities to be deployed per rack. This works best in data centers with fully loaded racks, otherwise there would be too much cooling capacity, and the air-conditioning losses alone could exceed the total IT load.

Security

Data Centers are high-security facilities as they house business, government, and other data that contains personal, financial, and other secure information about businesses and individuals.

This list contains the physical-security considerations when opening or co-locating in a data center:

Layered Security Zones. Systems and processes are deployed to allow only authorized personnel in certain areas of the data center. Examples include keycard access, alarm systems, mantraps, secure doors, and staffed checkpoints.

Physical Barriers. Physical barriers, fencing and reinforced walls are used to protect facilities. In a colocation facility, one customers’ racks and servers are often inaccessible to other customers colocating in the same data center.

Backblaze racks secured in the data center

Backblaze racks secured in the data center

Monitoring Systems. Advanced surveillance technology monitors and records activity on approaching driveways, building entrances, exits, loading areas, and equipment areas. These systems also can be used to monitor and detect fire and water emergencies, providing early detection and notification before significant damage results.

Top-tier providers evaluate their data center security and facilities on an ongoing basis. Technology becomes outdated quickly, so providers must stay-on-top of new approaches and technologies in order to protect valuable IT assets.

To pass into high security areas of a data center requires passing through a security checkpoint where credentials are verified.

Data Center security

The gauntlet of cameras and steel bars one must pass before entering this data center

Facilities and Services

Data center colocation providers often differentiate themselves by offering value-added services. In addition to the required space, power, cooling, connectivity and security capabilities, the best solutions provide several on-site amenities. These accommodations include offices and workstations, conference rooms, and access to phones, copy machines, and office equipment.

Additional features may consist of kitchen facilities, break rooms and relaxation lounges, storage facilities for client equipment, and secure loading docks and freight elevators.

Moving into A Data Center

Moving into a data center is a major job for any organization. We wrote a post last year, Desert To Data in 7 Days — Our New Phoenix Data Center, about what it was like to move into our new data center in Phoenix, Arizona.

Desert To Data in 7 Days — Our New Phoenix Data Center

Visiting a Data Center

Our Director of Product Marketing Andy Klein wrote a popular post last year on what it’s like to visit a data center called A Day in the Life of a Data Center.

A Day in the Life of a Data Center

Would you Like to Know More about The Challenges of Opening and Running a Data Center?

That’s it for part 2 of this series. If readers are interested, we could write a post about some of the new technologies and trends affecting data center design and use. Please let us know in the comments.

Here's a tip!Here’s a tip on finding all the posts tagged with data center on our blog. Just follow https://www.backblaze.com/blog/tag/data-center/.

Don’t miss future posts on data centers and other topics, including hard drive stats, cloud storage, and tips and tricks for backing up to the cloud. Use the Join button above to receive notification of future posts on our blog.

The post The Challenges of Opening a Data Center — Part 2 appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Mission Space Lab flight status announced!

Post Syndicated from Erin Brindley original https://www.raspberrypi.org/blog/mission-space-lab-flight-status-announced/

In September of last year, we launched our 2017/2018 Astro Pi challenge with our partners at the European Space Agency (ESA). Students from ESA membership and associate countries had the chance to design science experiments and write code to be run on one of our two Raspberry Pis on the International Space Station (ISS).

Astro Pi Mission Space Lab logo

Submissions for the Mission Space Lab challenge have just closed, and the results are in! Students had the opportunity to design an experiment for one of the following two themes:

  • Life in space
    Making use of Astro Pi Vis (Ed) in the European Columbus module to learn about the conditions inside the ISS.
  • Life on Earth
    Making use of Astro Pi IR (Izzy), which will be aimed towards the Earth through a window to learn about Earth from space.

ESA astronaut Alexander Gerst, speaking from the replica of the Columbus module at the European Astronaut Center in Cologne, has a message for all Mission Space Lab participants:

ESA astronaut Alexander Gerst congratulates Astro Pi 2017-18 winners

Subscribe to our YouTube channel: http://rpf.io/ytsub Help us reach a wider audience by translating our video content: http://rpf.io/yttranslate Buy a Raspberry Pi from one of our Approved Resellers: http://rpf.io/ytproducts Find out more about the Raspberry Pi Foundation: Raspberry Pi http://rpf.io/ytrpi Code Club UK http://rpf.io/ytccuk Code Club International http://rpf.io/ytcci CoderDojo http://rpf.io/ytcd Check out our free online training courses: http://rpf.io/ytfl Find your local Raspberry Jam event: http://rpf.io/ytjam Work through our free online projects: http://rpf.io/ytprojects Do you have a question about your Raspberry Pi?

Flight status

We had a total of 212 Mission Space Lab entries from 22 countries. Of these, a 114 fantastic projects have been given flight status, and the teams’ project code will run in space!

But they’re not winners yet. In April, the code will be sent to the ISS, and then the teams will receive back their experimental data. Next, to get deeper insight into the process of scientific endeavour, they will need produce a final report analysing their findings. Winners will be chosen based on the merit of their final report, and the winning teams will get exclusive prizes. Check the list below to see if your team got flight status.

Belgium

Flight status achieved:

  • Team De Vesten, Campus De Vesten, Antwerpen
  • Ursa Major, CoderDojo Belgium, West-Vlaanderen
  • Special operations STEM, Sint-Claracollege, Antwerpen

Canada

Flight status achieved:

  • Let It Grow, Branksome Hall, Toronto
  • The Dark Side of Light, Branksome Hall, Toronto
  • Genie On The ISS, Branksome Hall, Toronto
  • Byte by PIthons, Youth Tech Education Society & Kid Code Jeunesse, Edmonton
  • The Broadviewnauts, Broadview, Ottawa

Czech Republic

Flight status achieved:

  • BLEK, Střední Odborná Škola Blatná, Strakonice

Denmark

Flight status achieved:

  • 2y Infotek, Nærum Gymnasium, Nærum
  • Equation Quotation, Allerød Gymnasium, Lillerød
  • Team Weather Watchers, Allerød Gymnasium, Allerød
  • Space Gardners, Nærum Gymnasium, Nærum

Finland

Flight status achieved:

  • Team Aurora, Hyvinkään yhteiskoulun lukio, Hyvinkää

France

Flight status achieved:

  • INC2, Lycée Raoul Follereau, Bourgogne
  • Space Project SP4, Lycée Saint-Paul IV, Reunion Island
  • Dresseurs2Python, clg Albert CAMUS, essonne
  • Lazos, Lycée Aux Lazaristes, Rhone
  • The space nerds, Lycée Saint André Colmar, Alsace
  • Les Spationautes Valériquais, lycée de la Côte d’Albâtre, Normandie
  • AstroMega, Institut de Genech, north
  • Al’Crew, Lycée Algoud-Laffemas, Auvergne-Rhône-Alpes
  • AstroPython, clg Albert CAMUS, essonne
  • Aruden Corp, Lycée Pablo Neruda, Normandie
  • HeroSpace, clg Albert CAMUS, essonne
  • GalaXess [R]evolution, Lycée Saint Cricq, Nouvelle-Aquitaine
  • AstroBerry, clg Albert CAMUS, essonne
  • Ambitious Girls, Lycée Adam de Craponne, PACA

Germany

Flight status achieved:

  • Uschis, St. Ursula Gymnasium Freiburg im Breisgau, Breisgau
  • Dosi-Pi, Max-Born-Gymnasium Germering, Bavaria

Greece

Flight status achieved:

  • Deep Space Pi, 1o Epal Grevenon, Grevena
  • Flox Team, 1st Lyceum of Kifissia, Attiki
  • Kalamaria Space Team, Second Lyceum of Kalamaria, Central Macedonia
  • The Earth Watchers, STEM Robotics Academy, Thessaly
  • Celestial_Distance, Gymnasium of Kanithos, Sterea Ellada – Evia
  • Pi Stars, Primary School of Rododaphne, Achaias
  • Flarions, 5th Primary School of Salamina, Attica

Ireland

Flight status achieved:

  • Plant Parade, Templeogue College, Leinster
  • For Peats Sake, Templeogue College, Leinster
  • CoderDojo Clonakilty, Co. Cork

Italy

Flight status achieved:

  • Trentini DOP, CoderDojo Trento, TN
  • Tarantino Space Lab, Liceo G. Tarantino, BA
  • Murgia Sky Lab, Liceo G. Tarantino, BA
  • Enrico Fermi, Liceo XXV Aprile, Veneto
  • Team Lampone, CoderDojoTrento, TN
  • GCC, Gali Code Club, Trentino Alto Adige/Südtirol
  • Another Earth, IISS “Laporta/Falcone-Borsellino”
  • Anti Pollution Team, IIS “L. Einaudi”, Sicily
  • e-HAND, Liceo Statale Scientifico e Classico ‘Ettore Majorana’, Lombardia
  • scossa team, ITTS Volterra, Venezia
  • Space Comet Sisters, Scuola don Bosco, Torino

Luxembourg

Flight status achieved:

  • Spaceballs, Atert Lycée Rédange, Diekirch
  • Aline in space, Lycée Aline Mayrisch Luxembourg (LAML)

Poland

Flight status achieved:

  • AstroLeszczynPi, I Liceum Ogolnoksztalcace im. Krola Stanislawa Leszczynskiego w Jasle, podkarpackie
  • Astrokompasy, High School nr XVII in Wrocław named after Agnieszka Osiecka, Lower Silesian
  • Cosmic Investigators, Publiczna Szkoła Podstawowa im. Św. Jadwigi Królowej w Rzezawie, Małopolska
  • ApplePi, III Liceum Ogólnokształcące im. prof. T. Kotarbińskiego w Zielonej Górze, Lubusz Voivodeship
  • ELE Society 2, Zespol Szkol Elektronicznych i Samochodowych, Lubuskie
  • ELE Society 1, Zespol Szkol Elektronicznych i Samochodowych, Lubuskie
  • SpaceOn, Szkola Podstawowa nr 12 w Jasle – Gimnazjum Nr 2, Podkarpackie
  • Dewnald Ducks, III Liceum Ogólnokształcące w Zielonej Górze, lubuskie
  • Nova Team, III Liceum Ogolnoksztalcace im. prof. T. Kotarbinskiego, lubuskie district
  • The Moons, Szkola Podstawowa nr 12 w Jasle – Gimnazjum Nr 2, Podkarpackie
  • Live, Szkoła Podstawowa nr 1 im. Tadeusza Kościuszki w Zawierciu, śląskie
  • Storm Hunters, I Liceum Ogolnoksztalcace im. Krola Stanislawa Leszczynskiego w Jasle, podkarpackie
  • DeepSky, Szkoła Podstawowa nr 1 im. Tadeusza Kościuszki w Zawierciu, śląskie
  • Small Explorers, ZPO Konina, Malopolska
  • AstroZSCL, Zespół Szkół w Czerwionce-Leszczynach, śląskie
  • Orchestra, Szkola Podstawowa nr 12 w Jasle, Podkarpackie
  • ApplePi, I Liceum Ogolnoksztalcace im. Krola Stanislawa Leszczynskiego w Jasle, podkarpackie
  • Green Crew, Szkoła Podstawowa nr 2 w Czeladzi, Silesia

Portugal

Flight status achieved:

  • Magnetics, Escola Secundária João de Deus, Faro
  • ECA_QUEIROS_PI, Secondary School Eça de Queirós, Lisboa
  • ESDMM Pi, Escola Secundária D. Manuel Martins, Setúbal
  • AstroPhysicists, EB 2,3 D. Afonso Henriques, Braga

Romania

Flight status achieved:

  • Caelus, “Tudor Vianu” National High School of Computer Science, District One
  • CodeWarriors, “Tudor Vianu” National High School of Computer Science, District One
  • Dark Phoenix, “Tudor Vianu” National High School of Computer Science, District One
  • ShootingStars, “Tudor Vianu” National High School of Computer Science, District One
  • Astro Pi Carmen Sylva 2, Liceul Teoretic “Carmen Sylva”, Constanta
  • Astro Meridian, Astro Club Meridian 0, Bihor

Slovenia

Flight status achieved:

  • astrOSRence, OS Rence
  • Jakopičevca, Osnovna šola Riharda Jakopiča, Ljubljana

Spain

Flight status achieved:

  • Exea in Orbit, IES Cinco Villas, Zaragoza
  • Valdespartans, IES Valdespartera, Zaragoza
  • Valdespartans2, IES Valdespartera, Zaragoza
  • Astropithecus, Institut de Bruguers, Barcelona
  • SkyPi-line, Colegio Corazón de María, Asturias
  • ClimSOLatic, Colegio Corazón de María, Asturias
  • Científicosdelsaz, IES Profesor Pablo del Saz, Málaga
  • Canarias 2, IES El Calero, Las Palmas
  • Dreamers, M. Peleteiro, A Coruña
  • Canarias 1, IES El Calero, Las Palmas

The Netherlands

Flight status achieved:

  • Team Kaki-FM, Rkbs De Reiger, Noord-Holland

United Kingdom

Flight status achieved:

  • Binco, Teignmouth Community School, Devon
  • 2200 (Saddleworth), Detached Flight Royal Air Force Air Cadets, Lanchashire
  • Whatevernext, Albyn School, Highlands
  • GraviTeam, Limehurst Academy, Leicestershire
  • LSA Digital Leaders, Lytham St Annes Technology and Performing Arts College, Lancashire
  • Mead Astronauts, Mead Community Primary School, Wiltshire
  • STEAMCademy, Castlewood Primary School, West Sussex
  • Lux Quest, CoderDojo Banbridge, Co. Down
  • Temparatus, Dyffryn Taf, Carmarthenshire
  • Discovery STEMers, Discovery STEM Education, South Yorkshire
  • Code Inverness, Code Club Inverness, Highland
  • JJB, Ashton Sixth Form College, Tameside
  • Astro Lab, East Kent College, Kent
  • The Life Savers, Scratch and Python, Middlesex
  • JAAPiT, Taylor Household, Nottingham
  • The Heat Guys, The Archer Academy, Greater London
  • Astro Wantenauts, Wantage C of E Primary School, Oxfordshire
  • Derby Radio Museum, Radio Communication Museum of Great Britain, Derbyshire
  • Bytesyze, King’s College School, Cambridgeshire

Other

Flight status achieved:

  • Intellectual Savage Stars, Lycée français de Luanda, Luanda

 

Congratulations to all successful teams! We are looking forward to reading your reports.

The post Mission Space Lab flight status announced! appeared first on Raspberry Pi.

timeShift(GrafanaBuzz, 1w) Issue 28

Post Syndicated from Blogs on Grafana Labs Blog original https://grafana.com/blog/2018/01/05/timeshiftgrafanabuzz-1w-issue-28/

Happy new year! Grafana Labs is getting back in the swing of things after taking some time off to celebrate 2017, and spending time with family and friends. We’re diligently working on the new Grafana v5.0 release (planning v5.0 beta release by end of January), which includes a ton of new features, a new layout engine, and a polished UI. We’d love to hear your feedback!


Latest Stable Release

Grafana 4.6.3 is now available. Latest bugfixes include:

  • Gzip: Fixes bug Gravatar images when gzip was enabled #5952
  • Alert list: Now shows alert state changes even after adding manual annotations on dashboard #99513
  • Alerting: Fixes bug where rules evaluated as firing when all conditions was false and using OR operator. #93183
  • Cloudwatch: CloudWatch no longer display metrics’ default alias #101514, thx @mtanda

Download Grafana 4.6.3 Now


From the Blogosphere

Why Observability Matters – Now and in the Future: Our own Carl Bergquist teamed up with Neil Gehani, Director of Product at Weaveworks to discuss best practices on how to get started with monitoring your application and infrastructure. This video focuses on modern containerized applications instrumented to use Prometheus to generate metrics and Grafana to visualize them.

How to Install and Secure Grafana on Ubuntu 16.04: In this tutorial, you’ll learn how to install and secure Grafana with a SSL certificate and a Nginx reverse proxy, then you’ll modify Grafana’s default settings for even tighter security.

Monitoring Informix with Grafana: Ben walks us through how to use Grafana to visualize data from IBM Informix and offers a practical demonstration using Docker containers. He also talks about his philosophy of sharing dashboards across teams, important metrics to collect, and how he would like to improve his monitoring stack.

Monitor your hosts with Glances + InfluxDB + Grafana: Glances is a cross-platform system monitoring tool written in Python. This article takes you step by step through the pieces of the stack, installation, confirguration and provides a sample dashboard to get you up and running.


GrafanaCon Tickets are Going Fast!

Lock in your seat for GrafanaCon EU while there are still tickets avaialable! Join us March 1-2, 2018 in Amsterdam for 2 days of talks centered around Grafana and the surrounding monitoring ecosystem including Graphite, Prometheus, InfluxData, Elasticsearch, Kubernetes, and more.

We have some exciting talks lined up from Google, CERN, Bloomberg, eBay, Red Hat, Tinder, Fastly, Automattic, Prometheus, InfluxData, Percona and more! You can see the full list of speakers below, but be sure to get your ticket now.

Get Your Ticket Now

GrafanaCon EU will feature talks from:

“Google Bigtable”
Misha Brukman
PROJECT MANAGER,
GOOGLE CLOUD
GOOGLE

“Monitoring at Bloomberg”
Stig Sorensen
HEAD OF TELEMETRY
BLOOMBERG

“Monitoring at Bloomberg”
Sean Hanson
SOFTWARE DEVELOPER
BLOOMBERG

“Monitoring Tinder’s Billions of Swipes with Grafana”
Utkarsh Bhatnagar
SR. SOFTWARE ENGINEER
TINDER

“Grafana at CERN”
Borja Garrido
PROJECT ASSOCIATE
CERN

“Monitoring the Huge Scale at Automattic”
Abhishek Gahlot
SOFTWARE ENGINEER
Automattic

“Real-time Engagement During the 2016 US Presidential Election”
Anna MacLachlan
CONTENT MARKETING MANAGER
Fastly

“Real-time Engagement During the 2016 US Presidential Election”
Gerlando Piro
FRONT END DEVELOPER
Fastly

“Grafana v5 and the Future”
Torkel Odegaard
CREATOR | PROJECT LEAD
GRAFANA

“Prometheus for Monitoring Metrics”
Brian Brazil
FOUNDER
ROBUST PERCEPTION

“What We Learned Integrating Grafana with Prometheus”
Peter Zaitsev
CO-FOUNDER | CEO
PERCONA

“The Biz of Grafana”
Raj Dutt
CO-FOUNDER | CEO
GRAFANA LABS

“What’s New In Graphite”
Dan Cech
DIR, PLATFORM SERVICES
GRAFANA LABS

“The Design of IFQL, the New Influx Functional Query Language”
Paul Dix
CO-FOUNTER | CTO
INFLUXDATA

“Writing Grafana Dashboards with Jsonnet”
Julien Pivotto
OPEN SOURCE CONSULTANT
INUITS

“Monitoring AI Platform at eBay”
Deepak Vasthimal
MTS-2 SOFTWARE ENGINEER
EBAY

“Running a Power Plant with Grafana”
Ryan McKinley
DEVELOPER
NATEL ENERGY

“Performance Metrics and User Experience: A “Tinder” Experience”
Susanne Greiner
DATA SCIENTIST
WÜRTH PHOENIX S.R.L.

“Analyzing Performance of OpenStack with Grafana Dashboards”
Alex Krzos
SENIOR SOFTWARE ENGINEER
RED HAT INC.

“Storage Monitoring at Shell Upstream”
Arie Jan Kraai
STORAGE ENGINEER
SHELL TECHNICAL LANDSCAPE SERVICE

“The RED Method: How To Instrument Your Services”
Tom Wilkie
FOUNDER
KAUSAL

“Grafana Usage in the Quality Assurance Process”
Andrejs Kalnacs
LEAD SOFTWARE DEVELOPER IN TEST
EVOLUTION GAMING

“Using Prometheus and Grafana for Monitoring my Power Usage”
Erwin de Keijzer
LINUX ENGINEER
SNOW BV

“Weather, Power & Market Forecasts with Grafana”
Max von Roden
DATA SCIENTIST
ENERGY WEATHER

“Weather, Power & Market Forecasts with Grafana”
Steffen Knott
HEAD OF IT
ENERGY WEATHER

“Inherited Technical Debt – A Tale of Overcoming Enterprise Inertia”
Jordan J. Hamel
HEAD OF MONITORING PLATFORMS
AMGEN

“Grafanalib: Dashboards as Code”
Jonathan Lange
VP OF ENGINEERING
WEAVEWORKS

“The Journey of Shifting the MQTT Broker HiveMQ to Kubernetes”
Arnold Bechtoldt
SENIOR SYSTEMS ENGINEER
INOVEX

“Graphs Tell Stories”
Blerim Sheqa
SENIOR DEVELOPER
NETWAYS

[email protected] or How to Store Millions of Metrics per Second”
Vladimir Smirnov
SYSTEM ADMINISTRATOR
Booking.com


Upcoming Events:

In between code pushes we like to speak at, sponsor and attend all kinds of conferences and meetups. We also like to make sure we mention other Grafana-related events happening all over the world. If you’re putting on just such an event, let us know and we’ll list it here.

FOSDEM | Brussels, Belgium – Feb 3-4, 2018: FOSDEM is a free developer conference where thousands of developers of free and open source software gather to share ideas and technology. There is no need to register; all are welcome.

Jfokus | Stockholm, Sweden – Feb 5-7, 2018:
Carl Bergquist – Quickie: Monitoring? Not OPS Problem

Why should we monitor our system? Why can’t we just rely on the operations team anymore? They use to be able to do that. What’s currently changing? Presentation content: – Why do we monitor our system – How did it use to work? – Whats changing – Why do we need to shift focus – Everyone should be on call. – Resilience is the goal (Best way of having someone care about quality is to make them responsible).

Register Now

Jfokus | Stockholm, Sweden – Feb 5-7, 2018:
Leonard Gram – Presentation: DevOps Deconstructed

What’s a Site Reliability Engineer and how’s that role different from the DevOps engineer my boss wants to hire? I really don’t want to be on call, should I? Is Docker the right place for my code or am I better of just going straight to Serverless? And why should I care about any of it? I’ll try to answer some of these questions while looking at what DevOps really is about and how commodisation of servers through “the cloud” ties into it all. This session will be an opinionated piece from a developer who’s been on-call for the past 6 years and would like to convince you to do the same, at least once.

Register Now

Tweet of the Week

We scour Twitter each week to find an interesting/beautiful dashboard and show it off! #monitoringLove

Awesome! Let us know if you have any questions – we’re happy to help out. We also have a bunch of screencasts to help you get going.


Grafana Labs is Hiring!

We are passionate about open source software and thrive on tackling complex challenges to build the future. We ship code from every corner of the globe and love working with the community. If this sounds exciting, you’re in luck – WE’RE HIRING!

Check out our Open Positions


How are we doing?

That’s a wrap! Let us know what you think about timeShift. Submit a comment on this article below, or post something at our community forum. See you next year!

Follow us on Twitter, like us on Facebook, and join the Grafana Labs community.

Hard Drive Stats for Q2 2017

Post Syndicated from Andy Klein original https://www.backblaze.com/blog/hard-drive-failure-stats-q2-2017/

Backblaze Drive Stats Q2 2017

In this update, we’ll review the Q2 2017 and lifetime hard drive failure rates for all our current drive models. We also look at how our drive migration strategy is changing the drives we use and we’ll check in on our enterprise class drives to see how they are doing. Along the way we’ll share our observations and insights and as always we welcome your comments and critiques.

Since our last report for Q1 2017, we have added 635 additional hard drives to bring us to the 83,151 drives we’ll focus on. In Q1 we added over 10,000 new drives to the mix, so adding just 635 in Q2 seems “odd.” In fact, we added 4,921 new drives and retired 4,286 old drives as we migrated from lower density drives to higher density drives. We cover more about migrations later on, but first let’s look at the Q2 quarterly stats.

Hard Drive Stats for Q2 2017

We’ll begin our review by looking at the statistics for the period of April 1, 2017 through June 30, 2017 (Q2 2017). This table includes 17 different 3 ½” drive models that were operational during the indicated period, ranging in size from 3 to 8 TB.

Quarterly Hard Drive Failure Rates for Q2 2017

When looking at the quarterly numbers, remember to look for those drives with at least 50,000 drive hours for the quarter. That works out to about 550 drives running the entire quarter. That’s a good sample size. If the sample size is below that, the failure rates can be skewed based on a small change in the number of drive failures.

As noted previously, we use the quarterly numbers to look for trends. So this time we’ve included a trend indicator in the table. The “Q2Q Trend” column is short for quarter-to-quarter trend, i.e. last quarter to this quarter. We can add, change, or delete trend columns depending on community interest. Let us know what you think in the comments.

Good Migrations

In Q2 we continued with our data migration program. For us, a drive migration means we intentionally remove a good drive from service and replace it with another drive. Drives that are removed via migrations are not counted as failed. Once they are removed they stop accumulating drive hours and other stats in our system.

There are three primary drivers for our migration program.

  1. Increase Storage Density – For example, in Q3 we replaced 3 TB drives with 8 TB drives, more than doubling the amount of storage in a given Storage Pod for the same footprint. The cost of electricity was nominally more with the 8 TB drives, but the increase in density more than offset the additional cost. For those interested you can read more about the cost of cloud storage here.
  2. Backblaze Vaults – Our Vault architecture has proven to be more cost effective over the past two years than using stand-alone Storage Pods. A major goal of the migration program is to have the entire Backblaze cloud deployed on the highly efficient and resilient Backblaze Vault architecture.
  3. Balancing the Load – With our Phoenix data center online and accepting data, we have migrated some systems to the Phoenix DC. Don’t worry, we didn’t put your data on a truck and drive it to Phoenix. We simply built new systems there and transferred the data from our Northern California DC. In the process, we are gaining valuable insights as we move towards being able to replicate data between the two data centers.
During Q2 we migrated nearly 30 Petabytes of data.

During Q2 we migrated the data on 155 systems, giving nearly 30 petabytes of data a new, more durable, place to call home. There are still 644 individual Storage Pods (Storage Pod Classics, as we call them) left to migrate to the Backblaze Vault architecture.

Just in case you don’t know, a Backblaze Vault is a logical collection of 20 beefy Storage Pods (not Classics). Using our own Reed-Solomon erasure coding library, data is spread out across the 20 Pods into 17 data shards and 3 parity shards. The data and parity shards of each arriving data blob can be stored on different Storage Pods in a given Backblaze Vault.

Lifetime Hard Drive Failure Rates for Current Drives

The table below shows the failure rates for the hard drive models we had in service as of June 30, 2017. This is over the period beginning in April 2013 and ending June 30, 2017. If you are interested in the hard drive failure rates for all the hard drives we’ve used over the years, please refer to our 2016 hard drive review.

Cumulative Hard Drive Failure Rates

Enterprise vs Consumer Drives

We added 3,595 enterprise class 8 TB drives in Q2 bringing our total to 6,054 drives. You may be tempted to compare the failure rates of the 8 TB enterprise drive (model: ST8000NM005) to the consumer 8 TB drive (model: ST8000DM002), and conclude the enterprise drives fail at a higher rate. Let’s not jump to that conclusion yet, as the average operational age of the enterprise drives is only 2.11 months.

There are some insights we can gain from the current data. The enterprise drives have 363,282 drives hours and an annualized failure rate of 1.61%. If we look back at our data, we find that as of Q3 2016, the 8 TB consumer drives had 422,263 drive hours with an annualized failure rate of 1.60%. That means that when both drive models had a similar number of drive hours, they had nearly the same annualized failure rate. There are no conclusions to be made here, but the observation is worth considering as we gather data for our comparison.

Next quarter, we should have enough data to compare the 8 TB drives, but by then the 8TB drives could be “antiques.” In the next week or so, we’ll be installing 12 TB hard drives in a Backblaze Vault. Each 60-drive Storage Pod in the Vault would have 720 TB of storage available and a 20-pod Backblaze Vault would have 14.4 petabytes of raw storage.

Better Late Than Never

Sorry for being a bit late with the hard drive stats report this quarter. We were ready to go last week, then this happened. Some folks here thought that was more important than our Q2 Hard Drive Stats. Go figure.

Drive Stats at the Storage Developers Conference

We will be presenting at the Storage Developers Conference in Santa Clara on Monday September 11th at 8:30am. We’ll be reviewing our drive stats along with some interesting observations from the SMART stats we also collect. The conference is the leading event for technical discussions and education on the latest storage technologies and standards. Come join us.

The Data For This Review

If you are interested in the data from the two tables in this review, you can download an Excel spreadsheet containing the two tables. Note: the domain for this download will be f001.backblazeb2.com.

You also can download the entire data set we use for these reports from our Hard Drive Test Data page. You can download and use this data for free for your own purposes. All we ask are three things: 1) you cite Backblaze as the source if you use the data, 2) you accept that you are solely responsible for how you use the data, and 3) you do not sell this data to anyone. It is free.

Good luck, and let us know if you find anything interesting.

The post Hard Drive Stats for Q2 2017 appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

How to Use Batch References in Amazon Cloud Directory to Refer to New Objects in a Batch Request

Post Syndicated from Vineeth Harikumar original https://aws.amazon.com/blogs/security/how-to-use-batch-references-in-amazon-cloud-directory-to-refer-to-new-objects-in-a-batch-request/

In Amazon Cloud Directory, it’s often necessary to add new objects or add relationships between new objects and existing objects to reflect changes in a real-world hierarchy. With Cloud Directory, you can make these changes efficiently by using batch references within batch operations.

Let’s say I want to take an existing child object in a hierarchy, detach it from its parent, and reattach it to another part of the hierarchy. A simple way to do this would be to make a call to get the object’s unique identifier, another call to detach the object from its parent using the unique identifier, and a third call to attach it to a new parent. However, if I use batch references within a batch write operation, I can perform all three of these actions in the same request, greatly simplifying my code and reducing the round trips required to make such changes.

In this post, I demonstrate how to use batch references in a single write request to simplify adding and restructuring a Cloud Directory hierarchy. I have used the AWS SDK for Java for all the sample code in this post, but you can use other language SDKs or the AWS CLI in a similar way.

Using batch references

In my previous post, I demonstrated how to add AnyCompany’s North American warehouses to a global network of warehouses. As time passes and demand grows, AnyCompany launches multiple warehouses in North American cities to fulfill customer orders with continued efficiency. This requires the company to restructure the network to group warehouses in the same region so that the company can apply similar standards to them, such as delivery times, delivery areas, and types of products sold.

For instance, in the NorthAmerica object (see the following diagram), AnyCompany has launched two new warehouses in the Phoenix (PHX) area: PHX_2 and PHX_3. AnyCompany wants to add these new warehouses to the network and regroup them with existing warehouse PHX_1 under the new node, PHX.

The state of the hierarchy before this regrouping is shown in the following diagram, where I added the NorthAmerica warehouses (also represented as NA in the diagram) to the larger network of AnyCompany’s warehouses.

Diagram showing the state of the hierarchy before this post's regrouping

Adding and grouping new warehouses in the NorthAmerica network

I want to add and group the new warehouses with a single request, and using batch references in a batch write lets me do that. A batch reference is just another way of using object references that you are allowed to define arbitrarily. This allows you to chain operations, which means using the return value from one operation in a subsequent operation within the same batch write request

Let’s say I have a batch write request with two batch operations: operation A and operation B. Both batch operations operate on the same object X. In operation A, I use the object X found at /NorthAmerica/Phoenix, and I assign it to a batch reference that I call referencePhoenix. In operation B, I want to modify the same object X, so I use referencePhoenix as the object reference that points to the same unique object X used in operation A. I also will use the same helper method implementation from my previous post for getBatchCreateOperation. To learn more about batch references, see the ObjectReference documentation.

To add and group the new warehouses, I will take advantage of batch references to sequentially:

  1. Detach PHX_1 from the NA node and maintain a reference to PHX_1.
  2. Create a new child node, PHX, and attach it to the NA node.
  3. Create PHX_2 and PHX_3 nodes for the new warehouses.
  4. Link all three nodes—PHX_1 (using the batch reference), PHX_2, and PHX_3—to the PHX node.

The following code example achieves these changes in a single batch by using references. First, the code sets up a createObjectPHX operation to create the PHX parent object and attach it to the parent NorthAmerica object. It then sets up createObjectPHX_2 and createObjectPHX_3 and attaches these new objects to the new PHX object. The code then sets up a detachObject to detach the current PHX_1 object from its parent and assign it to a batch reference. The last operation uses that same batch reference to attach the PHX_1 object to the newly created PHX object. The code example orders these steps sequentially in a batch write operation.

   BatchWriteOperation createObjectPHX = getBatchCreateOperation(
        "PHX",
        directorySchemaARN,
        "/NorthAmerica",
        "Phoenix");
   BatchWriteOperation createObjectPHX_2 = getBatchCreateOperation(
        "PHX_2",
        directorySchemaARN,
        "/NorthAmerica/Phoenix",
        "PHX_2");
   BatchWriteOperation createObjectPHX_3 = getBatchCreateOperation(
        "PHX_3",
        directorySchemaARN,
        "/NorthAmerica/Phoenix",
        "PHX_3");


   BatchDetachObject detachObject = new BatchDetachObject()
        .withBatchReferenceName("referenceToPHX_1")
        .withLinkName("Phoenix")
        .withParentReference(new ObjectReference()
             .withSelector("/NorthAmerica"));

   BatchAttachObject attachObject = new BatchAttachObject()
        .withChildReference(new ObjectReference().withSelector("#referenceToPHX_1"))
        .withLinkName("PHX_1")
        .withParentReference(new ObjectReference()
            .withSelector("/NorthAmerica/Phoenix"));

   BatchWriteOperation detachOperation = new BatchWriteOperation()
       .withDetachObject(detachObject);
   BatchWriteOperation attachOperation = new BatchWriteOperation()
       .withAttachObject(attachObject);


   BatchWriteRequest request = new BatchWriteRequest();
   request.setDirectoryArn(directoryARN);
   request.setOperations(Lists.newArrayList(
       detachOperation,
       createObjectPHX,
       createObjectPHX_2,
       createObjectPHX_3,
       attachOperation));

   client.batchWrite(request);

In the preceding code example, I use the batch reference, referenceToPHX_1, in the same batch write operation because I do not have to know the object identifier of that object. If I couldn’t use such a batch reference, I would have to use separate requests to get the PHX_1 identifier, detach it from the NA node, and then attach it to the new PHX node.

I now have the network configuration I want, as shown in the following diagram. I have used a combination of batch operations with batch references to bring new warehouses into the network and regroup them within the same local group of warehouses.

Diagram showing the desired network configuration

Summary

In this post, I have shown how you can use batch references in a single batch write request to simplify adding and restructuring your existing hierarchies in Cloud Directory. You can use batch references in scenarios where you want to get an object identifier, but don’t want the overhead of using a read operation before a write operation. Instead, you can use a batch reference to refer to an object as part of the intermediate batch operation. To learn more about batch operations, see Batches, BatchWrite, and BatchRead.

If you have comments about this post, submit them in the “Comments” section below. If you have implementation questions, start a new thread on the Directory Service forum.

– Vineeth

Write and Read Multiple Objects in Amazon Cloud Directory by Using Batch Operations

Post Syndicated from Vineeth Harikumar original https://aws.amazon.com/blogs/security/write-and-read-multiple-objects-in-amazon-cloud-directory-by-using-batch-operations/

Amazon Cloud Directory is a hierarchical data store that enables you to build flexible, cloud-native directories for organizing hierarchies of data along multiple dimensions. For example, you can create an organizational structure that you can navigate through multiple hierarchies for reporting structure, location, and cost center.

In this blog post, I demonstrate how you can use Cloud Directory APIs to write and read multiple objects by using batch operations. With batch write operations, you can execute a sequence of operations atomically—meaning that all of the write operations must occur, or none of them do. You also can make your application efficient by reducing the number of required round trips to read and write objects to your directory. I have used the AWS SDK for Java for all the sample code in this blog post, but you can use other language SDKs or the AWS CLI in a similar way.

Using batch write operations

To demonstrate batch write operations, let’s say that AnyCompany’s warehouses are organized to determine the fastest methods to ship orders to its customers. In North America, AnyCompany plans to open new warehouses regularly so that the company can keep up with customer demand while continuing to meet the delivery times to which they are committed.

The following diagram shows part of AnyCompany’s global network, including Asian and European warehouse networks.

Let’s take a look at how I can use batch write operations to add NorthAmerica to AnyCompany’s global network of warehouses, with the first three warehouses in New York City (NYC), Las Vegas (LAS), and Phoenix (PHX).

Adding NorthAmerica to the global network

To add NorthAmerica to the global network, I can use a batch write operation to create and link all the objects in the existing network.

First, I set up a helper method, which performs repetitive tasks, for the getBatchCreateOperation object. The following lines of code help me create an NA object for NorthAmerica and then attach the three city-related nodes: NYC, LAS, and PHX. Because AnyCompany is planning to grow its network, I add a suffix of _1 to each city code (such as PHX_1), which will be helpful hierarchically when the company adds more warehouses within a city.

    private BatchWriteOperation getBatchCreateOperation(
            String warehouseName,
            String directorySchemaARN,
            String parentReference,
            String linkName) {

        SchemaFacet warehouse_facet = new SchemaFacet()
            .withFacetName("warehouse")
            .withSchemaArn(directorySchemaARN);

        AttributeKeyAndValue kv = new AttributeKeyAndValue()
            .withKey(new AttributeKey()
                .withFacetName("warehouse")
                .withName("name")
                .withSchemaArn(directorySchemaARN))
            .withValue(new TypedAttributeValue()
                .withStringValue(warehouseName);

        List<SchemaFacet> facets = Lists.newArrayList(warehouse_facet);
        List<AttributeKeyAndValue> kvs = Lists.newArrayList(kv);

        BatchCreateObject createObject = new BatchCreateObject();

        createObject.withParentReference(new ObjectReference()
            .withSelector(parentReference));
        createObject.withLinkName(linkName);

        createObject.withBatchReferenceName(UUID.randomUUID().toString());
        createObject.withSchemaFacet(facets);
        createObject.withObjectAttributeList(kvs);

        return new BatchWriteOperation().withCreateObject
                                       (createObject);
    }

The parameters of this helper method include:

  • warehouseName – The name of the warehouse to create in the getBatchCreateOperation object.
  • directorySchemaARN – The Amazon Resource Name (ARN) of the schema applied to the directory.
  • parentReference – The object reference of the parent object.
  • linkName – The unique child path from the parent reference where the object should be attached.

I then use this helper method to set up multiple create operations for NorthAmerica, NewYork, Phoenix, and LasVegas. For the sake of simplicity, I use airport codes to stand for the cities (for example, NYC stands for NewYork).

   BatchWriteOperation createObjectNA = getBatchCreateOperation(
                      "NA",
                      directorySchemaARN,
                      "/",
                      "NorthAmerica");
   BatchWriteOperation createObjectNYC = getBatchCreateOperation(
                      "NYC_1",
                      directorySchemaARN,
                      "/NorthAmerica",
                      "NewYork");
   BatchWriteOperation createObjectPHX = getBatchCreateOperation(
                       "PHX_1",
                       directorySchemaARN,
                       "/NorthAmerica",
                       "Phoenix");
   BatchWriteOperation createObjectLAS = getBatchCreateOperation(
                      "LAS_1",
                      directorySchemaARN,
                      "/NorthAmerica",
                      "LasVegas");

   BatchWriteRequest request = new BatchWriteRequest();
   request.setDirectoryArn(directoryARN);
   request.setOperations(Lists.newArrayList(
       createObjectNA,
       createObjectNYC,
       createObjectPHX,
       createObjectLAS));

   client.batchWrite(request);

Running the preceding code results in a hierarchy for the network with NA added to the network, as shown in the following diagram.

Using batch read operations

Now, let’s say that after I add NorthAmerica to AnyCompany’s global network, an analyst wants to see the updated view of the NorthAmerica warehouse network as well as some information about the newly introduced warehouse configurations for the Phoenix warehouses. To do this, I can use batch read operations to get the network of warehouses for NorthAmerica as well as specifically request the attributes and configurations of the Phoenix warehouses.

To list the children of the NorthAmerica warehouses, I use the BatchListObjectChildren API to get all the children at the path, /NorthAmerica. Next, I want to view the attributes of the Phoenix object, so I use the BatchListObjectAttributes API to read all the attributes of the object at /NorthAmerica/Phoenix, as shown in the following code example.

    BatchListObjectChildren listObjectChildrenRequest = new BatchListObjectChildren()
        .withObjectReference(new ObjectReference().withSelector("/NorthAmerica"));
    BatchListObjectAttributes listObjectAttributesRequest = new BatchListObjectAttributes()
        .withObjectReference(new ObjectReference()
            .withSelector("/NorthAmerica/Phoenix"));
    BatchReadRequest batchRead = new BatchReadRequest()
        .withConsistencyLevel(ConsistencyLevel.EVENTUAL)
        .withDirectoryArn(directoryArn)
        .withOperations(Lists.newArrayList(listObjectChildrenRequest, listObjectAttributesRequest));

    BatchReadResult result = client.batchRead(batchRead);

Exception handling

Batch operations in Cloud Directory might sometimes fail, and it is important to know how to handle such failures, which differ for write operations and read operations.

Batch write operation failures

If a batch write operation fails, Cloud Directory fails the entire batch operation and returns an exception. The exception contains the index of the operation that failed along with the exception type and message. If you see RetryableConflictException, you can try again with exponential backoff. A simple way to do this is to double the amount of time you wait each time you get an exception or failure. For example, if your first batch write operation fails, wait 100 milliseconds and try the request again. If the second request fails, wait 200 milliseconds and try again. If the third request fails, wait 400 milliseconds and try again.

Batch read operation failures

If a batch read operation fails, the response contains either a successful response or an exception response. Individual batch read operation failures do not cause the entire batch read operation to fail—Cloud Directory returns individual success or failure responses for each operation.

Limits of batch operations

Batch operations are still constrained by the same Cloud Directory limits as other Cloud Directory APIs. A single batch operation does not limit the number of operations, but the total number of nodes or objects being written or edited in a single batch operation have enforced limits. For example, a total of 20 objects can be written in a single batch operation request to Cloud Directory, regardless of how many individual operations there are within that batch. Similarly, a total of 200 objects can be read in a single batch operation request to Cloud Directory. For more information, see limits on batch operations.

Summary

In this post, I have demonstrated how you can use batch operations to operate on multiple objects and simplify making complicated changes across hierarchies. In my next post, I will demonstrate how to use batch references within batch write operations. To learn more about batch operations, see Batches, BatchWrite, and BatchRead.

If you have comments about this post, submit them in the “Comments” section below. If you have implementation questions, start a new thread on the Directory Service forum.

– Vineeth

Desert To Data in 7 Days – Our New Phoenix Data Center

Post Syndicated from Andy Klein original https://www.backblaze.com/blog/data-center-design/

We are pleased to announce that Backblaze is now storing some of our customers’ data in our newest data center in Phoenix. Our Sacramento facility was slated to store about 500 petabytes of data and was starting to fill up so it was time to expand. After visiting multiple locations in the US and Canada, we selected Phoenix as it had the right combination of power, networking, price and more that we were seeking. Let’s take you through the process of getting the Phoenix data center up and running.

Day 0 – Designing the Data Center

After we selected the Phoenix location as our next DC (data center), we had to negotiate the contract. We’re going to skip that part of the process because, unless you’re a lawyer, it’s a long, boring process. Let’s just say we wanted to be ready to move in once the contract was signed. That meant we had to gather up everything we needed and order a bunch of other things like networking equipment, racks, storage pods, cables, etc. We decided to use our Sacramento DC as the staging point and started gathering what was going to be needed in Phoenix.

In actuality, for some items we started the process several months ago as lead times for things like network switches, Storage Pods, and even hard drives can be measured in months and delays are normal. For example, depending on our move in date, the network providers we wanted would only be able to provide limited bandwidth, so we had to prepare for that possibility. It helps to have a procurement person who knows what they are doing, can work the schedule, and is creatively flexible – thanks Amanda.

So by Day 0, we had amassed multiple pallets of cabinets, network gear, PDUs, tools, hard drives, carts, Guido, and more. And yes, for all you Guido fans he is still with us and he now resides in Phoenix. Everything was wrapped and loaded into a 53-foot semi-truck that was driven the 755 miles (1,215 km) from Sacramento, California to Phoenix, Arizona.

Day 1 – Move In Day

We sent a crew of 5 people to Phoenix with the goal of going from empty space to being ready to accept data in one week. The truck from Sacramento arrived mid-morning and work started unloading and marshaling the pallets and boxes into one area, while the racks were placed near their permanent location on the DC floor.

Day 2 – Building the Racks

Day 2 was spent primarily working with the racks. First they were positioned to their precise location on the data center floor. They were then anchored down and tied together. We started with 2 rows of twenty-two racks each, with twenty being for storage pods and two being for networking equipment. By the end of the week there will be 4 rows of racks installed.

Day 3 – Networking and Power, Part 1

While one team continued to work on the racks, another team began the process a getting the racks connected to the electricty and running the network cables to the network distribution racks. Once that was done, networking gear and rack-based PDUs (Power Distribution Units) were installed in the racks.

Day 4 – Rack Storage Pods

The truck from Sacramento brought 100 Storage Pods, a combination of 45 drive and 60 drive systems. Why did we use 45 drives units here? It has to do with the size (in racks and power) of the initial installation commitment and the ramp (increase) of installations over time. Contract stuff: boring yes, important yes. Basically to optimize our spend we wanted to use as much of the initial space we were allotted as possible. Since we had a number of empty 45 drive chassis available in Sacramento we decided to put them to use.

Day 5 – Drive Day

Our initial set-up goal was to build out five Backblaze Vaults. Each Vault is comprised of twenty Storage Pods. Four of the Vaults were filled with 45 drive Storage Pods and one was filled with 60 drive Storage Pods. That’s 4,800 hard drives to install – thank goodness we don’t use those rubber bands around the drives anymore.

Day 6 – Networking and Power, Part 2

With the storage pods in place, Day 6 was spent routing network and power cables to the individual pods. A critical part of the process is to label every wire so you know where it comes from and where it goes too. Once labeled, wires are bundled together and secured to the racks in a standard pattern. Not only does this make things look neat, it standardizes where you’ll find each cable across the hundreds of racks that are in the DC.

Day 7 – Test, Repair, Test, Ready

With all the power and networking finished, it was time to test the installation. Most of the Storage Pods light up with no problem, but there were a few that failed. These failures are quickly dealt with, and one by one each Backblaze Vault is registered into our monitoring and administration systems. By the end of the day, all five Vaults were ready.

Moving Forward

The Phoenix data center was ready for operation except that the network carriers we wanted to use could only provide a limited amount of bandwidth to start. It would take a few more weeks before the final network lines would be provisioned and operational. Even with the limited bandwidth we kicked off the migration of customer data from Sacramento to Phoenix to help balance out the workload. A few weeks later, once the networking was sorted out, we started accepting external customer data.

We’d like to thank our data center build team for documenting their work in pictures and allowing us to share some of them with our readers.

















Questions About Our New Data Center

Now that we have a second DC, you might have a few questions, such as can you store your data there and so on. Here’s the status of things today…

    Q:Does the new DC mean Backblaze has multi-region storage?
    A:Not yet. Right now we consider the Phoenix DC and the Sacramento DC to be in the same region.

    Q:Will you ever provide multi-region support?
    A:Yes, we expect to provide multi-region support in the future, but we don’t have a date for that capability yet.

    Q:Can I pick which data center will store my data?
    A:Not yet. This capability is part of our plans when we provide multi-region support.

    Q:Which data center is my data being stored in?
    A:Chances are that your data is in the Sacramento data center given it currently stores about 90% of our customer’s data.

    Q:Will my data be split across the two data centers?
    A:It is possible that one portion of your data will be stored in the Sacramento DC and another portion of your data will be stored in the Phoenix DC. This will be completely invisible to you and you should see no difference in storage or data retrieval times.

    Q:Can my data be replicated from one DC to the other?
    A:Not today. As noted above, your data will be in one DC or the other. That said files uploaded to the Backblaze Vaults in either DC are stored redundantly across 20 Backblaze Storage Pods within that DC. This translates to 99.999999% durability for the data stored this way.

    Q:Do you plan on opening more data centers?
    A:Yes. We are actively looking for new locations.

If you have any additional questions, please let us know in the comments or on social media. Thanks.

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