Skip to main content

Windows 10 "Cannot update system reserved partition"

I've been using an earlier version of Windows 10 preview for a couple of weeks, and have been pleased with it. However when I tried to upgrade to a new drop, I was greeted with a cryptic message: "Cannot update the system reserved partition".


A little bit of research internally and on the Web exposed that the message appears when the system partition is full. To see the details of your drive: partitions, volumes and all, the command "diskpart" is your friend.





First list the volumes on the disk you're interested in:

diskpart> list volume


Some of the volumes might not have a drive letter associated with them. You can assign drive letters to the volumes you'd like to explore through


diskpart> select volume=N


Then assigning a drive letter through


diskpart> assign letter=E



Now you can look around the drive and figure out how to create some free space for the install, and all will be well.

Comments

Popular posts from this blog

Kindle Paperwhite

I have always been allergic to buying specialized electronic devices that do only one thing, such as the Kindle, the iPod, and fitness trackers. Why buy these when technology evolves so fast that a multi-purpose device such as the phone or a smart watch can eventually do the same thing, but with the convenience of updates that fix bugs and add functionality? So, I was shocked when this weekend I made an impulse buy and got the newest Kindle Paperwhite—a special purpose device for reading eBooks. I was walking past the Amazon store in the mall and saw that the newest Kindle Paperwhites were marked down by $40 for the holidays. The device looked good in the display, so I went in to look at it closely. The Paperwhite is small and light, with a 6” screen that is backlit and waterproof.   The text was crisp and readable, and in the ambient light, it felt like I am reading a printed book. I was sold and bought it on the spot. At home I have struggled to put it down. The bo...

A paper a day keeps the dr away: Dapper a Large-Scale Distributed Systems Tracing Infrastructure

Modern Internet scale applications are a challenge to monitor and diagnose. The applications are usually comprised of complex distributed systems that are built by multiple teams, sometimes using different languages and technologies. When one component fails or misbehaves, it becomes a nightmare to figure out what went wrong and where. Monitoring and tracing systems aim to make that problem a bit more tractable, and Dapper, a system by Google for large scale distributed systems tracing is one such system. The paper starts by setting the context for Dapper through the use of a real service: "universal search". In universal search, the user types in a query that gets federated to multiple search backends such as web search, image search, local search, video search, news search, as well as advertising systems to display ads. The results are then combined and presented back to the user. Thousands of machines could be involved in returning that result, and any poor p...

A paper a day keeps the doctor away: MillWheel: Fault-Tolerant Stream Processing at Internet Scale

The recent data explosion, and the increase in appetite for fast results spurred a lot of interest in low-latency data processing systems. One such system is MillWheel, presented in the paper " MillWheel: Fault-Tolerant Stream Processing at Internet Scale ", which is widely used at Google. In MillWheel, the users specify a directed computation graph that describe what they would like to do, and write application code that runs on each individual node in the graph. The system takes care of managing the flow of data within the graph, persisting the state of the computation, and handling any failures that occur, relieving the users from that burden. MillWheel exposes an API for record processing, that handles each record in an idempotent fashion, with an exactly once delivery semantics. The system checkpoints progress with a fine granularity, removing the need to buffer data between external senders. The authors describe the system using the Zeitgeist produ...