Today marks a bittersweet moment as I say goodbye to Cruise. When I joined the company seven months ago, my mission was to scale the AV services worldwide and to modernize the AV and Cloud service developer platforms. Despite the unexpected challenges following the October incident, my journey at Cruise has been incredibly enriching, teaching me the true essence of resilience, adaptability, and commitment to excellence. ...
Twitter does provide notifications for when new users start following you. It does now however provide any notifications when users stop following you. Now, there is an ample of web sites out there who do provide that service, in most cases though, they cost money, and ask you for a complete access to your Twitter account. ...
All complexity needs to be abstracted, right? This reductionist statements misses nuance around the inherent cost/benefit tradeoffs, especially when you consider these over time. Don’t get me wrong, there often are good reasons for additional layers to make things simpler (grow adoption, lowering toil, removing friction, etc.). Still, these layers come at the long-term cost that’s often is not a part of the evaluation process. ...
We are entering a period where custom, highly-optimized, vertical solutions are becoming viable option again. This is a good news for ISVs with proven domain expertise and skilled development resources. Why do I think so? We now have: Plethora of feature-rich developer frameworks, message queues, scalable data stores, and even lower-level components in the OSS community with great documentation and a large number of use-case validation Growing number of custom solution companies (more than just ISVs) with existing deep vertical/domain expertise who are also increasingly now investing in hiring and training strong development teams Virtually every Cloud provider offering either a raw Kubernetes service or managed container execution platform which (regardless how you feel about these technologies) creates ubiquitous surface area that can be addressed with a single solution Yes, there still are many ways in which these custom development efforts can fail. Still, as one who has started their professional career developing custom software, I’m glad to see how these kinds of efforts are becoming cost effective again and increasingly represent a viable option for differentiation and real business value delivery. ...
I had the opportunity to attend Google Next this year. Week after this event I joined Google. Here are some quick notes in no particular order: Registration was a pain, long lines. My first tech conference where I had to go through a metal detector. Impressive reminder of the core tech underlining Google Cloud (i.e. Borg) and Google’s experience in operating at scale. Serious commitment to ML and Data Science: invest in talent/community (Kaggle), vision/leadership (Fei-Fei Li keynote), powerful APIs (i.e. Label/Face Detection, OCR, Explicit Content etc.) Feels like the ease of use for Google is more important than time time market (see the above DS APIs but also Spanner UX). Clear understanding of data economy’s potential value (goes with the scale comment but the experience was apparent in many sessions/keynotes) Open/partner market makes stronger platform (Sam Ramji’s keynote drilled on this best), early hints of this were probably the main reason why I wanted to join Google Cloud team. Size/quality of the network (both, cables & tech), globally distributed data systems (specifically latency) are perhaps the best example of the user value here.
Data is growing at an exponential pace. Based on recent numbers from IDC, the total amount of data in 2015 (4.4ZB) will grow to 44ZB in 2020. Franky, how much is in Zettabyte is almost inconsequential. It is the fact that all of the data generated since the beginning of time (at least the electronic part), will grow 10x in just the next four years that’s shocking! ...
The presentation that goes along with this post is available here In my last post I went over the value cycle of machine generated data. In this post, I want to follow up with a few ideas on how to further amplify value of that data by expanding its context beyond the walls of owning organization, in a construct we came to know as Data Exchange, and list a few innovation opportunities in each one of these areas. ...
The “high-priests” of Big Data have spoken. Hadoop Distributed File System (HDFS) is now the de facto standard platform for data storage. You may have heard this “heresy” uttered before. But, for me, it wasn’t until the recent Strata conference that I began to really understand how prevalent this opinion actually is. ...
We are in a midst of drastic shift in application development landscape. Developers entering the market today use different tools and follow different patterns. One of the core patterns of on-line application development today is cloud scale design. While traditionally architectures would rely on more powerful servers, today, that approach simply does not scale. We have reached that point where, in many cases, there are no powerful enough servers, or their cost would be prohibitive. Considering the unpredictable usage patterns today’s on-line applications also must be flexible to address demand spikes and assure efficient service during low utilization. ...
Over the last decade, the access to best-of-bread data technologies has become easier. This is due mainly to the increasing popularity of open source software (OSS). While this phenomenon holds true in other areas like operating systems, application servers, development frameworks or even monitoring tools, it is perhaps most prevalent in the area of data. ...