Vmware, Inc.

Kashish Bhatia

Zubraj Singha

Goresh Musalay

Tanay Ganguly

Sachin Shinde

Randhir Singh

Prasanna Aithal

Vikas Suryawanshi

Kamal Jeet Charan

Akshay Jindal

The disclosure provides a method for handling heterogeneous input/output (I/O) load for containers running in a virtualized environment. The method generally includes receiving, from an application running in a container, an I/O indicating to write data to a persistent volume backed by a virtual disk file in storage, determining a maximum number of in-flight write I/Os allowed for the persistent volume based on a share of a total write I/O bandwidth assigned to the virtual disk file and allocated to the persistent volume, determining a current number of in-flight write I/Os for the persistent volume, and determining whether the current number of in-flight write I/Os for the persistent volume is greater than or equal to the maximum number of in-flight write I/Os allowed for the persistent volume to determine whether the received I/O is to be rejected or processed.

Method to handle heterogeneous input/output (I/O) load for containers running in a virtualized environment

A data structure tracks the usage of an eager-zeroed virtual disk on a per block basis and this data structure is referenced during migration or cloning of the eager-zeroed virtual disk so that copying of the zero blocks can be avoided. A method of migrating or cloning the eager-zeroed virtual disk stored in a first storage device comprises: determining for each of a plurality of unique sets of blocks using this data structure, whether or not any of the blocks in the unique set has been written to since the initialization of the virtual disk; and for each unique set determined to have at least one block that has been written to since the initialization of the virtual disk, issuing a copy command to make a copy of all blocks in the unique set in a second storage device.

Hypervisor-assisted migration or cloning of eager-zeroed virtual disks

The disclosure provides an approach for upgrading a virtual machine (VM) using an instant clone. A method includes initiating updating of the VM on a host in a datacenter; creating a clone of the VM on the host, in response to initiating the update; receiving a first write input/output (I/O) request for a first data block; checking a first disk bitmap associated with a first delta disk for whether a first bit associated with the first data block is set; based on the first bit being set, checking a scanner bitmap for whether a second bit associated with the first data block is set; and based on the second bit being set: waiting until the first data block is merged into a second disk; and performing the first write I/O to the first data block in the second disk after the first data block is merged into the second disk.

Update of virtual machines using clones

The disclosure provides a method for caching data. The method generally includes receiving, from an application running in a first container, an I/O to write data in a storage virtual disk to a block associated with an LBA, determining a cache is assigned to the first container and the storage virtual disk using a container mapping table comprising a first container mapping table entry mapping the first container and the disk to the cache and a second container mapping table entry mapping a second container and the disk to the cache, writing the data to the block in the storage virtual disk and to a cache block in the cache, computing a hash of the data, adding an entry that maps the LBA to the hash in an LBA table, and adding an entry that maps the hash to the cache block and to the disk in a hash table.

Centralized, scalable cache for containerized applications in a virtualized environment

Virtual memory space may be saved in a clone environment by leveraging the similarity of the data signatures in swap files when a chain of virtual machines (VMs) includes clones spawned from a common parent and executing common applications. Deduplication is performed across the chain, rather than merely within each VM. Examples include generating a common deduplication identifier (ID) for the chain; generating a logical addressing table linked to the deduplication ID, for each of the VMs in the chain; and generating a hash table for the chain. Examples further include, based at least on a swap out request, generating a hash value for a block of memory to be written to a storage medium; and based at least on finding the hash value within the hash table, updating the logical addressing table to indicate a location of a prior-existing duplicate of the block on the storage medium.

Saving virtual memory space in a clone environment

Example methods and systems to process input/output (I/O) requests in a distributed storage system in a virtualized computing environment are disclosed. One example method includes executing a first thread to destage one or more data writes, wherein the one or more data writes correspond to a first bucket; executing a second thread to destage the one or more data deletes, wherein the one or more data deletes correspond to a second bucket; in response to executing the first thread, buffering write I/Os associated with the one or more data writes in a logical queue; in response to executing the second thread, buffering delete I/Os associated with the one or more data deletes in the logical queue; and adjusting a number of slots in the logical queue dedicated to buffer the delete I/Os based on a relationship between the first bucket and the second bucket.

Method and system to process data delete in virtualized computing

Example methods are provided to identify unused memory regions in pages that are allocated for storing executable code. One or more of the unused memory regions are usable as a secure location to store confidential information shared between a hypervisor on the host and a guest (such as a guest virtual computing instance) that runs on the host. The one or more unused memory regions may also be used to store executable code (such as valid executable code of antivirus software or other security program) that has been prevented/delayed in its execution by malicious code that has occupied the pages, thereby providing the executable code with sufficient memory resources to enable the executable code to at least partially complete execution.

Hypervisor-assisted secured memory sharing among host and guest operating system

An example computing device includes a processor and a memory coupled to the processor. The memory may include a diagnostic daemon executing in a user space. The diagnostic daemon may include a plugin layer and a plurality of plugins communicatively connected to the plugin layer. Each plugin may perform at least one operation related to diagnostic data collection. The plugin layer may receive an event from a component running in the computing device upon the component encountering an error. The event may include a plugin identifier and an operation identifier. Further, the plugin layer may route the event to a plugin of the plurality of plugins based on the plugin identifier. Furthermore, the plugin may determine an operation to be performed corresponding to the component based on the operation identifier and execute the operation to collect a type of diagnostic information specified for the component.

Event-based diagnostic information collection

Supporting execution of a computer program by using a memory page of another computer program

Example methods and systems for input output (IO) request handling based on tracking information are described. One example may involve a computer system configuring, in a cache, a zero-filled logical memory page that is mappable to multiple logical block addresses of a virtual disk. In response to detecting a first IO request to perform zero writing at a logical block address, the computer system may store tracking information indicating that zero writing has been issued. In response to detecting a second IO request to perform a read at the logical block address, the computer system may determine that that zero writing has been issued for the logical block address based on the tracking information. The zero-filled logical memory page may be fetched from the cache to respond to the second IO request, thereby servicing the second IO request from the cache instead of the virtual disk.

Input output (IO) request handling based on tracking information

The disclosure provides an approach for implementing a deduplicated (DD) assisted caching policy for a content based read cache (CBRC). Embodiments include receiving a first input/output (I/O) to write first data in storage as associated with a first logical block address (LBA); when the first data is located in a CBRC or in a DD cache located in memory, incrementing a first deduplication counter associated with the first data; when the first data is located in neither the CBRC nor the DD cache, creating the first deduplication counter; when the first deduplication counter meets a threshold after incrementing, and the first data is not located in the DD cache, adding the first data to the DD cache; and writing the first data to the storage as associated with the first LBA.

Deduplication assisted caching policy for content based read cache (CBRC)

Disclosed herein is a system and method for checking and maintaining consistency of blocks stored in a virtual disk with a content based read cache (CBRC). When blocks are written to the cache and virtual disk, a hash is computed for the block and stored in a digest file on the virtual disk. In the background, each block is obtained from the virtual disk, its hash is recomputed, and the hash is compared to the stored hash in the digest file. If the comparison indicates a mismatch, then an error is reported.

Virtual disk file resiliency for content based read cache (CBRC) enabled environment

Methods and systems are disclosed for populating a fail-over cache. When host computer systems in a system each have a content based read cache, the methods and system provide several functions applied in different orders for determining blocks that are to be included in the fail-over cache. Each function attempts a different strategy for combining the contents of the caches of each host computer system into the fail-over cache. If any strategy is successful, then the fail-over cache is placed into service. If all of the strategies fail, then an eviction strategy is employed in which blocks are evicted from each cache until the combination of caches meets a requirement of the fail-over cache, which, in one embodiment, is the size of the fail-over cache.

Growing community of inventors

Bengaluru, India

Kashish Bhatia