#ucberkeley

[soyarmenio]

UC Berkeley niega censurar una película armenia sobre la guerra de 44 días, aclarando que el aplazamiento fue por motivos logísticos en medio de acusaciones de presión política. https://soyarmenio.com/diaspora-armenia/berkeley-censurar-pelicula-armenia/

[engineeringpu]

Entrepreneurship at Plaksha | By UC Berkeley faculty Mark Searle

Mark Searle is an award-winning multiple-time startup and scaleup CEO & COO across multiple industries, in international enterprise and consumer markets. He is the Innovation Program Managing Director: Engineering & Business Schools, University of California, Berkeley. He is also an independent consultant, coach and mentor. He is teaching the Entrepreneurial Challenge Lab at Plaksha as a Visiting Faculty. In this video he talks about his experience teaching at Plaksha and how entrepreneurship at Plaksha is different.

[ceostroud]

A song from UC Berkeley made in 2013 - The original is live on SoundCloud :)

Go YC :)

Free trial :)

[great-photography-attributed]

Old Lovers By Thomas Hawk https://flic.kr/p/2qwxhrA

[andrew-excelleen]

Day at Work: Wedding Dress Designer

[govindhtech]

Filestore Powers Massive JupyterHub At UC Berkeley

Filestore powers one of the biggest JupyterHub deployments in US higher education at UC Berkeley.

What is JupyterHub?

JupyterHub, which makes Jupyter Notebooks more accessible to larger user groups, has emerged as a crucial platform for collaborative data science, enabling researchers, students, and developers to work together on challenging projects. The manner that data science education is delivered at scale has been completely transformed by its capacity to oversee numerous user contexts and grant access to shared resources.

However, these advantages are not without difficulties, as anyone who has worked on a large-scale JupyterHub implementation will attest. Managing file storage for a variety of users and computationally demanding operations soon becomes a major challenge as deployments scale. To guarantee seamless operations and effective workflows, storage solutions must be dependable, scalable, and performant.

UC Berkeley uses JupyterHub as a collaborative data science environment for students, teachers, faculty, staff, and researchers possibly the largest such deployment in American higher education. They employ Datahub, a highly customised Zero to JupyterHub implementation, which consists of more than 15 hubs serving 15,000 users across more than 35 departments and more than 100 courses. Naturally, punctuality and accessibility are critical as assignments and projects have due dates, and academic calendars control quizzes and examinations.

When UC Berkeley and Google initially began corresponding, UC Berkeley was very forthright about the difficulties of maintaining such a sizable and engaged user base, particularly given its limited resources. They experienced financial difficulties, similar to many other colleges, which made it challenging to staff a sizable IT team. Actually, a small team consisting of just two full-time employees was overseeing this enormous JupyterHub deployment, with the help of devoted volunteers and part-time workers.

It was soon evident that their current setup, which depended on user home directories that were self-managed and mounted on a self-managed NFS service that was hosted on Google Compute Engine, was not keeping up with the demands of the growing organisation. Their expanding user base required a more dependable and integrated experience, so they had to find a way to handle demand growth without sacrificing usability or speed.

Being a preeminent research university, they also had to strike a compromise between the demands of their constrained IT funds and the objectives of cross-departmental training. This is where the managed NFS storage solution Filestore from Google Cloud comes into play. Google hope that by revealing UC Berkeley’s path to Filestore, Google will be able to offer insightful analysis and useful advice to anyone facing comparable obstacles in their own pursuits.

What makes Filestore special?

The squad was operating in almost continual crisis mode when Shane joined it in October 2022. A surge of new Datahub customers in the middle of the semester taxed the capacity of the GKE architecture. Worse, the self-managed NFS service would frequently crash from overload.

By re-architecting the configuration to segregate particular course hubs and JupyterHub support infrastructure into their own node pools, the team was able to fix the GKE performance issues. For such users, this improved performance, but the underlying storage problems remained. One key point of failure had emerged: the self-managed NFS service. The team had installed a systemd timer that automatically restarted the NFS service every 15 minutes as a band-aid solution to keep things operating.

Although total disruptions were avoided, the self-managed infrastructure was still having difficulty keeping up. The user base continued to increase quickly, workloads were getting heavier, and the budget was just not able to keep up with the ongoing demand for additional servers and storage. They required a more economical and successful solution. At that point, they got in touch with the Filestore team and Google Cloud. The UC Berkeley team was persuaded that Filestore was the best option in less than an hour. Because the Filestore Basic HDD tier allowed them to customise instance size and was reasonably priced, they were especially intrigued in it.

It’s important to note that there are three Filestore tiers: Basic, Zonal, and Regional, and selecting between them isn’t always an easy choice before delving into UC Berkeley’s move. Although basic instances have limitations on capacity control (you cannot reduce capacity), they offer good performance. For workloads involving data science education that must be completed with minimal delay, zonal instances offer lightning-fast performance.

However, they are restricted to a particular zone within an area, as the name implies. In the event of an outage in that zone, the workloads may be affected. In contrast, Filestore Regional synchronously replicates data among three zones in a region to safeguard it in the event of a failure in one of the zones. The three of them trading places? Cost, flexibility in storage management, performance, and storage SLA. Selecting one of the three requires balancing performance with your level of patience for downtime. Budgetary constraints and capacity limitations will undoubtedly also be important factors in the choice.

Making the switch from Filestore to DIY NFS

Shane and his group were excited to test Filestore as soon as they had a firm grasp of it. They launched a demonstration deployment, establishing a connection between a Filestore instance and a smaller JupyterHub environment. Being the hands-on Technical Lead that he is, Shane jumped right in, pushing the system even further by running some bonnie++ benchmarks from within a single user server notebook pod.

Handling Filestore

Shane and his team at UC Berkeley have experienced a level of performance and stability they never would have imagined possible after switching to Filestore. They claim that Filestore is now a “deploy-and-forget” solution. Their users, those thousands of students who rely on Datahub, haven’t reported any performance concerns, and they haven’t had a single minute of outage.

Their management overhead has also been significantly decreased. They have a few basic Google Cloud alerts configured to interact with their current PagerDuty system and notify them in the event that any Filestore instance fills up to 90% of its capacity. These warnings are uncommon, though, and increasing storage when necessary is simple.

They have put into practice a straightforward yet efficient plan to further optimise their consumption and keep costs under control. They right-size their Filestore instances depending on usage trends after archiving user data to Cloud Storage at the conclusion of each semester. To make sure they are only paying for the storage they require, they either build smaller instances or combine hubs onto shared instances. For data migration between instances, Rsync continues to be their go-to partner. Although it takes time, this operation has become a standard component of their workflow.

In conclusion

The experience of UC Berkeley emphasises an important lesson for anyone implementing large-scale educational platforms as force multipliers for teaching: the complexity and volume of JupyterHub installations increase, and with them, so do the demands on the supporting infrastructure. Finding solutions that are both financially viable and technically sound is essential to success. Filestore proved to be that solution for Datahub, offering a potent combination of performance, reliability, and operational efficiencies and empowering the upcoming generation of data scientists, statisticians, computational biologists, astronomers, and innovators, despite the presence of some missing automation tools, a minor learning curve with Filestore Basic, and a higher price tag.

Read more on govindhtech.com

[thesabertoothwalrus]

[arlylelauren]

Going back to Berkeley always feels like Stevie returning to The Velvet Underground.

The sun sets on another day, another semester, another class year. To our graduates whose time on campus is coming to an end, remember that you will always be Golden Bears. Fiat lux and go bears! #ucberkeley #sathertower #campanile #myucberkeley by @abi_speers. (at UC Berkeley)

[yuumei-art]

Unreachable

Wandering mind, full of creation

Meandering lines, lost in elation 

Each stroke, I broke a little inside

Each fate, I hate. My will defied

I painted this in Feb 2022 about what it's like to be an artist with repetitive strain injury. In 2008, When I was 18, I made my first comic titled 1000 Words, it was about an artist helping a little girl with a broken family similar to my own. It received such positive feedback that I changed my Environmental Science major at UCBerkeley to Art major. Ever since then, my goal has been to tell stories with my art. Stories that are important to me. My next comic, Knite, was about a boy who wants to put the stars back into the polluted skies of China, my homeland. The comic after that, Fisheye Placebo, is a cyberpunk story about living in the age of technology, about fighting censorship and propaganda.

Unfortunately, I never got to finish Knite nor Fisheye Placebo. By the time I was 24, I was drawing day and night with no regards to my health. Not only did I get repetitive strain injury in my drawing hand, but my entire health suffered. My roommates had to rush me to the ER after fainting one night. I remember looking at my swollen right hand, my fingers like sausages, not even able to hold a pen, and just cry.

I've gone to the doctors and physical therapists. One told me I have Lupus (I do not), and another told me to put ice on it. More recently, I met a friend who happens to an amazing physical therapist and he was able to help me regain a lot of use of my hand. At my worst, I could only draw an hour a week, but now I am able to draw 2 hours a day. My hand is unlikely to fully heal, but I'm so grateful to regain what I have.

To my fellow artists who suffers the same, please know you're not alone. I can't promise that it'll get better, and it's cliche to say don't give up, but I want to keep hoping that no matter what the world throws at us, we will continue to make art.

[engineeringpu]

Chancellor Speak | Dr. Sastry on his appointment as Plaksha's Founding Chancellor

We are excited to announce that Plaksha University has appointed Dr. S. Shankar Sastry of the University of California, Berkeley, as the Founding Chancellor.

[great-photography-attributed]

Staying Power By Thomas Hawk https://flic.kr/p/2qixa1C

[insurgentepress]

Dura mestizaje entre neandertales 7,000 años en Europa y Asía

Un nuevo análisis de ADN antiguo de humanos modernos en Europa y Asia determina que el mestizaje con los neandertales comenzó hace 50,500 años y duró unos 7,000 años, así lo reveló un equipo de investigadores del @UCBerkeley.

Agencias/Ciudad de México.- Un nuevo análisis de ADN antiguo de humanos modernos en Europa y Asia determina que el mestizaje con los neandertales comenzó hace 50,500 años y duró unos 7,000 años. Ese mestizaje, que finalizó cuando los neandertales comenzaron a desaparecer, dejó a los euroasiáticos con muchos genes heredados de nuestros ancestros neandertales, que en total constituyen entre el 1% y…